Dynamic risk profiling: PEP and sanctions screening that’s a whole lot smarter

Watchlist Screening

In the business world, falling in with the wrong crowd is to be avoided at just about any cost. The recent money laundering scandals that have rocked Credit Suisse bear testament to this, where the financial institution has been found guilty of failing to uphold appropriate anti-money laundering (AML) measures related to a Bulgarian cocaine trafficking gang, amongst other charges. Closer to the political arena, the war in Ukraine has seen global sanctions against Russian entities reach new heights, with companies taking additional precaution to avoid such business relations.

Then there is the issue of fraud and corruption, where such accusations are splashed across media publications worldwide on a daily basis, with prominent names stepping in and out of the limelight. For financial institutions, while a sanctions and politically exposed person (PEP) check is generally locally mandated, it is also just best practice. Sanctions screening AML solutions and the automated and perpetual profiling of the politically connected is more relevant than ever, with businesses turning to artificial intelligence (AI) to mitigate their compliance risk. AI is a term thrown about a great deal in the business arena in recent years. Yet, what is it that AI is actually shaking up when it comes to PEP and sanctions screening?

As a brief introduction, PEP relates to those individuals who hold a significant public position, be it locally or internationally, such as government ministers or heads of judiciary. Sanctions relate to those persons, entities or countries with whom it is prohibited to conduct business, by way of regulatory order from an overarching authority. OFAC screening, for instance, is the check performed by companies as to whether a customer is on the watchlist held by the Office of Foreign Assets Control, a division of the U.S. Department of the Treasury. A sanctions list pertains to criminal activity which is seen as a threat to the global community, from war crimes and terrorism to drug and human trafficking. PEPs, on the other hand, elevate business risk as they are considered more likely to engage in financial corruption.

Given the diverse and disparate data sources for such watchlists, how does a company ensure accurate and real-time screening, with an eye to minimising time-consuming and money-draining false positives? Mismatches and omissions are all too common where data quality is questionable, arising from such issues as spelling and date of birth errors to poor formatting and missing information. Where thousands of names need to be screened, the complexity is magnified. This is why our end-to-end AI-powered solution was born, where machine learning has dramatically reduced compliance error and risk. A broader spectrum of information can now be incorporated into AML practices, where machine learning, as the name implies, learns from feedback about the accuracy of historical matches to continuously reduce false positives over time.

From a PEP perspective, we start by building structured lists and social graphs by scraping government websites and public information relating to political positions. Global PEP and sanctions lists are also integrated, where these are continually and automatically updated. Individual clients often choose to incorporate specific blacklists and whitelists, which serves to augment risk mapping. From here, we devise an extensive risk network, plotting connections and relationships to political and embargoed players, coming to understand who holds sway. This influence, risk of criminal activity or probability of reputational damage may not always be obvious. AI’s next-generation coverage of social media is useful in this regard, mapping relationships which may not make news headlines, but are nonetheless politically and economically significant. Slowly, the bigger picture comes into focus, with bits of information collected from here and there, as data sets are curated, evaluated, amalgamated and used to gauge risk. Not only is it a means of zooming out and curating a holistic risk map, but the process is dynamic. This is key to ensuring that risk assessments are perpetually up-to-date, with AI feeding in new information on a just about minute-by-minute basis.

Ultimately, our algorithms bridge the gaps in continuous PEP and sanctions screening. Our AI-based AML suite is customisable and configurable, offering a single solution for screening multiple watchlists and profiles. It’s about de-risking your company using the best in cutting-edge KYC and AML / CTF technologies.

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