Arachnys And AI To Reduce False Positives, Joan McGowan, Celent Research
In Part 1 of this two-part report, AI Made to Reduce False Positives, Part 1: Detection Capabilities and Use Cases, Celent looks at the limitations of transaction monitoring systems and the crippling impact of high false positive rates on the industry.
The report explains the causes of false positives and shows why artificial intelligence (AI) has the potential to be a powerful accelerator of surveillance systems and more accurate risk identification. It also explores the combinations of AI technologies that can be leveraged to help reduce false positive rates, while being explainable to the regulators.
David is a former investigator who has advised banks, law firms and leading multinationals on corruption, fraud, money-laundering and other risks. He is a regular speaker on the use of technology for collection, analysis and reporting in a KYC/AML context. He graduated from Oxford University.