In an increasingly crowded adverse media landscape, location data associated with news stories can be particularly useful to compliance teams when it comes to accurately matching customer names and addressing compliance threats.
Given the clarity that it can provide, many firms are now integrating location data as a secondary identifier, in addition to identifiers such as dates, times, and monetary amounts. Location data has the potential to significantly enhance the customer screening process, offering a far greater level of coverage at scale for adverse media name searches.
Location-enhanced name searches can represent a valuable advantage in a challenging adverse media environment – not least in reducing the cost of false positive alerts triggered by the sheer volume of news stories. With that in mind, it’s time for compliance teams to explore the potential of location data to transform the accuracy and efficiency of their screening process.
What is location data?
When firms screen customers against adverse media, they use certain identifiers to help match names against stories, and develop a more accurate understanding of compliance risk. Location information is one of those identifiers: by extracting location data from stories, compliance teams increase the likelihood of a correct name match, and so enhance their anti-financial crime (AFC) compliance response.
Even when location data is only a small component of a given story, it may carry significant screening value. For example, if a search for a customer living in Scotland triggers an alert from a local news outlet, such as “The Cheltenham Echo”, it is unlikely that the story in question will be about the same person given the localised, southern-Midlands focus of the source, and so can be quickly remediated as a false positive.
It’s easy to underestimate the prevalence (and potential) of location data in media stories. Around 95% of media articles include some location component that carries value for compliance risk assessment. In this context, the term ‘location data’ may include:
Places referred to in the story itself
The place in which the story itself was filed
The place of media publication
The physical location or headquarters of the media outlet
Ripjar’s AI Risk Profiles feature, available as part of the Labyrinth Screening platform, offers further insight into the value of location data. Around 99% of AI Risk Profiles that include adverse media articles contain location information.
By using location data in combination and context with other indicators, compliance teams can significantly enhance its value in the name-matching process, and ultimately, in the accuracy of screening results.
What screening problems does location data solve?
Navigating the vast landscape of adverse media is a significant screening challenge. Firms must sort through huge volumes of data to find relevant risk information, while managing the associated noise, including duplicate stories or stories about people with similar names – all of which can drastically increase the false positive alert rate. Some of the most common location challenges include:
Frequent travellers: High profile customers, such as politicians, may travel around the world frequently and generate numerous news stories in the locations that they visit. This can confuse name searches and make it harder for compliance teams to get to the meaningful risk data that they need.
Name variance: Adverse media stories concerning the same topic may duplicate references to the same location, creating extra work for screening solutions: “Oxford’, for example, may also be referred to in stories as “Oxfordshire”, “Oxon” and “OX”.
Punctuation: Some location references include lots of punctuation, such as Manhattan, New York, New York. Complexity of punctuation may make it hard for screening solutions to identify the meaningful data.
By implementing context-driven searches which incorporate location data, compliance teams can cut through that screening noise, reduce false positives, and enrich their customer risk profiles.
Criminal methodologies
Location data isn’t just a ‘nice to have’ option for compliance teams. As criminal methodologies evolve, and regulators respond, firms must be able to keep up with a constantly evolving risk environment, embracing screening innovation wherever possible to meet compliance expectations..
With this challenge in mind, location data takes on an added significance – not just as a secondary identifier but as an integral component of compliance strategy, capable of transforming the accuracy and effectiveness of the name search process.
Regulatory trends and requirements
Beyond adverse media screening applications, financial regulators are zeroing-in on the potential of location data in wider compliance.
Since 2020, the US Office of Foreign Assets Control (OFAC) has required obligated entities to implement IP address geolocation screening measures, along with location-screening considerations as part of due diligence, for virtual currency firms. OFAC set out its location screening expectations in its paper: Sanctions Compliance Guidance for the Virtual Currency Industry. Similarly, in June 2024, the US Bureau of Industry and Security (BIS) added addresses to its watchlists, essentially prohibiting trade with entities at the designated locations.
It goes without saying that location data has always been critical in the enforcement of international sanctions, including OFAC’s programmes against Iran, Cuba, Venezuela, and so on. As that data becomes more available, and more functional, it’s likely that authorities around the world will seek to integrate it further into screening requirements – with adverse media screening a priority.
Who can benefit from location data screening?
All firms with anti-money laundering (AML) compliance concerns may benefit from integrating reliable location data into their screening process since it promises an extra layer of accuracy and confidence for the risk assessment process, while reducing the time and cost associated with false positive alert remediation.
Firms with particularly large retail client bases, stretched across multiple locations, may find even greater value, not least in enhancing the trust relationship between users of a particular platform and secondary service providers associated with it. In these contexts, identity matching must be more discerning to ensure it functions effectively at the largest scales.
Travel aggregation sites, for example, offering products and services in multiple global locations will benefit significantly from that enhanced trust metric. Online accommodation exchanges will be able to enhance the trust and confidence between both guests and hosts, while simultaneously offering expedited onboarding and smoother payment processing. Meanwhile, retail banks and B2C tech companies that trade internationally also stand to benefit from enhanced location screening capabilities.
Like regulators, industry bodies have begun to pick up on the potential advantage of location data. Events like TrustCon, for example, offer forums where experts can discuss innovations, including advanced adverse media screening.
Next Generation Location Screening with Ripjar
With screening solutions powered by industry-leading AI technology, Ripjar is harnessing the power of location data to keep our clients at the cutting edge of financial crime compliance.
In the latest upgrade to the Labyrinth Screening platform, we integrated additional enhanced location data analysis capabilities, designed to help compliance teams build out rich, detailed customer risk profiles and significantly reduce the potential for false positive alerts. Our screening technology integrates AI algorithms to identify and extract relevant information from both structured and unstructured data sources, and facilitate faster, stronger compliance decisions.
Labyrinth’s location data analysis also offers valuable flexibility, automatically adjusting name match scores based on the population of a given location. A search for “John Smith” in Cheltenham, for example, would deliver a higher score than a search for “John Smith” in London, given the disparity in population and the lower number of “John Smith” names in the former location. The system combines that feature with frequency of names appearing in media screening results to determine the likelihood of a correct match, and assign an accurate score.
Labyrinth Screening Location Test Results
Our location data identifiers are achieving real-world screening results, at scale, in a complex and challenging adverse media landscape. In an early trial by a US-based technology company involving 1.2 million people registered with address data, location-enhanced Labyrinth Screening achieved over 90% true positive accuracy in its top screening hits.
The company highly values internal trust between its service providers and its clients, and so needs as smooth a screening process as possible, that preserves the user experience. The trial demonstrated Labyrinth’s capacity to deliver that type of media screening at scale. In the riskiest 3,000 of the customer names screened, the upgraded system revealed the following AML compliance risks:
The manufacture of illegal or controlled drugs
Organised criminal trafficking of drugs
Attempted murder
Prostitution of a minor
A charge of armed robbery and aggravated battery causing harm
Using a combination of location data and name-frequency, the upgraded Labyrinth Screening process not only delivered a higher rate of exact identity matches but enabled the tech company to permanently remove many of the highest risk accounts.
Good news is usually good for business, but in a crowded media landscape, many banks and financial institutions miss potentially high-value news stories about their clients or prospects, even when they’re looking for them. These types of positive news stories can represent potentially valuable business opportunities, which is why it makes sense to have a means of identifying them as they emerge – in the same way that a firm screens for negative news to protect against compliance risk.
In this context, freed from a regulation-mandated classification as ‘adverse’ or ‘negative’ news media, the stories can be classified as ‘positive’ news.
To get the most out of positive news screening, firms need to understand what they’re looking for, and how they can leverage their existing tech stack or engage new technology to bring in the kind of stories they want.
What is Positive News?
Positive news essentially refers to any story about an existing or potential client that holds some prospect of value for a financial institution. Positive stories can involve a range of business-relevant developments or events, including:
A rumoured sale or acquisition
An upcoming client profile in a leading news publication
A client’s nomination for an industry award
An award of a royal warrant
A new investment
A new product release
An IPO
Expansion in a new region
Stories involving high wealth individuals are just as valuable, including news about lucrative promotions, inheritances, marriages, family events, or any circumstance that might generate an opportunity to invest money.
What is Positive News Screening?
Positive news screening describes the process of actively searching for positive stories about existing clients or new prospects, in order to generate new business. It is especially prevalent in private banking, wealth management, and banks with high net worth clients, but is growing in application across a range of banks and financial institutions who are recognising the benefits it offers.
Many banks already implement a positive news screening solution via a team of researchers, sometimes known as a Client Development Team, who manually scour the internet for positive news information. When a potential opportunity is identified, the team works to verify the story, and establish a line of communication. This manual approach shares common ground with manual negative news screening, including its time-consuming inefficiencies such as difficulties scaling, human error, and ongoing drain on employee time and attention.
