1 Introduction

Oracle Financial Crime and Compliance Management Cloud Service makes use of the Cloud Matching Service, which provides a flexible and customizable strategy for matching customer records to watch list records. Sanctions screening typically requires the business to employ tightly-defined, zero-tolerance matching policies that will identify every possible match against a sanctions list. In these cases, the additional review work of lower probability matches will be necessary.

By contrast, a business carrying out PEP screening may choose a strategy of finding and investigating only the most likely matches against the PEP list, and the additional work required to confirm or eliminate weaker matches may not be cost-effective for the business.

Oracle Financial Crime and Compliance Management employs matching rules widget to configure the rules for screening.

These can be enabled and disabled as needed, to tune the behavior of Oracle Financial Crime and Compliance Management Cloud Service to your requirements. The matching rules are built around name matching.

Other identifiers are also used in the matching rules, but their main purpose is to rank matches by strength, and thereby to enable a most-likely approach to review potential matches.

For example, strong matches to Sanctions lists should be regarded as the most urgent matches, requiring immediate attention. Strong matches to PEP records will require follow-up, but may not be so urgent. Looser matches to PEP records may not be worth the time and operational cost of review.

In general, the looser the match rule, the more likely it is to raise false positives. It is not possible to eliminate all false positives, especially if there is a requirement to identify all true matches.

Tuning the matching strategy is, therefore, a trade-off between the proportion of true matches that are not detected and the work required to manually eliminate false positives. This will be evident in the examples in this document.