“The financial industry is shifting towards real-time data analysis, deploying technologies such as artificial intelligence, machine learning and the cloud in transitioning towards a digital ecosystem.”?

Payments fraud is a significant challenge for banks and is set to become more problematic as payment channels and payment services providers (PSPs) proliferate, regulation reshapes the way payments are transacted and the world migrates away from cash towards electronic, often real-time, payments.

Combating real-time payment fraud continues to be crucial for banks as payments transactions become more innovative and real time schemes are rolled out globally. Many leading banks have started adopting ML for financial fraud and management of false positives. A combination of ML- and AI-based solutions have the potential to deliver business benefits and operational efficiencies to financial institutions as they battle payments fraud. Now is the time to act – banks must move away from the static, rules-based business model of payments fraud detection and take advantage of new technologies including AI and ML to switch to real-time controls, checks and balances. Fraud detection systems must be flexible to adapt to changing data and fraud scenarios. To do this, a culture of transition towards digital transformation must exist throughout the organisation.

In Europe, the revised Payment Services Directive (PSD2) allows third party developers to directly interact with a partner banks’ customers, raising questions about the use of customer data by the third parties and extension of the security boundaries. This trend towards open banking is being adopted elsewhere in the world, including in Australia, the US and Hong Kong. In the increasingly networked ecosystem of payments, identifying fraudsters will be a challenge, but under PSD2, financial institutions are required to monitor all transactions for fraud-related activities.

The traditional, silo-based approach to fraud detection is fast becoming obsolete. For too long, banks have lagged in their ability to align fraud detection with the speed of transactions as payments move away from cash towards CNP (Card Not Present) transactions. The financial industry is shifting towards real-time data analysis, deploying artificial intelligence, machine learning and Cloud capability to transition towards a digital ecosystem. Banks must ensure they stay ahead of the increasing technological threat from criminals and fraudsters.