Like manual negative news screening, manual positive news searches are increasingly unsuitable for dealing with 21st century data burdens. If your firm is struggling with manual search inefficiency, it’s time for a new approach to positive news.
Understanding the Positive News Screening Process
Under risk-based compliance regimes, most banks and financial institutions integrate technology to screen customers against negative news. Covering global news sources, screening technology solutions deliver financial intelligence that can be used to build-out detailed customer risk profiles and inform compliance decisions.
Positive news screening solutions are built on the same screening technology. Rather than identifying risk indicators, such as a customer’s sanctions designation or political exposure, positive solutions instead identify indicators that the customer has or could become a financial prospect.
The functional components and techniques of positive screening are not substantially different to the negative screening process. Positive news teams use existing adverse media risk classifiers alongside additional ones to capture positive indicators, including sources of wealth, or ultimate beneficial ownership (UBO), and then develop leads to open up new business opportunities. The underlying software is also the same, and functions by linking individuals and entities to particular categories of news story.
Why Screen for Positive News?
Demand for new financial opportunities typically drives positive news screening efforts, but it’s important to understand the wider benefits of the process, and how it adds value to businesses.
Data Value
Negative news screening is often characterised as a ‘needle in a haystack’ process, with teams working through vast amounts of irrelevant data – only a fraction of which is eventually useful for compliance decision-making.
In implementing an effective positive news solution, firms can transform the value and efficiency of their data collection process by making a much greater proportion of that data relevant to their business objectives.
Applying Innovation
Cutting-edge screening technology, such as generative AI (GenAI) enabled search tools, may initially be applied in only a limited capacity if their use is restricted to risk screening. Natural language processing (NLP) systems, for example, use sophisticated algorithms to identify compliance risk in unstructured data such as news articles or social media posts.
Those compliance assets are capable of identifying and processing positive news from those same media sources – with the same speed, efficiency, and quality of intelligence output. Implemented effectively, positive screening not only increases the value of technology for firms that lean in to innovation, but delivers a potentially important competitive edge.
Opportunity Profiles
Customer risk profiles essentially collate important risk data, such as a subject’s political exposure, their connection to organised crime, sanctions designations, and so on. Compliance teams use these profiles to efficiently map and understand a given target’s risk level, and use that insight to make better decisions.
However, customer profiles don’t have to be limited to risk insight. In a solution designed to capture positive news, screening software is tasked to generate customer ‘opportunity profiles’ which collate positive data points, and outline the potential benefit of pursuing the target as a partner.
Risk vs Reward
In risk-based compliance regimes, screening outputs are assessed against a firm’s risk appetite. Positive screening outputs add a new metric to that process, delivering new insight that allows firms to assess customers on a scale of risk to reward. The more depth and detail the screening process generates, the more accurately a firm can balance the risk and reward of a potential business relationship.
Customer Documentation
The more a firm knows about its customers, the more it can do to create better business outcomes. Positive news screening outputs, in the form of summary briefings, photographs, or news snippets, can be easily extracted and transferred to electronic or physical documents, which can be circulated internally and used to help improve the customer relationship.
AI Topic Classification
AI search tools typically apply topic classifiers to help identify and process adverse media. Compliance teams run searches calibrated for certain topics such as ‘Financial Crime’, ‘Bribery and Corruption’, and ‘Corporate Malfeasance’ – which are further categorised by ‘Personal’ or ‘Business’ risk.
Positive news solutions use exactly the same approach, either repurposing existing classifiers such as ‘Source of Wealth’ or adding new ones that capture opportunity instead of compliance risk. These opportunity classifications may cover story topics such as ‘Business Development Projects’, ‘Entrepreneurship’, ‘Philanthropy’, and ‘ESG and Sustainability’.
Increasing Compliance Value
It’s easy to view compliance simply as a cost-burden which provides value only by helping the company avoid regulatory penalties. By generating meaningful opportunity-intelligence, however, positive screening changes the profile of the compliance function: money spent on strengthening risk screening capabilities now also strengthens a firm’s capability to identify potentially lucrative new leads, and emphasises the skills and expertise of senior compliance personnel.
Seize Your Opportunities: Ripjar Positive News Screening
Ripjar’s Labyrinth Screening platform provides industry-leading client screening capabilities for organisations around the world, generating actionable financial intelligence in seconds to ensure strong decision-making in a complex data landscape.
Labyrinth’s positive news screening capabilities match that speed, depth, and accuracy, enabling client name searches of thousands of global media sources, in real-time, and in multiple foreign languages. Integrating cutting-edge AI analytics, Labyrinth helps firms build out rich, detailed customer profiles from only the most relevant positive news data, and uses GenAI technology to create concise summaries of the most valuable opportunity insight.
In Ripjar’s recent “Secrets to Effective Adverse Media Screening” AI masterclass, our speakers discussed what financial institutions need to consider when designing and deploying an effective adverse media solution. With over 90% of attendees conducting it, either manually or automated, it is clear that adverse media screening is a key pillar of customer due diligence.
Although simple in theory, implementation can lead to large numbers of irrelevant hits. With 41% of attendees stating that adverse media false positives are one of their greatest challenges, firms need to be smarter about how they deploy their resources to target risks.
Tech-led tools and automated solutions can help reduce manual efforts and meet regulatory requirements. When implemented correctly, adverse media screening brings many benefits:
Meeting regulatory requirements to identify high-risk clients and counterparties
Identifying potential reputational risk issues
Acting as an early warning system for potential risk exposure
Considerations for implementation
Using traditional, unstructured adverse media databases and search engines means reading, digesting and interpreting information in a manner which is time-consuming, costly, and may lead to making decisions without the best available information. With over one third of masterclass attendees currently conducting adverse media screening manually, the move to an automated solution is often not a simple matter of ‘plug-and-play’. Considerations include:
The risk-based approach
The risk-based approach recognises that the risk profile of firms’ offerings and customers varies widely, and risk mitigation measures need to be proportionate. Industry guidance from the Wolfsberg Group highlights the need for a proportionate screening approach directly linked to a firm’s size, geographical presence, customer type and products offered. For example, what is right for a domestic financial institution versus a large global firm may not be the same. Firms should use their risk appetite and expectations from senior management and regulators to map their approach to how they screen customers. For example, do they want to know everything about all clients or only financial crime-focused information for those who are high-risk?
Is there a “one size fits all” approach?
With over 16% of attendees stating that managing regulatory change over multiple jurisdictions was a challenge, the integration of adverse media screening could be less complex if you have a single global process. Where possible, the solution, approach and process should be global-led with adjustments for various jurisdictions. For example, if one jurisdiction requires only high-risk clients to be screened, and another requires screening for all clients, the tool and process can be the same but the ‘who’ and ‘what’ you screen can be different.
The who, what and when
Given the vast extent of unstructured data available, defining the sources you use for the clients you wish to screen is crucial. These can be categorised into buckets:
Collated structured data e.g. Dow Jones sanctions and PEP lists
Collated unstructured data e.g. Factiva media database
Uncollated unstructured data – much of the rest of the web
You can target the sources used for screening by leveraging other data points you have. For example, if you have a UK client that only trades domestically you may only screen them against UK sources, however, if you have an international client trading globally you may want to screen them globally to get a full picture of potential risks.
Other considerations include:
When should screening be conducted (e.g. daily, weekly or trigger-based)?
Who is screened (e.g. all customers or only certain groups? Customers only, or also UBOs, counterparties, suppliers etc.?)
How is screening conducted (e.g. periodic, batch, or ongoing)?
Which findings are relevant (e.g. certain types of predicate offences or reputational issues may be irrelevant)?
Which media sources are credible (e.g. newspaper articles, online forums, blogs, social media)?
Looking for the right solution
Before procuring a solution, understand your organisation’s screening processes thoroughly. Assess if processes are heterogeneous or uniform to help assist implementation. Define your requirements and map them against the solutions and expertise that a vendor can bring, to address any gaps in your framework. Vendors will not understand your internal process flows so it is important you know how the tool will integrate with existing tools and processes, and can determine if you have the right internal skills to support implementation.
The people are important
Nearly 20% of masterclass attendees noted that finding the right resources and skills to deal with the outputs of adverse media screening was a key challenge for them. When managing alerts, people need to be good at both identifying the key risks within an alert and understanding the materiality of these risks in the context of the relationship that you have with that client. Rather than a specific background or role experience, prioritise hiring people with good analytical, critical thinking and communication skills.
The devil is in the detail
When firms look at the tools employed to assist with screening, they must have well-defined and structured parameters; otherwise, they risk returning too many irrelevant findings or missing vital information.
Think about the matching criteria
There are many different properties that can be used to generate an adverse media screening match. Adding new variants increases the opportunity for effectiveness, but it can also reduce efficiency. The broader your parameters, the more likely the system will find a relevant risk, but with a greater chance of being inundated with a lot of false positives.
