Effective continuous Fraud and/or Money laundering detection – business rules plus anomaly detection: 1+1=3!
Implementing and optimizing business rules in combination with anomaly detection can be challenging, but is unavoidable if you pro-actively want to meet regulatory requirements.
Business rules are predefined rules and thresholds established by organizations to identify specific patterns or behaviors associated with fraud or money laundering activities. These rules are typically based on expert knowledge, regulations, industry best practices, and historical data and are effective for detecting known fraud patterns. They can provide real-time alerts when a match is found.
Anomaly detection techniques are designed to identify unusual or unexpected patterns, behaviors, or outliers in (grouped) data that might indicate fraudulent or suspicious activities. Anomaly detection algorithms analyze data against normal transaction patterns and identify activities that deviate significantly from the norm and detect novel or previously unknown fraud and money laundering attempts that don’t fit predefined rules.
By combining business rules with anomaly detection, organizations can have a more comprehensive approach to fraud and money laundering detection. They can leverage the coverage and accuracy of predefined rules while also capturing previously unknown fraud/ money laundering attempts through anomaly detection. The complementary nature of both techniques helps reduce false positives and false negatives, improving the overall detection accuracy. Examples of successes: use of cryptocurrency, unexpected international money flows.
Implementing and optimizing a combined approach can present several challenges, including challenges with data integration, data quality/variability, real time processing, model calibration and validation, organizational silo’s, privacy/ethical considerations and regulatory Compliance. With regards to the regulatory Compliance, an organization needs to make sure it aligns with various regulatory requirements, such as anti-money laundering laws, Know Your Customer (KYC) regulations, and privacy laws. Making it even more complex.
In simple words: ensuring compliance and keeping up with regulatory changes can be demanding. “If you think that compliance is expensive: try non-compliance”. This famous quote from former US Deputy Attorney General Paul McNulty will perhaps help you decide to take the next step in adding anomaly detection to your business rules!
There are several key metrics and methodologies to measure the success of continuous detection strategies. Five common approaches that will support you to evidence effectiveness:
> Detection Rate
> False Positive Rate
> Response Time
> Cost/ Efficiency
> External Benchmarks.
SYGNO is specialized in automated model generation based on good behavior and can help you to effectively reduce false positives and increase true positives, by a combined approach. We can accomplish an impressive improvement for you within 3 months.
Contact us for more information or a demo via email@example.com.
Contact us to find out how we can help you respond to the next generation of financial crime.