Sibos 2018: Machine Learning to fight fraud in real-time payments

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With real-time payment systems receiving mass adoption around the globe, consumers, merchants, and financial institutions want to do payments, settle bills and transfer money faster and more secure.

The need for speed can, however, result in the increase the opportunities for fraud, and according to experts at the day three Sibos session on combatting fraud on real-time payments, Machine Learning can be used on a broader scale to reduce such risks.

Panelist David Rich, the executive vice-president, Mastercard, said: “ML or decision science is key. The only way to beat real-time fraud is to play in real time and this can only be done on an ML basis. We need to be predictive and not reactive.”

Westpac’s global transaction services general manager, Di Challenor explained: “There’s a real focus on fraud in the NPP world. The NPP has rich data and great benefits, but as a bank, we have to assess it and ensure there is no financial crime risk. We’re looking at digital IDs to protect money movement and citizen information.”

Fellow panelist HSBC’s global head of correspondent banking, Barbara Patow commented: “We need to bring regulators on the journey and as a community work together and evolve together.”

 

 

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