Having the capability to consider various factors such as culture, script and origin, and ensuring the accuracy of matches is crucial. Depending on data quality, flexibility becomes essential; data might contain errors due to operator mistakes or intentional name alterations by the client. Having access to diverse matching variations is vital in such cases. Comprehensive matching requires the availability of multiple options to accommodate varying data qualities and scenarios. By considering additional identifiers such as entity type, gender, age or date of birth, nationality, and location can further streamline results.
The positives of false positives
False positives can be useful – if you understand what is driving false positives you can use this to provide feedback and correlate the outputs to the risks you want to see. You should also look at false negatives to identify if you are missing information that is relevant and could directly impact your risk. Reviewing these to understand why certain information is being picked up and some isn’t is key in balancing efficiencies vs risk mitigation.
Driving efficiencies
Getting the balance right in optimising outputs is often an iterative process but there are some steps firms can take to make a more immediate impact.
Decrease the fuzziness
The obvious answer is decreased fuzzy matching levels but, with many screening systems, this can have an impact on effectiveness. You need to decide what level of recall you expect and the relevance of matches you expect to see, and balance this accordingly. Test different matching levels and see which returns an optimal number of results without missing true hits.
Reduce the volume of data
Conduct targeted screening by defining the client segment you wish to screen against the types of risks you are interested in. This customisable approach enables tailored risk management by segment and risk interest. You can also reduce the volume of alerts by deduping clients at name level, creating ‘whitelists’ or being smarter about how you deal with larger global names who may trigger more alerts than other clients.
Improve the data
Continuously enhancing your adverse media screening quality involves refining attributes. This includes addressing name rarity, eliminating aliases, and mapping relationships mentioned in articles, such as familial ties, to ensure comprehensive profile accuracy. These measures are a value-adding way to refine and optimise screening results.
The power of AI
The conflict of doing too much with artificial intelligence (AI) and machine learning (ML) versus not doing enough is the dichotomy for many financial crime professionals today. With only 10% of masterclass attendees currently using it for adverse media screening, it is clear that there is much more scope for its use.
Alongside more traditional ML and AI, new generative AI models are able to solve broad sets of problems, creating more opportunities for its use, such as Ripjar’s Compliance Copilot. There is a huge potential in having these types of AI and ML support analysts in reviewing cases and becoming more efficient by finding more relevant information without being bogged down in unrelated information.
When deciding which is the right approach, you may conclude it is not just one type of ML or AI that you want to use; it might be a blend of different approaches to tackle the right tasks in the right way. Once you implement your chosen solution(s) you need to ensure you build the right model governance to ensure that bias does not creep in, and to showcase to the regulator and your internal stakeholders how it works and how it is performing. You will also need to consider how to keep it relevant and determine what your long-term plan is to retrain and update it as applicable.
Conclusion
Whatever solution you implement for adverse media screening, it is important that it drives the right outcomes for the risks you are trying to identify and manage. Understanding the scope of who and what you screen, optimising the technology that you use to reduce false positives, and having the right skills to manage the outputs are key considerations when deploying adverse media screening.
Adverse media screening is critical to the global fight against financial crime but in an ever-changing risk landscape, firms should always be prepared for new challenges. With that goal in mind, in 2023, Ripjar conducted research into the adverse media challenges faced by global anti-financial crime professionals, in order to derive statistical data about their concerns and expectations for the future.
News media and other online media sources such as blogs, forums, and social media posts, are particularly useful for anti-money laundering (AML) and counter-financing of terrorism (CFT) strategies because they typically reveal customers’ true risk levels before that information is confirmed by official sources. However, the adverse media landscape is constantly changing, with the pace of breaking news stories forcing firms to adjust their compliance posture quickly to manage new risks.
The scope of risk-based AML/CFT regulations means that firms must carefully consider how to implement their adverse media screening solutions, including which technology tools they should integrate, and how their strategies need to change in the short and long term. Ripjar’s State of Adverse Media Screening 2023-2024 report examines that landscape, exploring the contemporary screening challenges that firms face, and how new technology is changing compliance processes.
The report comprised a survey of 205 compliance professionals from different industries and across the EMEA region. In this article, we take a closer look at key insights from the survey, and how automated screening solutions can help firms address these challenges in 2024.
2024’s Key Adverse Media Screening Challenges
Our survey identified the following key challenges faced by respondents looking to implement adverse media screening solutions in 2024:
Resource and Budget Constraints
Effective adverse media screening requires firms to address compliance risk by allocating sufficient budget, resources, and employee focus to the relevant tasks. However, balancing screening costs with AML/CFT compliance obligations can be challenging: manual screening, for example, using internet search engines (such as Google or Bing) to check customer names, may be the cheapest approach but is typically time-consuming, inconsistent, and prone to costly human error. With almost 50% of firms believing that the challenge of keeping in step with regulatory change will increase, automated screening solutions represent a time and cost efficient alternative to outdated manual processes. However, automated tools are not necessarily a one-size-fits-all solution and must be integrated within a wider compliance infrastructure and calibrated to meet individual risk appetites.
False Positives
While adverse media screening should help firms identify risk as comprehensively as possible, the process can generate a high volume of false positive alerts as a result of similar sounding names, ambiguities in search parameters, or linguistic factors (such as non-Western naming conventions). False positive alerts can be costly since they must be remediated in order to address potential risk – a process which takes time and resources, and slows down the wider compliance function. Given that 40% of firms believe that the problem of dealing with false positive alerts will increase in 2024, compliance teams should seek to integrate technology solutions to help reduce that burden – including AI tools capable of making sense of unstructured data, and even using secondary identifiers to help resolve customer identities.
Technology and Data Integration
Adverse media screening is only as good as the technology that supports it. In practice, this means that firms must understand how tech innovations in screening will fit and function within their wider compliance infrastructure in order to meet their AML/CFT compliance obligations. Similarly, compliance employees must ensure that the data they feed into screening solutions is of sufficient quality to generate meaningful financial intelligence, and to enable effective risk decision making.
Regulatory Change
AML/CFT screening solutions are shaped by regulation. However, the global regulatory landscape is in a state of constant change as governments work to keep pace with evolving technology and criminal methodologies. This means that firms must maintain a perspective on incoming regulations, and consider how they will need to adjust their screening solutions to meet new compliance standards. In our survey, 47% of firms believed that the challenge of keeping up with incoming regulations would increase in the future.
Adverse media screening is currently an obligation in a number of jurisdictions – for example, it is included in the EU’s 6th Anti-Money Laundering Directives (6AMLD). Since adverse media screening typically involves the use of customers’ personal data, firms must also be aware of local privacy regulations, such as the EU’s GDPR.
How Will Screening Challenges Change?
In addition to revealing their key adverse media screening challenges, our survey asked firms which adverse media challenges would be most likely to increase in the future. Our respondents identified 3 top challenges:
Keeping up with new regulations: 47%
Managing the complexity of new technology solutions: 41%
Receiving too many irrelevant alerts (false positives) 40%
The challenges identified emphasise the need for firms to maintain perspective on the regulatory and screening technology horizons, reviewing their compliance infrastructure regularly in order to identify potential weak points, or opportunities to strengthen.
Current Screening Strategies Being Used in 2024
The challenges outlined in the 2023-2024 report offer the following insight into the screening strategies that firms currently use to meet their compliance obligations – along with attitudes and expectations about the impact of screening technologies.
Reliance on Manual Screening
While automated screening solutions are available and accessible in 2024, a surprising 84% of firms remain reliant on manual screening processes. As noted above, the slow speed and unreliability of manual searches makes them unsuitable for fighting modern financial criminal threats, and firms using them exclusively may be exposing themselves to unacceptable levels of risk. Similarly, as competitors integrate new screening innovations, firms that rely on manual screening may see customers drop off in favour of more efficient alternatives.
Tech Integration
Given that 90% of firms want to increase their use of screening automation, it’s likely that there will be integration challenges in the coming years. 39% of surveyed firms identified the integration of new screening technology into existing infrastructure as their biggest challenge – which means that compliance teams will need to carefully consider how a given innovation adds value to their organisation. Similarly, firms will need to think about whether new technologies match their budgetary needs and risk appetite, and whether they should be run internally, or by a third party service provider.
Evolving Capabilities
While automated compliance solutions offer enhanced accuracy, efficiency and speed, recent innovations, in particular artificial intelligence and machine learning tools are revolutionising the adverse media screening landscape. Large language models (LLM) and generative AI (GenAI) appear to hold particular promise, with the potential to screen vast amounts of data in seconds and extract the most relevant information. It can be overwhelming to consider how the potential application of AI will impact screening processes since both its regulatory implications and screening capabilities have not been fully tested.
For example, in our survey, 70% of firms were confident that LLMs will be able to identify high-risk individuals. That statistic clashes with many current experiences of LLMs, many of which generate incorrect outputs, or even fabricate responses to certain prompts. What’s clear is that GenAI used in a screening setting must be developed specifically for the task and thoroughly tested to ensure accuracy of output – not all LLM technology will be appropriate for screening use without significant constraints being put in place.
