The results
4 months
to go live across all correspondent banking
1
global solution for transaction monitoring and customer risk assessment
All
countries of operation with reduced false positives
Key takeaways
- The world's largest cooperative financial institution (~$1.9 trillion in assets, 7,200 branches) was fined for failings across customer due diligence, transaction monitoring and alert investigation after changes in local financial regulation.
- ThetaRay deployed a single machine learning solution for transaction monitoring and customer risk assessment, giving the compliance team centralized visibility across all business lines and transactions.
- The ThetaRay solution went live across all correspondent banking in 4 months, before the deadline established by the regulator.
- ThetaRay reduced false positives in all countries where the bank operates while identifying unknown typologies of financial crime.
The challenge: regulatory fines and unmanageable false positives
The world's largest cooperative financial institution (~$1.9 trillion in assets), with a regional bank network of 7,200 branches, was struggling to stay compliant with its existing financial crime detection systems. Following changes in the local financial regulation, the bank was fined for failings across customer due diligence, transaction monitoring and alert investigation.
The compliance team was dealing with unmanageable levels of false positives, and potentially missing financial crime, because of multiple legacy rules-based solutions. The result was increasing costs and failure to comply with regulatory requirements.
Project scope: proof of concept (POC)
The bank was looking to replace its legacy rules-based solutions with a machine learning solution across the entire Current Account (CA) and Corporate Investment Banking (CIB) portfolio. The bank also intended to deploy the solution across all lines of business globally.
Objectives
- Implement a solution that could be globally deployed in less than 6 months across all of correspondent banking.
- Extend coverage to include the financial institution's global cash management, trade finance and capital markets.
- Deploy a machine learning customer due diligence solution that could transform the current manual and static approach into a dynamic, real-time customer risk assessment process for all customers.
- Ensure compliance with local and global regulators.
The solution: one machine learning platform for monitoring and risk assessment
ThetaRay deployed a proprietary global single machine learning solution for Transaction Monitoring and Customer Risk Assessment. The solution significantly reduced risk, identifying unknown typologies of financial crime, while reducing false positives in all countries where the financial institution operates.
The results
Global single solution deployment
ThetaRay deployed a single solution for Transaction Monitoring and Customer Risk Assessment, which gave the compliance team centralized visibility of all business lines and transactions.
Substantial reduction of false positives
ThetaRay significantly reduced the number of false positive alerts. By establishing normalcy based on the data, the machine learning transaction monitoring solution detected abnormal behavior, ensuring only true positives were alerted.
Improved risk detection
ThetaRay Transaction Monitoring successfully identified unknown financial crime, enhancing the bank's detection ability and achieving significant risk and cost reduction.
4-month project turnaround
The solution went live across all correspondent banking in 4 months, lowering the financial institution's risk exposure. This was achieved before the deadline established by the regulator.
Regulator satisfaction
By introducing more robust and dynamic transaction monitoring and client risk assessment solutions across its global framework, the financial institution was able to turn its compliance failings into recognition as a leader in financial crime detection.
Frequently asked questions
What is machine learning customer risk assessment?
In this Tier 1 bank project, machine learning customer risk assessment replaced a manual and static customer due diligence approach with a dynamic, real-time customer risk assessment process for all customers.
Why was the Tier 1 cooperative bank fined?
Following changes in local financial regulation, the Tier 1 cooperative bank was fined for failings across customer due diligence, transaction monitoring and alert investigation, driven by multiple legacy rules-based solutions.
How long did the ThetaRay deployment take at the Tier 1 bank?
ThetaRay's solution went live across all of the bank's correspondent banking in 4 months, ahead of the bank's objective of less than 6 months and before the deadline established by the regulator.
Can one solution handle both transaction monitoring and customer risk assessment?
Yes. ThetaRay deployed a single global machine learning solution for Transaction Monitoring and Customer Risk Assessment, giving the bank's compliance team centralized visibility of all business lines and transactions.
How does ThetaRay reduce false positives in correspondent banking?
ThetaRay establishes normal behavior based on the data and detects abnormal behavior, so only true positives are alerted. At the Tier 1 bank, this reduced false positives in all countries where the bank operates.
