Transaction fraud monitoring lies at the heart of fraud prevention for acquiring banks, and while the effort in decreasing fraud rates has advanced significantly, so has the sophistication of fraudsters themselves.

The emergence of AI within fraud solution models has come to the fore in recent years and along with it, newly realised appreciation of the value of transaction data, current and historic. Banks need to get to grips with processing and utilising these data to full advantage, to inform a robust and futureproof strategy which can both increase approvals and reduce fraud.

For transaction monitoring solutions to drive value, serving both merchants and acquirers alike, intelligence on any given transaction needs to be issued in real time before the submission of authorisation.

Approval rates, pricing, customer-centricity, and fraud rates are always going to be key differentiators in a very competitive market. Within these parameters, banks need to continually improve their service to remain competitive, while navigating the various tools and techniques that are rapidly emerging. Different business models prioritise different aspects of case management and scoring, using traditional rules-based methods and more data-led AI and ML approaches.

This Finextra industry sentiment report was produced in association with Brighertion, a Mastercard company. It is based on several industry interviews, through which we aim to take a pulse on the industry’s general appetite for real-time, AI-driven, data-rich transaction fraud monitoring, and the various models, technologies, and priorities that shape acquirers’ anti-fraud strategies.

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