Regardless of industry attitudes, the clear regulatory potential of AI technology, and the current pace of advances, means that industry focus on integration of screening functions will increase in the short to medium term.
How Automation Will Change Adverse Media Screening in 2024
Despite the challenges currently facing tech integration in adverse media screening functions, there are plenty of ways in which automation can have a qualitative impact, and enhance the compliance process. Key areas in which automation is likely to have an impact on adverse media screening in 2024 include:
Skills Shortages
The compliance function can place a significant amount of pressure on employees, in particular in the finance sector, where regulations often carry strict penalties. The ‘Great Resignation’ has seen skilled employees leave finance roles in positions around the world, with firms struggling to make up the shortfall. Automated screening tools can directly address that challenge by bringing speed, accuracy, and efficiency to the process, reducing the potential for human error, and freeing up compliance employees from tedious manual work, such as data entry, for more valuable assignments.
Data Analysis
AI technologies such as LLMs are effective at interpreting unstructured media data in multiple languages, which is essential in adverse media screening. However, they are not suited to identity-matching and other key screening requirements. With the right mix of AI and machine learning techniques, firms can sort through this risk-related data in seconds, summarising and formatting the information in order to enable stronger, faster decision-making.
Risk Profiles
With the benefit of machine learning and natural language processing technology, AI screening tools can be tasked with extracting the most relevant data about subject entities, and then using that data to build unique risk profiles for each customer. Enriched with specific depth and detail, customer data not only helps to identify true risk, but reduces the potential for false positives by helping to distinguish customers with similar or exact-matched names. In the same way, AI tools can help firms account for multilingual screening challenges, including non-Western naming conventions and characters, or the use of nicknames or aliases.
Labyrinth Adverse Media Screening
Ripjar’s Labyrinth Screening platform is a powerful adverse media screening solution built on next generation machine learning technology. Capable of searching thousands of global adverse media sources across multiple languages, including news stories, blog and social media posts, sanctions lists, and watchlists, Labyrinth Screening generates actionable financial intelligence in seconds, helping compliance employees make faster, stronger decisions about customer risk.
Labyrinth also incorporates AI Risk Profile technology, extracting the most relevant risk data about subject entities in order to resolve ambiguities and reduce false positive alerts. Our AI Risk Profiles solution uses intuitive AI to remove noise from customer name searches. The technology addresses the challenge of common and high profile name matches, and of duplicated story subjects, while adding secondary identifiers to each profile so that compliance employees have the information they need to assess risk at their fingertips.
AI Summaries is a new feature available within AI Risk Profiles that uses GenAI to add a clear, concise summary of adverse media risk to each customer profile, resulting in a 90% reduction in customer assessment time.
The Hong Kong Monetary Authority (HKMA) is responsible for protecting Hong Kong’s financial system. In that role, it works with the city’s banks and financial institutions to detect and address criminal threats such as money laundering, often with a focus on the integration of innovative technology solutions. The strategy is part of HKMA’s Fintech 2025 initiative and has helped make Hong Kong a global hub for regtech adoption, with around 85% of the city’s banks integrating some form of regtech to manage their anti-money laundering (AML) compliance needs in 2023.
Exploring AML Insight
The HKMA’s approach to regtech integration evolves to meet emerging risks. In 2021, the regulator published its inaugural Case Studies and Insights paper as a way of exploring the ways in which Hong Kong financial institutions are deploying technology to address AML risk, and ultimately enhancing the city’s collective response to financial crime.
In Case Studies and Insights Volume 2, published in September 2023, the HKMA included a case study which focused on the integration of an innovative, AI-powered news monitoring solution with natural language processing (NLP) technology that had helped a Tier 1 Hong Kong bank enhance its AML adverse media screening process. The study highlights the significant challenges that banks face when screening individual customers – in particular the friction and inefficiencies of collecting and analysing global adverse media, or negative news, for critical risk information.
Let’s take a closer look at the HKMA’s case study to find out how cutting-edge AI technology tools can help financial institutions in the APAC region not only address their screening challenges but boost their overall AML compliance response.
Adverse Media Screening Challenges
The risk-based approach to compliance required by the HKMA (following FATF guidelines) means that financial institutions in the country must build out risk profiles with enough information to facilitate effective decision-making about the AML risk that customers present. For international banks, this requirement entails searching customer names across a global media landscape, and dealing with a multitude of emergent screening problems that not only complicate the screening process with noise and false positive alerts, but also degrade products and services.
The case study bank implemented its screening platform to help it overcome common challenges associated with adverse media screening, including:
Speed and accuracy:Manual screening via search engines or other methods is slow and likely to miss key risks in vast quantities of media data.
Credibility of data: Many negative news screening solutions fail to effectively filter out low quality results from sources such as such as social media or personal blog posts.
Misidentification and duplication: Duplication of news stories and false positive alerts can significantly affect screening speed and effectiveness, as compliance teams work through alerts to filter relevant data.
Multi-language matching: Global adverse media screening must not only be able to detect customer names in news stories in multiple languages, but also account for the translation, transcription, and transliteration of names, plus the use of different characters, regional naming conventions, and so on.
Overcoming Multi Language Screening Challenges with AI
The Hong Kong bank needed a solution that would help it overcome the specific challenges of global negative news screening (outlined above), while generating more flexible, impactful risk data that could make a meaningful difference to its compliance performance and help it deliver services at the level expected of a Tier 1 institution.
Software integration offers a way to address many efficiency-related screening challenges since automated search algorithms are capable of processing data faster, more accurately, and in greater volumes, than manual screening. However, automation doesn’t completely eliminate multi-language screening challenges, such as the important need to identify similar-sounding names, duplicate stories, or other issues where contextual information may be required to make a decision.
While automated solutions may be able to capture data for specific risk keywords such as “crime”, “fraud”, or “bribery”, that approach may still be too sensitive, and result in an overwhelming amount of false positive alerts. The false positive rate can be critical to compliance: too many alerts, slow the compliance process to a crawl and force AML teams to remediate manually in order to build accurate risk assessments.
Natural Language Processing Software: Development and Deployment
The bank in the case study addressed its false positive challenge by integrating AI-powered NLP screening software as part of its adverse media screening solution. Working closely with the third party provider, the bank was able to refine the NLP screening software throughout its development, tailoring it to its risk environment, while also helping the provider enhance it for deployment in other financial institutions.
Natural language processing platforms are capable of analysing and understanding the data points within large volumes of unstructured data, and connecting those points in order to generate responses to questions or prompts. In the context of multi-language adverse media screening, automated NLP is useful for entity resolution: trained on media stories in different languages, NLP may accurately identify the subjects of name searches based on contextual information such as age, occupation, nationality, and other relevant risk data. Using that data, NLP makes it easier and faster for compliance teams to tackle false positive challenges, including distinguishing between duplicate stories and similar sounding names, interpreting translated content, identifying the use of nicknames, and so on.
After deploying the NLP-powered name screening software, the Hong Kong bank reported that its risk detection had “significantly improved”. The bank noted that the software enhanced its screening solution to the extent that it was identifying previously unknown risks with its customers, and had prompted compliance teams to apply enhanced due diligence (EDD) measures to resolve the emergent risks.
Choosing an NLP Vendor
Both the Hong Kong case study bank and its third party provider pointed out that the metric of success in the deployment of the NLP name screening software should not be limited to a reduction in the false positive alert rate, but should be based on a range of qualitative and quantitative metrics across large samples of data. With that in mind, the effectiveness of NLP integration is heavily dependent on the ability of the software to be customised to an institution’s risk environment: financial institutions should seek screening software that offers the greatest scope for capturing and analysing customer data, and that generates meaningful, actionable financial intelligence.
Labyrinth Screening for Faster, Stronger Decision Making
Ripjar’s Labyrinth Screening platform is designed to meet the needs of specific risk environments, offering customisable customer name searches across thousands of global media sources, sanctions lists and watchlists, in real time and in over 25 languages.
Generating financial intelligence in seconds, Labyrinth Screening is further enhanced by powerful entity resolution features which facilitate stronger compliance decision-making. The AI Risk Profiles feature extracts only the most relevant risk data from extensive global name searches, in order to build individual customer risk profiles quickly, complete with entity-specific risk data. AI Summaries is an expansion to AI Risk Profiles that employs generative AI to add a brief, impactful adverse media risk summary to each customer profile in clear, concise prose, and that can reduce the time needed for a customer risk assessment by up to 90%.
Learn more about Ripjar’s NLP-powered adverse media screening technology
Ripjar’s first survey report on adverse media screening highlights the role of advanced technology in revolutionising risk detection and enhancing anti-money laundering efforts.
