Authorised Push Payment (APP) fraud losses are expected to climb to $612 million in India by 2026 from $330 million in 2021— a record CAGR of 13.15 percent — according to Scamscope, a new report by global payments software company ACI Worldwide and GlobalData, a leading global analytics firm.

APP fraud scams involve fraudsters tricking their victims into willingly making large bank transfers to them — in many cases, this happens via social engineering across social media networks or via telephone. The growth of real-time payments has given rise to this new type of fraud, which in many markets is growing at a much faster rate than card fraud.

In 2022, one quarter (25 percent) of fraudulent transactions in India are valued between Rs 50,001 and Rs 1,00,000, and a further 19 percent are valued between Rs 20,001 and Rs 50,000. Together, these ranges make up around 44 percent of the total instances of fraud in the country.

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Despite the rising concern around fraudulent payment activities, almost a third of the victims in India continue to show high brand loyalty after they have been victims of APP scams and are more likely to choose to keep their account open, the report further reveals.

The report looked at the most prevalent types of APP scams in three geographies — India, the US and UK — and concluded that Product (37.8 percent), Romance (18.4 percent) and Investment scams (16.3 percent) are the most commonly reported APP scams across all three markets.

The report also provides recommendations for financial institutions to address APP fraud:

Banks must get ahead of incoming regulatory changes and strengthen and optimise both processes and technologies in the fight against APP scams.

Robust technology solutions are needed for the collection of more and better customer data — behavioural data is key to tackling social engineering.

Better collaboration: banks at the initiating and receiving ends of transactions must collaborate more closely to better understand where money is being sent and why. That means creating a network of intelligence based on the sharing of fraud signals in metadata format, and in real-time.

Banks must get serious about disrupting mule account networks. That means monitoring money coming into as well as out of customers’ accounts and analysing the behaviour of those accounts.

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