Banking | Real-time payments need real-time security

Representative image

Damon Madden

The COVID-19-related lockdowns compelled many of us to adapt to a digital life: transforming the way we pay, and get paid. However, the rush to online and digital payments, by new digital converts, also provided huge opportunity for the unscrupulous. The result: cybercrime soared in India, as it did elsewhere.

This rise in fraud was also reflected in consumer sentiment; Indian consumers’ concern around fraud rocketed from 47 percent at the beginning of the pandemic to 71 percent now. With the surge in fraud, banks became the first point of contact for many victims, with 60 percent opting to call or visit the branch.

Given the impact such fraud has on customer wellbeing, trust, and user experience, the more resources and solutions banks have at their disposal to combat crime, the better it is for consumers.

Here are three steps banks can take to mitigate fraud, and, thereby, ensure customers safety and satisfaction.

Real-time Fraud Prevention

Last year saw the use of real-time payments rise exponentially. India, the global real-time payments poster child, led the way with over 25 billion real-time transactions. But where real-time payments move freely, fraud moves faster. The net effect: the more ways we pay and more places we pay, the more opportunities for cybercriminals.

Traditional approaches to cybersecurity are reactive, and rule-based — scanning for a set of ‘known’ indicators that signal an attack, and then remediating it (which is often too late). Given this magnitude of risk exposure, the time for traditional reactive solutions has past us. Machine learning and AI, when combined with behavioural analytics (that scan for patterns and inconsistencies) can help financial institutions bolster real-time protection.

In the digital payments era, those banks that commit to robust real-time fraud management will be more resistant to fraud, and see their risk profile decrease, without compromising on customer experience.

Smart Tech

The increase in potential attack points, combined with digital payments’ thinner margins, ensure banks feel the impact on profitability, and return on investment. As a result, the financial community is coming together, via Adaptive Machine Learning, to deliver real-time fraud scores, to help turn the tide in favour of the banks.

Federated machine learning, an emerging AI 2.0 solution, is also enabling banks to supplement proprietary data, and improve the performance of their models without compromising IP, data privacy, or compliance obligations. By gaining access to a vastly-expanded source of real-time fraud and risk data analytics, payment networks can grow their adoption of real-time payments while mitigating their fraud exposure. Another winner in this approach are the smaller financial institutions with limited resources—which can now build and leverage the shared intelligence and economies of scale for managing real-time risks.

Getting Proactive

Personal Identifying Information (PII) and other identity data is now more valuable to fraudsters than card or account details. Such data in the wrong hands can be used to access lines of credit often totalling more than a customer’s total savings, and impacts customers well beyond the repayment of funds. So, if banks are to maximise protection for customers, and maintain the integrity of their institution, data protection at every stage of the customer lifecycle becomes an imperative.

Behavioural biometrics, for example, can help to determine whether the data entered was by a customer or by a fraudster using stolen or synthetic identities. A behavioural biometric profile of account holders significantly reduces the risk of account takeover attacks. With real-time payments, once a transaction is ‘pushed’, it currently cannot be rescinded. Hence, scammers use social engineering to create scenarios which manipulate the customer to push the payment.

Behavioural biometrics can also reduce vishing or Authorised Push Payment (APP) scams by identifying unusual behaviour patterns such as how a user navigates a page, their typing speed and cadence for entering information, or hesitations, if any.

As the payments landscape continues to evolve, and real-time payments gain dominance, businesses, payment companies, banks, and regulators will increasingly work in tandem to stay one step ahead of fraudsters. The only comprehensive defence against this evolving threat is a combination of advanced real-time technologies, behavioural analytics, increased consumer security awareness, and community-based intelligence.

In a real-time future, cybersecurity is a community effort, and it will be up to everyone to play their part.

Damon Madden is Principal Fraud Analyst, ACI Worldwide. Views are personal, and do not represent the stand of this publication.