LONDON, 25 July 2023: Ripjar, the trusted provider for identifying and tackling criminal and malicious activity, has today released its 2023 State of Adverse Media Screening report, based on a survey investigating the use of adverse media screening among compliance professionals. In a rapidly evolving regulatory landscape, compliance leaders are recognising the strategic importance of technology in combatting financial crime. The report highlights the shift from considering technology as a discretional choice to a critical investment, with 62% of respondents acknowledging the over-reliance on manual processes and emphasising the untapped potential of technology adoption.
Additional key findings from the report show that:
Of the firms who are using tech for screening, 71% of respondents say they use some form of artificial intelligence (AI) and machine learning (ML) as a core component of their adverse media screening
20% are still conducting adverse media screening entirely through manual processes
Only 14% of companies aren’t considering using ChatGPT, or other Large Language Models, as an additional capability for adverse media screening. 50% are considering its use in the future, 34% are taking active steps to explore these models, and 2% are already using them.
Investigating the future of adverse media screening and sentiment in the industry, Ripjar surveyed 205 compliance professionals from across Benelux, Sweden, Finland, Germany, France, Italy, the United Kingdom, and the United Arab Emirates.
The report examines attitudes to adverse media screening, the current role that technology plays in media screening, and what the future outlook is set to be. It also takes a view on the current challenges around adverse media screening, how current technology is implemented, and moving away from manual processes.
In addition, the report looks into the introduction of Large Language Models (LLMs), such as ChatGPT. These are set to significantly disrupt many operational processes within every organisation. Only 14% of respondents said that their companies won’t be considering LLMs for their future screening operations, with 50% considering them in the future, 34% taking active steps to explore these models now, and 2% already using them in their day to day operations. The research has also revealed significant differences in trust surrounding LLMs, too. 58% of respondents found that they are somewhat confident in them, 23% are not very confident, while 12% are very confident.
As organisations navigate an increasingly challenging regulatory environment, embracing technology for adverse media screening offers distinct advantages in optimising compliance efforts. The report shows that technology-driven solutions empower firms to effectively manage risks, make sense of vast amounts of unstructured data, and prioritise alerts for analysts. The report then concludes that the adoption of advanced technology is crucial for organisations to proactively mitigate risks and ensure compliance in an ever-evolving landscape.
Jeremy Annis, CEO and co-founder of Ripjar, said: “We are witnessing a transformative era in adverse media screening, driven by advancements in AI and machine learning. Our survey report highlights the significant impact that technology adoption can have on improving risk detection and compliance surplus. At Ripjar, we work closely with ground-breaking compliance professionals dealing with a vast range of challenges. We are excited to see how innovative solutions will continue to empower compliance teams and shape the landscape of risk management.”
Gabriel Hopkins, Chief Product Officer at Ripjar, said: “This survey report underscores the transformative power of technology in the fight against financial crime. With advancements in AI and machine learning, organisations now have access to powerful tools to enhance operational efficiency and bolster anti-money laundering. The findings highlight that firms leveraging sophisticated technology solutions are seeing significant advantages. While the potential for AI is immense, our customers highlight the importance of working with a trusted solution which provides both performance and the required levels of model governance.”
Ripjar is a data intelligence platform company whose mission is to help organisations and governments automate the detection, investigation, and monitoring of threats from criminal activity. Founded by former members of the UK’s Government Communications Headquarters (GCHQ), Ripjar develops software products that combine automation, artificial intelligence, and data visualisation to help companies solve the most complex risk and security management problems at scale.
Adverse media screening is typically framed as a component of regulatory compliance in jurisdictions around the world, and is necessary for firms seeking to protect themselves against serious financial and criminal penalties. However, while adverse media (or negative news) serves as a valuable early warning system against criminal risks such as money laundering and terrorism financing, it’s worth remembering that it can also help to protect firms against significant reputational damage.
Reputational damage can be just as impactful as the penalties imposed by regulators following compliance violations. In addition to discouraging customers from directly purchasing goods and services, and ceding commercial advantages to competitors, reputational damage can shake markets, and lead to drastic reductions in share value.
Customer screening is crucial to modern AML/CFT strategies since it allows compliance teams to build out accurate customer risk profiles, informed by relevant, current data. Adverse media screening is particularly useful because news stories and other types of online media often reveal compliance risks long before that information is confirmed by government or law enforcement agencies. By implementing an effective screening solution, firms can detect adverse media involving their customers as soon as possible, and capture risk data that other customer due diligence (CDD) processes may have missed.
However, reputational risks often fall outside the scope of traditional regulation-focused AML data sources (such as watchlists), which makes adverse media a valuable supplementary resource for enhancing risk profiles. Unlike other types of AML/CFT risk, reputational risk can be hard to address: news stories can break and develop quickly, and may be shared widely on social media before a firm has had a chance to respond. By screening against adverse media, firms can get ahead of reputational threats, react swiftly to new developments, and make important compliance decisions before damage is inflicted.
Sanctions Screening
Since sanctions lists change constantly, adverse media offers a particular advantage in the swift detection of sanctions compliance risk, which can cause significant reputational damage (should a violation occur). Recent geopolitical events, such as the Russian invasion of Ukraine, demonstrate the speed at which sanctions can evolve, and the need for firms to be agile when determining their risk exposure.
Reputational Risk Categories
To enhance the effectiveness of adverse media screening, it’s useful to categorise relevant data by type. Certain adverse media stories entail both regulatory and reputational risk, so the more accurately a firm can determine the specific threat that a story entails, the more effectively it can deploy a compliance response.
By categorising types of adverse media, it’s possible to identify story characteristics that carry the possibility of reputational damage. For example:
Human slavery: The exploitation of labour as human slavery. While companies may not engage directly in human slavery, they may be exposed to risk via their supply chain.
Human trafficking: The illegal movement of people for the purposes of exploitation. Human trafficking is often linked to forced prostitution or slavery.
Drug trafficking: The illegal movement of drugs for the purposes of sale and distribution.
Arms dealing: The illegal trade in weapons, including those with indiscriminate effects such as landmines and cluster bombs.
Bribery and corruption: The illegal use of wealth or power to gain unfair advantage or favourable business outcomes. Bribery is particularly damaging when it involves government officials.
Environmental damage: Activities that harm the environment, such as drilling and mining, toxic waste disposal, or carbon emissions.
Discrimination: Companies that discriminate on the grounds of race, gender, sexual orientation, and other protected characteristics.
Workplace health and safety: The failure to protect employees in the workplace or exposure to poor working conditions. Health and safety issues may be of particular concern in developing nations.
Animal welfare: Cruelty to animals during transport and trade, or activities that impact on protected species.
Sanctions: The violation of trade prohibitions with sanctioned nations or persons, including connections to terror groups.
There is significant crossover between different reputational risks, and many of the activities outlined above also entail criminal risk exposure.
Effective Adverse Media Screening
Reputational damage is hard to predict, and varies by the type of activity involved and by the way that a story is reported. However, in order to avoid, or at least mitigate, reputational damage, firms need to see it coming as early as possible. However, identifying specific reputational risks amongst a crowded landscape of adverse media stories, means being able to search huge amounts of data from around the world with speed and accuracy.
Ripjar’s Labyrinth Screening platform is designed to help firms manage their screening obligations, and protect themselves from reputational damage in a complex and constantly changing risk landscape. Powered by cutting edge machine learning technology, Labyrinth Screening is capable of searching thousands of global news sources, sanctions lists and watchlists, in over 20 foreign languages, delivering actionable intelligence in seconds and helping you make important compliance decisions with confidence.
Learn more about how Ripjar’s screening capabilities can help with reputation protection: contact us
Financial compliance shouldn’t be a box-ticking exercise: by monitoring and screening customers and transactions in accordance with regulations, firms can actively contribute to the global fight against financial crime and make financial systems safer from activities such as money laundering and terrorism financing. The earlier that financial crime risks can be detected, the more likely it is that firms can adjust their compliance framework, prevent crimes from happening in the first place, and reduce any potential damage.
Adverse media – or negative news – is one of the best early-warning signs of anti-money laundering (AML) and counter-financing of terrorism (CFT) risk because criminal activities may be revealed in news stories (and other online sources such as blogs or social media posts) before they are confirmed officially. That forewarning allows firms to establish the AML risk a particular customer presents faster than they would have by relying on other compliance processes such as customer due diligence (CDD).
In order to use adverse media screening as an early warning of risk, it’s important that firms understand what to look for when searching for customer names, and why the resulting data is so valuable for regulatory compliance.
Let’s take a closer look at the reasons why adverse media screening is such a useful early warning mechanism.
Categorising Risk
The adverse media landscape holds a wealth of potentially relevant risk data which can be used to make crucial compliance decisions. The utility of that data as an early warning can be further enhanced by organising adverse media stories into categories, and then assessing their relevance to a firm’s risk appetite. At Ripjar, for example, we organise adverse media into risk categories including:
Bribery and corruption: Activities including active and passive bribery, extortion, embezzlement, influence peddling, misuse of power, and blackmail.
