It’s not John, it’s James. In the US alone, it is estimated there are over 30,000 people who share the same name, James Smith. In Korea, almost 20% of the population – some 10 million people – share the same family name of Kim. The world is also home to over 150 million with the same given name – Mohamed. Cases of mistaken identity are common, particularly when searching over large volumes of data, but they needn’t be.
Almost all investigatory work, whether in law enforcement, counter terrorism or within the anti-money laundering (AML) and due diligence processes of a bank, require accurate ways of searching and discovering specific entities in large data sets. However, poor record keeping, missing or incomplete data and legacy matching-logic hamper these efforts. False positive matches – selecting the wrong entity – and worse, false negatives (where a critical search result is missed altogether) are abundant.
Not only are they not unique, there is also no standard way of rendering names. Thus, James Smith can be Jim Smith, J Smith, J M Smith, as well as a huge array of possible typos, transpositions, aliases, or renderings in different dialects, alphabets and scripts. Matching against “exact hit” names works when data quality is very high, but it means there are no alerts at all if names have even the slightest variation, increasing the chances of criminals slipping through the net. Similarly, so-called “fuzzy matching” which will alert if one or two characters are different, still cannot account for the sheer variety and array of cultural nuances in how names are rendered in different types of data.
The solution is to use data to drive a new type of matching logic – advanced Entity Resolution. Ripjar uses observations from millions of names, deriving matching logic from how the name is used in real-world situations.
Entity Resolution is an essential capability in the fight against financial crime, fraud and terrorism. By improving the quality of the data that is used to make decisions such as enforcing international sanctions or alerting to possible corruption or fraud, it can dramatically improve the effectiveness and efficiency of human analysts and allow small teams to scale investigations to the demands of the modern information environment.
Combining recent work in entity resolution and NLP means that analysts can now see the complete picture across structured and unstructured data, and data-driven approaches to name matching covering transliterations, scripts and other real-world name variants can give 90% more accuracy than legacy “fuzzy matching” technology. Robust data privacy controls mean interconnected graphs of knowledge, resolving entities from all available data sources can be now built without compromising user privacy or data protection.
If you would like to know more about Ripjar’s approach and how we have helped global institutions roll out breakthrough innovations in entity resolution to support their counter-financial crime programmes, please download our whitepaper or get in touch with the team below.
David Balson
Director of Intelligence
Contact us for a demo today
30% of financial services employees polled do not believe modern slavery is something which happens in the UK. Worse, 45% of board/director level employees believe the same. I’m not sure that I’m in either group, I knew that Modern Slavery and Human Trafficking (MSHT) took place here.
However, I had not stopped to think about all of the connections to the fraud and financial crime which I’ve spent many years of my life trying to tackle. The very best estimates suggest that there are more than 130,000 victims of modern slavery in the UK today and maybe many more. Globally, it’s estimated that on any day 40 million people are trapped. What does modern slavery look like? Fear and desperation are what keep people enslaved in the modern world. That might be though some sort of debt bondage, fear of deportation or threats to family.
What can we do about it? Education is key. As with so much criminal activity, it is only worth committing if you can syphon off the proceeds. So we all need to aware of the warning signs of MSHT and know how to report suspicions. Likewise, we need to continue to be vigilant to identify financial crime of all types. Specifically, MSHT is a predicate or contributory crime to money laundering. (For more on this: read our blog here)
We should never trivialize the complexity of the battle against money laundering, but understanding the connections is a first step, and it seems that investors and clients are increasingly putting pressure on their banks and other financial organisations to do more. If you are interested in learning more details, I’d highly recommend this report put together by Themis.
I started learning about MSHT due to the Tribe Freedom Foundation and an amazing decision by Darren Innes at Nasdaq. Darren put a team together to run across Scotland to raise money for Tribe and suggested Ripjar do the same. Later this week our adventure begins. Alina Akindele, Anthony Birley, Conor Hickey, Dean Jones, Nick Wright, Sharon Turner, Tom Garnett and I will meander our way from Helensburgh to Dunbar running throughout the night and covering 218 KM (136 miles) with total 2,400m of vertical ascent. The forecast looks ok. The strong insect repellent is packed. The head-torches are charged. And any training we’ve not yet done is now just wishful thinking.
