Reported by FinTech Global

According to Moody’s, a fundamental theme underpins know your customer (KYC) risk screening: names. A person’s name is their key identifier and in screening processes names are of course vital, but names are very rarely unique – unlike the people who claim them.

Names can be complicated. Name matching is especially difficult in a global dataset of names captured by sources including government watchlists and adverse media from different countries — including names in more than 70 languages and numerous scripts. The complications grow when the names include those of risk-relevant persons and organizations, some of whom may be deliberately trying to avoid detection.

To manage this process, Moody’s has established an intelligent screening solution supported by a team of cross-functional screening specialists. The team combines qualitative anthro-linguistic expertise with access to tailored quantitative data science algorithms and machine learning techniques to overcome name-matching challenges and deliver accurate results.

Moody’s has three main avenues for identity to dismiss ambiguity among common names:

1. Grid profiles maintain high-quality standards on identifying data, including date of birth, addresses, and aliases, particularly among premium content profiles enhanced with entity-based research.
2. Customisable filters for alias, address and date of birth analyse and rule out matches with conflicting identity information.
3. Review provides additional post-match research on Grid profiles to reduce alerts to high-confidence matches.

Moody’s Grid profiles capture all available aliases as recorded in adverse media coverage to ensure identification of risk entities. Further research is included with our high-risk premium content sets, such as politically exposed persons (PEPs) + family or close associates. Review screening also includes critical watchlist logic and optional OFAC-search style algorithms to detect high-risk sanctioned entities.

5 steps to overcome name matching challenges using intelligent screening

Going from many names to a few and then arriving at a final alert can be done with intelligent entity screening processes in the following five steps:

1. Conduct initial searches: Use multiple search algorithms to generate a broad list of potential matches based on the names you are screening.
2. Rescore results: Refine the search results by considering the cultural context of names, applying specific rules for certain cases, and making necessary adjustments based on additional information like date of birth (DOB) or addresses.
3. Apply filtering: Narrow down your results further by implementing firm-specific rules and apply custom filters that account for the severity and types of risks associated with the entities.
4. Review: Use our AI system to score the alerts and automatically suppress false positives. Review the remaining matches against custom guidelines specific to your firm.
5. Make alert decisions: Have analysts review the shortlist of potential matches. They will make final decisions based on the integrated system’s data and the context of the inquiry.

Read full report: https://fintech.global/2024/06/04/overcoming-kyc-name-matching-challenges-with-intelligent-screening/