Corporate malfeasance: Transgressions perpetrated by officers of an organisation, including financial deception, negligence, anti-competitive practices, and a range of unethical activities such as discrimination or unfair labour practices.
Financial crime: Major financial crimes including insider trading, fraud, market manipulation, and large scale tax evasion.
Predicate crime: Crimes that generate illegal proceeds that must be laundered, including drug trafficking, people trafficking, theft, forgery, cyber-crime, and illegal gambling.
Reputational risk: Activities that may be legal or illegal and that negatively affect a customer’s reputation, including environmental damage, workforce exploitation, animal welfare, and unethical trade practices.
Sanctions and embargoes: The risk of being sanctioned by governments or international organisations like the United Nations.
Terrorism and terrorism funding: Membership or financial support for terrorist groups, and incitement to commit terrorism.
While adverse media categorisation isn’t a magic bullet for managing risk, it’s a particularly useful way of determining effective compliance responses quickly. By better understanding the type of risk they face early, firms may be able to increase the impact of their compliance response and optimise the outcome.
Anticipating Criminal Activity
As governments introduce new regulations, and criminals find more sophisticated ways to exploit financial systems, banks and financial service providers must keep pace. With that in mind, one of the primary reasons to screen for adverse media is to ensure that your organisation is able to spot criminal risks on the horizon.
While customers may not yet be charged with crimes, or even involved in criminal investigations, breaking media stories and other forms of online content often reveal business ventures and relationships, financial difficulties, or political changes that will alter the risk landscape and that will lead to criminal risk in the future. Similarly, new sanctions designations may be anticipated via stories that expose customer connections to countries and individuals designated on sanctions lists. Supplemented by additional compliance data, including the relevant CDD information, adverse media can help firms gauge risk before a criminal threat manifests.
Avoiding Compliance Fines
Compliance violations have serious consequences, not least significant financial penalties which may impede a firm’s ability to continue doing business. Not all compliance penalties are created equal, and they vary by the type and severity of violation: money laundering the proceeds of drug trafficking, for example, may incur a greater fine than proceeds from other predicate crimes. Similarly, fines may vary by jurisdiction: in the UK for example, money laundering fines are unlimited, while US AML compliance penalties may reach $1 million or 1% of the assets of the offending institution (whichever is greater).
Depending on a firm’s risk appetite, adverse media screening represents a way to spot and avoid potentially damaging compliance fines. It’s therefore vital that firms stay up to date with the latest regulatory changes as they pertain to compliance fines. In the UK, for example, recent regulatory changes introduced strict liability for sanctions violations, which means that fines may be imposed regardless of a firm’s awareness of customer wrongdoing. The sanctions landscape evolves constantly, and adverse media screening should be a priority for any firm seeking to stay ahead of new designations and costly fines.
Avoiding Reputational Damage
Adverse media does not just act as an indicator of potential AML risk: in situations where firms have ethical priorities or responsibilities, it may also serve to prevent reputational damage. While involvement in financial crime has always entailed a degree of reputational risk, the nature of the modern media landscape means the resulting damage is often more acute: stories can be published quickly by news organisations and shared widely between users of social media sites. Managing reputational damage is difficult in a perpetually-connected world, so the better firms are at spotting incoming risks, the easier it is to prevent.
It’s worth bearing in mind that reputational risk is becoming a significant priority thanks to the rise of environmental, social, and governance (ESG) concerns, which include issues like labour disputes, climate change, and workplace equity. Not only is the public becoming more sensitive to ESG issues, but governments are beginning to regulate associated practices. As that dynamic continues, the importance of early risk detection will also increase, with firms incentivised to address reputational risk with the same speed and efficiency as traditional criminal risks.
Maintaining Ongoing Vigilance
The early detection of risk is crucial in an effective compliance framework. In practice, however, firms should monitor and screen for risks on an ongoing basis as a way to manage an evolving compliance landscape in which new criminal methodologies and new regulatory obligations emerge regularly. Unfortunately, not all compliance solutions give firms the capability to implement ongoing monitoring and screening, and instead rely on analogue CDD processes, and manual adverse media checks, sometimes conducted via search engines.
Ongoing screening, and early risk detection, requires firms to implement technology solutions capable of managing large amounts of data (including adverse media) from sources around the world. Ripjar’s Labyrinth Screening platform was created with this requirement in mind: powered by machine learning technology, Labyrinth enables firms to screen millions of adverse media sources, sanctions lists, and watchlists in real time, and delivers actionable intelligence in seconds. With name search functions in over 20 foreign languages, Labyrinth ensures your organisation has the capability to detect changes in risk as soon as possible, and adapt quickly when the risk landscape changes.
Learn more about our adverse media screening capabilities: contact us today
While Adverse Media (AM) regulations and requirements vary significantly across the world, the need to implement adverse media screening as part of a risk management solution is a consistent compliance challenge. To help you meet that challenge, in August 2022, Ripjar Chief Product Officer Gabriel Hopkins and CEO and co-founder Jeremy Annis hosted an AM screening webinar, focusing on the need for businesses to build a balanced AM screening solution tailored to their unique risk concerns.
Catch up on some of the key points from our webinar here.
Defining Adverse Media Screening
Adverse media screening – sometimes called negative news screening – refers to the process of using different types of media to inform a risk-based compliance process. Speaking in the webinar, Jeremey Annis defined the process as “monitoring the media to manage an organisations’ risk posture and exposure, through customers or related parties, to financial crime and reputational risk”.
Jeremy noted that adverse media usually refers to unstructured content, such as newspaper articles, websites, blogs, social media posts, and other online data posts – rather than typical name screening data sources, such as international sanctions lists or politically exposed persons (PEP) lists. Unstructured adverse media tends to be “fast and messy”, with new stories entering the ecosystem and then evolving and changing as new information emerges. By nature, it is inexact and potentially confusing.
With that in mind, adverse media screening solutions must be agile and flexible and capable of combining a range of structured customer data with unstructured sources derived from the global news landscape. Similarly, adverse media screening represents a way for organisations to move towards a system of ongoing compliance – with processes informed by continuous monitoring technology that adds depth and context to structured customer due diligence (CDD) information or suspicious activity alerts.
Regulator Attitudes to Adverse Media
Financial regulators and authorities have begun to mandate some adverse media screening as part of their risk management frameworks. During the webinar, Gabriel and Jeremy stressed the importance of understanding jurisdictional attitudes to adverse media screening and set out several notable regulatory positions:
The EU: The EU’s Sixth Anti-Money Laundering Directive (6AMLD), adopted across the EU and in the United Kingdom, came into effect on 3 June 2021, with a stronger focus on adverse media screening than its previous iterations. Specifically, 6AMLD stipulates that organisations must implement “systematic” adverse media checks: while that direction may include a broad range of search and screening mechanisms, it represents a tightening of regulatory expectations, ensuring EU organisations are contributing meaningfully to the global fight against money laundering.
The United States: While the US has not gone as far as the EU in introducing a mandatory system of checks, the Financial Crimes Enforcement Network (FinCEN) recently emphasised the importance of adverse media screening as a compliance tool. Many US organisations have interpreted that move as an indication that the financial industry needs to be ready for incoming regulations.
Singapore: The Monetary Authority of Singapore (MAS) has generally been ahead of global adverse media trends. As far back as 2018, MAS was coordinating with banks in Singapore on a requirement for quality adverse media checks as part of the city-state’s anti-money laundering and counter-financing of terrorism framework. Implemented in a variety of Singapore banks, those AM screening processes were then exported to those same organisations’ branches in other jurisdictions out of a need to maintain a level regulatory playing field.
International regulators: The Financial Action Task Force (FATF), an inter-governmental AML/CFT regulator, has long advocated for adverse media checks, with guidance set out in its 40 Recommendations. That sentiment was recently amplified by the influential Wolfsberg Group, which published a Negative News Screening FAQ in May 2022. The FAQ took a ‘common sense’ approach to explaining the significance and importance of adverse media screening as part of the effort to combat financial crime.
Establishing an Effective Adverse Media Solution
The webinar panel’s discussion included a range of fundamental considerations for building an adverse media screening solution that balances efficiency with the need for regulatory robustness. The panel’s key adverse media screening considerations included:
Search scope: Firms should understand what kind of media coverage their adverse media screening solution needs, taking into account factors such as customer risk profiles and areas of operation. That consideration should ultimately determine what kind of adverse media data they include in their searches and whether local outlets should be included. Customers with business interests in South America, for example, should be screened against local South American news sources.
Customer screening requirements: It is important to understand how much of a given customer population should be screened against adverse media. This consideration is fundamental to the risk-based approach endorsed by the FATF and requires organisations to conduct customer risk assessments. When a customer is determined to present a high risk of financial crime, adverse media screening is a way to ensure their risk profile remains accurate throughout the relationship. The more high risk customers that an organisation has, the more robust and efficient their adverse media screening solution needs to be (and the more value can be provided).
