Top Japanese Bank Identifies Ultimate Counter Parties and Correlates Risk with Detection Model Rules
A top Japanese bank was lacking the ability to assess the risks associated with the ultimate originators and beneficiaries of the wire transactions that it processed and cleared. Unlike its regular customers, these entities were not being reviewed through any Know-Your-Customer (KYC) processes or any of the Customer Identification Programs (CIP). Further complicating matters of identifying these entities and ascertaining relevant information was the lack of standardized referential data and distinct identifiers.
The Matrix-IFS team developed a unique methodology to identify and classify the external originators and beneficiaries into risk-based categories using inconsistent data attributes and an automated process to parse high-risk geographic information from the wires’ free-form text. The team combined the risk of the entity with the risk of the domicile country in order to establish a risk score per wire transaction.
By aggregating the risked-based scores of the transactional activities, a risk profile was created for each of the external entities. Once the same methodology was applied to the transactions alerted by the detection scenario models, an enhanced risk-rating system was implemented so that the detection scenario models would produce a higher percentage of high-risk transaction wires, while the low-risk wire transactions would not be alerted.
As a result, false positive alerts were reduced by 40%.
Additional enhancements are being applied to both the entity classification process and transactional risk classification process to optimize tuning of the rules and increase the scrutiny on the higher risk wires while reducing scrutiny on the low risk wires to support the bank’s business growth and diversification.