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Ripjar Expands AI Risk Profile Capabilities with Generative AI

Enhanced capabilities will utilise large language model (LLM) technology to provide users with fast and concise AI Summaries of adverse media mentions for high-risk entities. 

LONDON, 22 November 2023: Ripjar, the trusted provider for monitoring and investigating threats, risks and criminal activity, today announces the launch of AI Summaries, an extension to its Labyrinth Screening platform.

AI Summaries builds on Ripjar’s existing AI Risk Profiles feature, which assembles screening information into single 360o profile views for people and companies, identifying areas of relevant risk across adverse media, sanctions, watchlists and politically exposed persons (PEP) data.

Powered by generative artificial intelligence (GenAI), AI Summaries are part of Ripjar’s RiskGPT programme which utilises the latest AI and machine learning to reimagine and revolutionise complex compliance tasks. 

Each summary takes a profile’s consolidated adverse media results and produces a clear narrative overview for analysts to review. Typically consisting of two to five paragraphs of text, with links back to the original sources, AI Summaries provide full provenance to the original data.

The capability significantly enhances and simplifies the screening process, making it even faster for analysts to review the relevant adverse media risk identified within a profile. The new approach drives effectiveness as super-charged analysts work better with clearer data.

When used together, AI Risk Profiles and AI Summaries reduce the average time to assess new and existing customers by over 90%. By reading a profile summary, analysts save up to eight minutes compared to reviewing significant media extracts, and even more time compared to reading the articles in full.

This new capability comes at a time when compliance analysts are under increased pressure to stay ahead of global regulations and to fully utilise a broad range of information sources to identify risks. By harnessing the capabilities of artificial intelligence through AI Risk Profiles and AI Summaries, organisations can transform their customer screening and achieve effective risk identification at scale.

Jeremy Annis, Ripjar’s Co-Founder and CEO, stated: “Combined with our existing AI Risk Profiles, Ripjar’s new AI Summaries represent a major step forward in screening. Financial institutions are grappling with rising costs and time pressures when conducting compliance activities, including customer and counterparty screening. By distilling complex adverse media data into concise narratives, AI Summaries provide organisations with the information they need to make critical decisions quickly and accurately. We’re proud to be transforming the battle against financial crime by developing innovative solutions which leverage the power of AI in a responsible manner.”

Ripjar has pioneered the use of AI in compliance. Within the RiskGPT programme, the company is investing in new ways to combine the latest generative AI with traditional forms of machine learning to optimise for efficiency and effectiveness within a strictly regulated domain. 

A range of further innovations is currently in development, extending both AI Risk Profiles and AI Summaries. Set to launch in early 2024, the company’s next addition to Labyrinth Screening will utilise large language model technology to better support analysts in reviewing and dispositioning financial crime alerts, with further innovations set to launch soon after.

Read more about Ripjar’s AI Summaries launch.

About Ripjar

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.   

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