Public vs commercial media sources: Adverse media screening solutions may draw on commercial or publicly available news stories – both of which offer different advantages. Publicly available adverse media refers to data derived from scrapes of news websites – while that information is free, it is limited in archival scope and often involves copyright concerns which can limit its usefulness. By contrast, commercial adverse media sources offer a greater depth of archival information that allows for searches over longer periods of time.
Source diversity: An adverse media screening solution should take in a diverse range of media sources, including screen and print sources, established news websites and independent sites, blogs, forums, social media platforms, and any other relevant form of media. That diversity should also take into account the geographic relevance of the data collected, and source credibility: an established news organisation, for example, is likely to produce more credible and higher quality media than a personal blog or social media network, and be of more use in any subsequent money laundering compliance decisions.
How Ripjar Can Help With Adverse Media Screening
Given the challenges and demands of 21st century compliance, your organisation needs an adverse media screening solution that delivers meaningful risk data from a crowded and often chaotic landscape of sources. Key to that requirement is a capability to assess large volumes of data efficiently, searching for customer names in a variety of languages, for example, or using fuzzy logic tools to identify inefficient and potentially costly false positives.
With that in mind, Ripjar’s adverse media screening solution, Labyrinth Screening, has been designed to be a powerful screening tool, capable of conducting name searches in 21 languages and of capturing changes to customer risk profiles in real time. Powered by next generation machine learning technology, Labyrinth Screening goes further than conventional KYC tools by balancing the demands of regulatory compliance with adaptive, ongoing screening support. Our platform can be tailored to the compliance needs of an individual business in order to address risk exposure, while reducing costly false positive alert rates, and adapting to emerging criminal risk and incoming regulations.
Risk management should be more than just a series of ‘box ticking’ data collection exercises. While many anti-money laundering (AML) and counter-financing of terrorism (CFT) regulations focus on capturing static customer information such as names, addresses and business details, it’s vital that you also understand your risk exposure in a constantly-evolving compliance landscape.
Adverse media screening, sometimes referred to as negative news or negative media screening, describes the process of searching for news stories that are relevant to a customer’s AML/CFT risk profile. It takes in traditional screen and print media, as well as online sources such as blogs, forums and social networks. With a global reach, including foreign language news sources, adverse media screening is one of the best ways of building an accurate, up-to-date picture of the counterparty risk that your company faces, and of anticipating future threats. In some jurisdictions, adverse media screening is even codified by law as an AML/CFT compliance requirement.
With these factors in mind, it’s vital you understand how and why your adverse media screening solution can help you meet your regulatory obligations. To optimise your compliance response, read our list of the 5 key reasons you need effective adverse media screening.
1. Spot Emerging Threats Early
When customers are onboarded, the AML/CFT risk that they present may not be immediately apparent. In the same way, existing customers may become involved in activities or be exposed to global events which are likely to increase compliance risk later in the business relationship. Adverse media offers banks and financial institutions a way to spot this kind of emerging threat early since negative news screening may detect certain business activities or financial behaviours that indicate a customer’s risk profile is likely to change.
For example, negative news screening may detect that a client with overseas business interests has connections with Russia, putting them at increased sanctions compliance risk at some point in the future as a result of measures taken in response to the Russian invasion of Ukraine. Similarly, negative news screening may reveal criminal activities (including money laundering predicate offences) that do not result in charges – but which indicate that customers should be scrutinised more closely in the future for ongoing risk indicators.
2. Keep Track of Broader Business Risks
An AML/CFT solution may be set up around the specific risks that an individual customer presents, and screen against a range of relatively static qualities, such as names, addresses, beneficial ownership, business locations, and transaction counterparties. Those data points provide only a very limited perspective on a customer’s risk profile, and do not take into account wider variables that might be affecting the business relationship.
Since the media landscape is constantly changing, with stories evolving on a daily basis, adverse media screening offers a way for organisations to keep track of the broader risk environment. Even better, the information that your compliance team gathers during the remediation of an adverse media alert will help to strengthen your AML/CFT response going forward. In particular, adverse media alerts may help firms stay ahead of geopolitical crises, new criminal methodologies, and new regulatory trends. Adverse media screening may, for example, help your company detect new Environmental, Social and Governance (ESG) risk liabilities – including environmental crimes and unethical labour practices.
3. Identify Beneficial Owners and Shell Companies
Criminals often set up shell companies or use complex corporate structures to conceal their involvement in money laundering transactions and avoid AML/CFT scrutiny. In some cases, shell companies may be set up in low-regulation countries like the Cayman Islands, in order to avoid compliance measures in higher regulation countries and force investigators that are attempting to trace illegal funds to navigate cross-border regulatory disparities. While firms may implement measures that require customers to reveal beneficial ownership, doing so may be challenging and add to the compliance burden.
Since the ownership of shell companies is a frequent subject of investigative media reports around the world, adverse media screening may help firms detect when customers are using corporate structures to commit financial crimes. Global adverse media screening tools are particularly important in this context because of the likelihood that customers are using foreign shell companies to avoid domestic regulations.
4. Discover New Information about PEPs
Politically exposed persons (PEP) are elected officials and government employees that pose an elevated AML/CFT compliance risk. That risk stems from the increased likelihood of PEPs being involved in financial crimes, including bribery and corruption, as a result of their access to government funds and their ability to avoid regulatory scrutiny. Given that threat, companies must screen customers against PEP lists regularly and be aware when a customer’s status as a PEP changes following their election to a political position or employment in a government agency.
The challenge of PEP screening reflects the speed with which the political landscape can change as individuals assume political office. Global adverse media screening is so useful at capturing information about PEPs because foreign news outlets frequently report on elections and on stories involving political corruption which domestic outlets do not.
5. Generate Information for AML Investigations
Regardless of whether an adverse media search generates an alert, the subsequent remediation process provides useful data points to help guide any future financial crime investigation. AML screening by necessity involves the analysis of a vast range of news stories, generating potential connections to a spectrum of financial activities.
The value of adverse media data will depend on the depth and detail of the search conducted. When conducting negative news screening, companies should also consider the quality, relevance, and reliability of the data, taking into account factors like political bias and media sources. Stories from an established mainstream news outlet, for example, with years of industry output, are likely to be more credible and reliable than data sourced from an internet forum or social network.
Adverse Media Screening Technology
In order to meet their adverse media compliance requirements, companies must implement an effective software screening solution capable of capturing relevant news stories from around the world. Ripjar’s Labyrinth Screening solution has been developed with that objective in mind, integrating next generation compliance technology, including real time global adverse media searches in 21 languages, to ensure you stay informed whenever your customers’ risk profiles change.
To find out how Ripjar can help with your adverse media screening, contact us today.
Since money laundering is frequently a global crime, in order to identify negative news involving their customers, financial institutions must adjust their screening solutions to capture stories from foreign media sources. However, in order to collect that data effectively, adverse media solutions must be capable of understanding a range of local language systems – a process known as multi-script language screening.
In their 2022 Negative News Screening FAQ, the Wolfsberg Group, a prestigious intergovernmental banking association, set out a range of significant multi-script language considerations. To help your organisation optimise its risk-based negative news solution and achieve compliance with jurisdictional anti-money laundering (AML) regulations, we’re taking a closer look at the details of the FAQs.
Why Do Financial Institutions Need Multi-Script Language Screening?
From a regulatory perspective, adverse media stories can be valuable compliance assets, potentially revealing customer involvement in financial crime before that information is confirmed by official sources.
Where local news organisations publish or broadcast in non-Latinate language systems, however, it may be difficult for financial institutions to match their customer’s name to negative news as a result of unfamiliar spellings, characters, or naming conventions. With this in mind, multi-script language screening represents a crucial compliance tool, enabling financial institutions to identify high risk customers in a range of local language news stories, and use the information that they provide to maintain regulatory compliance.
Key Multi-Script Language Screening Terms
In order to effectively implement multi-script language screening as part of a negative news solution, financial institutions and their compliance employees should be familiar with the following terms and concepts:
Transliteration
Solutions must be able to transfer words written in one script to another, in order to facilitate pronunciation and transcription. An example might involve a name written in the Japanese Kanji script: ‘歌川豊春’ transliterated to Latin script as ‘Utagawa Toyoharu’, or the German ‘Hans Rüdi Müller’ to ‘Hans Ruedi Mueller’.
Transcription
Words that are written in one language script may need to go through transcription in order to be written in another. Transcription typically involves a conversion system but methods can vary significantly. In practice, this means that names can be transcribed differently with different transcription methods, for example ‘Osama Bin Laden’ and ‘Usama Bin Laden’.
Translation
Where names are rendered in a foreign language, translation describes the process of capturing the meaning of that name in another language. For example, ‘Monaco Di Baviera’, which literally means ‘Nun of Bavaria’ is translated in English as ‘Munich’.
