A US property & casualty insurance company was experiencing high volumes of false positives, as well as inefficiencies in their case review process. More importantly, they had concerns about the quality of their data and the potential risk this presented of missing true suspicious activity. Aware of FinScan’s expertise in data quality for compliance, they brought the AML vendor on board to evaluate and help correct the issues that were negatively impacting their screening program.

By assessing the quality of the data being fed into the company’s sanctions screening software, they discovered a plethora of inaccuracies and inconsistencies that posed a real threat of missing true hits and putting the company at risk of damaging fines.

The data quality assessment revealed three primary issues that had the potential to cause false negatives: 2.4 million records (86% of the file) were missing date of birth information, 18K records (0.64%) lacked first name information, and an additional 40K records had multiple names combined in the name field or names embedded in non-name fields and therefore were not being screened. Additionally, FinScan identified that more than 20% of the customer records were duplicates, which would have serious implications on the productivity of their team’s alert review process.

Using FinScan Data Prep, the client was able to identify, link, and consolidate duplicate records from all source applications to present only the surviving record for screening, which eliminated the need to review the same alert multiple times. The screening results for each source record were then captured and fed back into the originating applications without disruption.

Finally, by fine tuning FinScan’s matching algorithms, the client was able to assign more importance to crucial information such as name, gender, and country while using date of birth as a secondary matching criterion. This ensured that incomplete data would not negatively affect the screening results and that the matching accuracy of those with complete information would be improved. Furthermore, by leveraging FinScan’s data quality capabilities to parse their 2.8 million records and create new records where needed, the company was provided with peace of mind that they were screening 100% of their customers against the OFAC list.

Thanks to FinScan’s integrated data quality engine, the client was able to mitigate risk by correcting data errors and uncovering 407 customers on the OFAC list that would have resulted in substantial fines if undetected. Removing 560,000 duplicate alerts saved them 2,796 hours of manual review time annually – equivalent to $75K in FTE costs. The reduction in risk and increased effectiveness of their screening program have proven to be invaluable to the success of the organization’s AML compliance efforts going forward.

If you are ready to take control of your data and your screening process, speak to our experts today.