Utilising AI to Prevent Financial Crime

Utilising AI to Prevent Financial Crime

The convergence of open banking, data protection regulation, digitalisation of services and advancement of technology and artificial intelligence has caused profound and prolific changes to the financial services industry. It has also opened new doors and fresh opportunity for fraudsters, who are equally taking advantage of new technologies and the reams of data that now exists in the banking ecosphere.

Keeping transactions secure as financial organisations move into a world of open banking is a race that gets faster by the launch of a new banking API. Risk management, cyber security and fraud strategists need to collaborate to stay ahead of the competition, while addressing the needs of the new digital customer, which includes the hefty task of protecting their data.

Questions about liability in multi-party transactions and ever-increasing systems and protocols abound, as businesses transform to an end-state not yet known. New attack vectors in transactions and account opening come to the fore on a daily basis. How can banks utilise Machine Learning (ML) and AI in the fight against fraud in this real-time and fully digital marketplace

With the emergence of open source technology, is there scope for data sharing to arm organisations with real-time information and anomaly detection? Could business functions communicate better internally to support the fight against fraud?

This research paper by Finextra, in association with Feedzai, gathers the views of several senior data science and fraud experts from across the financial services industry on how to tackle fraud with AI as open banking and digitalisation continue to evolve.


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