Thank you to everyone who has sponsored us so far. If you haven’t and you would like to contribute to a truly worthy cause, you can do so quickly and easily on our fundraising page below – for the overall team or a specific runner.
https://www.justgiving.com/team/ripjar
Gabriel Hopkins
Chief Product Officer, Ripjar
2020 and 2021 have definitely been bumper years in risk management. Businesses, governments and financial institutions face serious risks on all fronts – whether hidden in their supply chain, their client relationships or in their operations. In the wake of the global pandemic, we are all living through the outcome of how we have, or have not, successfully managed those risks.
As the G7 leaders meet in sunny Cornwall, it is interesting to reflect on which risks will dominate the next few years. It is natural that the risk landscape alters over time, but I think it is fair to say that underneath all other concerns, the nature and understanding of risks has changed noticeably over the last few years. Global leadership on these issues matter more than ever – to drive change, inspire others and enhance regulatory guidance – and we are seeing a resurgent America re-join the world stage and start to exert its influence on the global stage.
At the heart of the new risk agenda for groups such as the G7 is to understand what new governance models need to put in place around tackling climate change, the environment and wider issues society such as exploitation and modern slavery. These risk factors are often clustered as ESG – or Environmental, Social and Governance – Risk and may pose questions to decision makers such as:
- Can my organisation continue to support or finance coal-fuelled power stations, or companies involved with the deforestation in Brazil?
- Are we comfortable with our clients’ exposure to a regime that turns a blind eye to modern slavery?
- Is enough being done to counter bribery and corruption?
In answering these questions, corporations face a combination of regulatory, reputational or moral incentives – but if we are to create a more prosperous and safer society more may need to be done.
Consumer preferences are rapidly shifting too – partly as a result of the pandemic – and there is growing demand for brands who are actively conscious of potential reputational issues, and the public reaction can be extremely cruel to organisations who are caught unaware of poor or illegal practices in their vendor networks or supply chains.
The challenge here is to find a way to reliably measure corporate exposure to these important risks. Our Ripjar technology has proved expert at understanding when clients are connected to financial crime, and this week I was delighted to announce at our user forum that we will be extending the same machine algorithms to review news and media data for signals relating to ESG risk to help organisations get ahead of their potential exposure and make the right decisions about who to do business with.
The next 5 years will see a huge shift in sentiment against poor ESG practices. No longer will it just be a large group of activists at events like the G7, but it is likely that public opinion shifts behind the move for governments, banks and corporations to do more and work more efficiently to guard against ESG risks. Contact us today to find out how you can put effective controls in place.
Gabriel Hopkins
Chief Product Officer, Ripjar
It’s a phrase we’ve got used to hearing. An abundance of caution has proven to be an essential technique in the battle against the global Covid-19 pandemic. From masks to social distancing, from working from home to vaccines, the multitude of different ways we’ve learned to manage the risk of transmission has saved hundreds of thousands, if not millions of lives worldwide. It’s also a critical component when considering how to protect your business against financial crime and reputational damage – adopting a risk-based approach when on-boarding and screening clients.
Just like the pandemic, it is easy to manage risk when considering just your immediate surroundings and needs. Manual, one-off searching of databases and search engines can unearth red flags such as adverse media hits, sanctioned entities and political exposure. But what about managing the risk of entire client populations of millions? The difficulty in maintaining an abundance of caution becomes exponentially more difficult when manual searching and human review doesn’t scale.
Ripjar’s Labyrinth screening engine now enables global financial institutions and other large enterprises to understand and manage the risks associated with all of their clients – whether old or new. The sophisticated view provides the ability to make the right decisions at the right moment, alerting on new risks when they become known, not just when they are manually reviewed. Moving from a reactive to proactive management of these types of risk means compliance teams spend less time reviewing data and can ensure that vital information is not missed.
Combining data from millions of sources including premium news feeds, the web and commercial and public watchlists, Labyrinth uses advanced Natural Language Processing (NLP) and Machine Learning to automatically identify the warning signs and alert on client risk which analysts can then fully investigate.
Ripjar’s intelligence-grade technology provides more efficient and effective ways of detecting the hidden risk of financial crime, corruption, bribery, modern slavery and other predicate offenses that are essential to managing compliance and reputational issues. Our proprietary entity resolution technology’s market-leading accuracy reduces false positives and ensures that news data in dozens of global languages, scripts and other permutations are also automatically searched to create consistent and comprehensive risk management.
With the amount of online content and news data growing every day, on-boarding and monitoring clients may require an abundance of caution to manage the clear risks of financial crime and reputational damage, however with smart technology such as Labyrinth, that risk can be managed more easily, effectively and securely than ever before.
Jeremy Annis, CEO
Ripjar