Risk-Based Multi-Script Language Screening
In a risk-based AML solution, the need to deploy multi-script language screening depends on the customers with which a financial institution does business, and the markets in which they operate. Financial authorities may also impose a regulatory requirement on the institutions within their jurisdiction to conduct effective negative news screening.
Given their potential importance in an AML programme, multi-script adverse media solutions should be developed with the following considerations:
The capability of the screening solution to recognise non-Latinate characters, such as characters from the Cyrillic, Mandaric, or Arabic alphabets.
The quality of the datasets, including the names of customers and media sources, that the solution can draw on in order to accurately screen against negative news stories.
The capability of the screening solution to transliterate customer names from a native script to familiar Latin characters.
Multi-Script Screening and Compliance
Multi-script language screening can present a complex and evolving compliance challenge. Depending on regulatory requirements, financial institutions must ensure that they integrate multi-script screening effectively as part of their AML/CFT solution. This typically means taking a multilingual approach to compliance, and appointing local teams with expertise in the relevant local languages.
Financial institutions should consider the availability of foreign media sources, watch lists and technology tools in order to enhance their solution, and be aware of the minimum negative news screening requirements imposed in their jurisdiction. With this in mind, many financial institutions engage a third-party adverse media screening provider in order to implement multi-script language screening in their AML compliance solution.
Following Financial Action Task Force (FATF) guidance, most anti-money laundering (AML) and counter-financing of terrorism (CFT) regulations require financial institutions to take a risk-based approach to compliance. Predicated on a need to perform risk assessments on individual customers, the risk-based approach is applicable to every aspect of modern AML/CFT, including negative news screening (NNS).
On 11 May 2022, global banking association the Wolfsberg Group released an FAQ on negative news considerations. The FAQ includes a focus on risk-based negative news screening (also referred to as adverse media screening) as part of a wider AML/CFT solution, including how to manage the scope of a news search.
To help your business integrate risk-based negative news screening as part of your AML/CFT solution, we’re taking a closer look at the Wolfsberg Group’s insightful FAQ.
What is the Risk-Based Approach?
Risk-based AML/CFT is the process of assessing individual customers to determine the level of criminal risk that they present, and then deploying a compliance response proportional to that risk. Under the risk-based approach, higher risk customers may warrant more intensive AML/CFT measures and controls, while lower risk customers may warrant simpler measures.
The risk-based approach represents a way for organisations to balance regulatory obligations with budget and resources. Given the complexity and expense of AML/CFT compliance, financial institutions may direct time and money towards their higher risk customers rather than their lower risk customers.
Risk-Based Negative News Screening
In the context of financial compliance, negative news screening may be a measure that financial institutions deploy for a subset of their portfolio, including their higher risk customers. Customers with elevated public profiles, such as politically exposed persons (PEP), may be featured in news stories that reveal involvement in financial crime. Similarly, news stories may reveal that foreign customers have been designated on sanctions lists before that information is confirmed officially.
Negative news screening may also be applied to lower risk customers in a much broader manner. Financial institutions may run simple name searches, for example, for customers with less visible public profiles who do not justify the same level of compliance effort as their higher risk counterparts.
Determining the Scope of a Negative News Search
Financial institutions must use their customers’ risk profiles to determine the focus and scope of their negative news screening measures. Key risk factors that should inform the negative news screening process include:
The services and products that the customer uses.
The customer’s demographic profile.
The customer’s geographic location or the locations with which they have business connections.
The criminal risks associated with the financial institution’s industry segment.
The details of the customer’s internal risk profile (as informed by the factors described above).
Certain internal and business factors will also play a part in shaping a risk-based negative news screening solution. Financial institutions should consider the following factors:
How often previous customers or clients have been involved in criminal incidents.
The legal and reputational consequences of doing business with customers involved in financial crime.
The speed with which the financial institution could move to address exposure to compliance liability.
The financial crime typologies, such as bribery or political corruption, that are typically revealed by effective negative news screening.
The resources available to dedicate to adverse media screening.
Risk Categorisation
Negative news stories do not necessarily all present the same level of compliance risk, and the substance of specific stories may affect customer profiles in different ways. With this in mind, financial institutions should seek to categorise news stories by risk, using groupings such as:
Regulatory violations
Drug trafficking
Human trafficking
Cyber-crime
Financial crime
Similarly, the source and format of the negative news story is also relevant to a financial institution’s risk appetite. When gauging the risk that individual stories present, it may be important to consider:
Source credibility: An established news outlet may be considered to have more credibility than a personal blog or a webpage that is available for public editing.
Governmental influence: Some news sources may be state affiliated or have political biases that affect the character of their stories.
Customer relationship: The significance of negative news may ultimately be determined by the relationship that a financial institution has with its customer. With that in mind, the risk that negative news stories represent may be mitigated by privileged insights that a given financial institution has into a customer’s financial activity.
The global media landscape is diverse and shifts constantly as news stories break. When a business searches for negative news to address its risk-based compliance challenges, it should expect to have to collect and analyse vast amounts of media with the goal of extracting specific data points about its customers.
While global negative news stories originate from a variety of sources, including screen and print sources, the vast majority of stories are hosted, and available, online in formats such as websites, blogs and social media platforms. Businesses may search for customer involvement in adverse media by conducting manual searches on web-based search engines – but should be aware of the limits of these web-based tools, and how to enhance their results for better risk management utility. On 11 May 2022, the Wolfsberg Group published a series of negative news screening (NNS) FAQs to help financial institutions enhance their anti-money laundering (AML) and counter-financing of terrorism (CFT) risk management. Building on points raised in the Wolfsberg Group FAQs, we’re exploring the role that internet search engines can play in a NNS solution.
Search Engine Limitations
The online availability of news media suggests that internet searches, via search engines such as Google or Bing, may be suitable for the compliance-focused NNS process. However, search engines are essentially algorithm-driven content browsing mechanisms and not exhaustive AML/CFT databases. While search engine searches offer some utility for negative news screening requirements, the results they generate are not optimised for financial compliance and their algorithms may omit or de-prioritise certain relevant data points.
With that in mind, firms should integrate search engines into their negative news screening process with an understanding of their limitations. In order to address those limitations, and to optimise their screening functionality, firms might seek to use search engines with the following features:
The capability to select specific parameters for searches and results, for example, setting languages, timelines, geographical scope, and the number of results displayed per page.
Advanced search options such as the capability to specify search terms, content types, file types, and domain names.
The capability to specify exact and partial search-term matching.
Search engine negative news screening involves a range of additional complications, not least those relating to the language in which a search is conducted. Words that are written in a local language system, for example, may deliver different results than the same terms searched in their translated equivalent.
The Importance of Keywords in NNS
Keywords are crucial to internet-based negative news screening. The most effective screening processes should involve defined keywords (sometimes referred to as key terms, or search phrases) in conjunction with the targeted customer’s name. There is no universally-codified approach to the application of keywords as part of a NNS search, which means the keywords your business chooses for each case should be aligned with your risk appetite and compliance priorities. Important considerations for keyword use as part of a NNS search include:
Length: Search engines place limits on the number of keywords that may be used in a search. It may be necessary to run supplementary keyword searches if their length exceeds this limit.
Precision: It can be difficult or even impossible to get consistent results from search engines, while use of generic keywords may deliver too high a volume of results with numerous false positive hits. Accordingly, keywords should be formulated with suitable precision in order to achieve an acceptable level of search relevance.
Language: Keywords searched in different languages may generate different results. Firms should think carefully about what language keywords should be in for optimal NNS effect. Alternatively, firms may search in multiple languages providing the keywords have been translated correctly.
Search Engine Oversight
Most search engines are subject to the oversight of their owners who may alter or remove results without notice, or adjust the ways in which their algorithms generate results. This means that NNS searches may differ even when conducted within the same parameters or with the same keywords. Similarly, some search engines may be affected by corporate or political influence or may filter out results to meet local regulatory requirements such as censorship or data protection laws. In the EU, for example, the General Data Protection Regulation (GDPR) sets out strict rules concerning the retention of personal data and includes a ‘right to be forgotten’, which requires firms to delete customers’ personal information when it is no longer necessary.
The potential for search engine results to change in this manner is obviously a problem for regulatory compliance, which relies on firms being able to generate accurate, relevant information on an ongoing basis.
Search Engines and Compliance Technology
It is clear that negative news screening approaches should not rely on search engines alone to meet their risk-based compliance obligations. With that in mind, firms should consider search engines only as part of a tiered approach to NNS within their wider compliance technology deployment. This approach may involve the generation of an initial high volume of negative news alerts that are subsequently whittled down by the application of adverse media screening strategies, including the use of manual search engine searches. In this context, search engine results may be particularly useful for enriching the NNS process, adding depth and context to alerts and helping to address potential false positive alerts.
