Technology is the future, and the future is now. Oracle’s Sonny Singh discusses how banks are using emerging technologies such as machine learning and graph analytics to improve financial crime investigations and compliance management.

The complexity and cost of battling fraud, money laundering and other types of financial crime continues to compound for large enterprises – especially financial institutions. Criminals constantly hone their tactics and invent new ones. Transactions grow exponentially in volume and speed, compliance requirements escalate and there’s no pause in sight.

Firms are looking to stem the tide on two fronts: increasing the speed and accuracy of detection and improving the overall efficiency of their investigation and compliance processes.

The evolution of big data and machine learning (ML) technology is coming to bear on both challenges. Here is where we are and where technology is taking the financial industry in these critically important areas.

Economics and Criminal Sophistication Demand Greater Efficiency and Accuracy

The stakes of compliance are high and getting higher, driven by both the sheer number of regulatory changes financial firms need to track and heed and the extreme cost to compliance.

The RegTech Council reported a Bain & Co.

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