Preventing fraud in real-time payments
What insights can the U.S. take from early real-time payments adopters?
Change is constant in the banking and payments industry – and organizations that can keep pace with this change while outsmarting the associated risks, gain a competitive advantage.
One significant change across the industry currently is the widespread move to real-time, account-to-account payments.
Many are saying that it’s about time, not least because real-time payments support the modernization of our banking systems, reflecting the increasingly real-time nature of commerce and the API economy.
Also known as faster payments, instant payments and RTP, real-time payments offer opportunities for new payments use cases and impact other payment types – both in obvious ways (such as the displacement of cash and checks) and surprising ways (such as the convergence of bank payments and cards infrastructures over time).
Real-Time Payments are coming to the U.S.
Now, real-time payments are coming to the United States, with The Clearing House launching its Real-Time Payments (RTP) service in 2017.
Banks and payment service providers are already seeing advantages from real-time payments, including:
- Developing innovative real-time payments products that meet the needs of the API economy
- Reducing cash and check usage
- Introducing new facilities, such as Request for Payment (RFP), which enable one party to request a payment, to which the payee may initiate and authorise a credit transfer
What associated risks could the move bring?
Alongside the benefits, any advance in payments technology also bring its challenges to banks – particularly their fraud operations teams.
Real-time payments are processed as they happen and cannot be reversed – there is no time for manual fraud review steps. Not all these payments are low-value person-to-person payments. In the U.K., for example, the average transaction through Faster Payments is approximately $1,000.
So, criminals see opportunities to exploit vulnerabilities in existing fraud systems – particularly when you need to make fraud decisions almost immediately.
From what we’ve seen in the UK & Europe with balance transfers and transfer-to-bank fraud, there are three key areas of risk for organizations to manage in the move to real-time payments:
- Making accurate fraud decisions quickly This industry shift means tackling fraud in a new market space, without relying on historical data. It is essential that instant payments systems have integrated fraud systems that keep one step ahead of the criminals to make informed fraud decisions within seconds.
- Preparing for targeted fraud attacks Many existing fraud systems have no automated decision workflow and rely on manual review. Fraudsters may exploit this vulnerability, hitting banks with a number of attacks in short timeframes, similar to a brute force attack. Fraud teams will become inundated with cases and need to act quickly to protect their customers.
- Managing the risk of increasing fraud operations costs Existing fraud systems which rely on manual review and static data cannot take the strain of new threats, producing too many false alerts for operations teams to deal with. To avoid increasing recruitment costs, organizations need to understand individual payment behaviour holistically, in real time, to make fast, accurate, automated decisions.
We saw similar rapid change in fraud management when the U.S. moved to EMV in 2015. Understanding real-time individual behaviour, particularly in digital environments, was essential to cope with the consequent rise in Card Not Present fraud.
So, how do we tackle these real-time payments risks?
Time for some good news. What we’ve learnt is that banks can keep one step ahead by understanding every individual in real-time, without facing high implementation or upgrade costs.
We know that banks see implementing real-time payments as the foundation of their future payments architecture. They are turning to modern systems fit for this purpose, rather than relying on heavyweight, costly, turn-of-the-century technology. The same applies to their fraud platforms.
Advanced machine learning technology uses adaptive behavioural analytics to monitor individuals in real time and spot exactly when behaviour changes. By detecting anomalies across every event and channel, banks can spot and block new fraud attacks as they occur.
Icon Solutions’ partner Featurespace’s ARIC platform uses this exact approach to give banks informed, automated business decision making – increasing client control over customer protection, without blocking genuine customer activity.
What’s the next steps for organizations wanting to embrace real-time payments?
With lightweight payments frameworks, machine learning and adaptive behavioural analytics, banks making the business case for real-time payments systems no longer need to face high implementation or upgrade costs.
First published on Bobsguide