Online lenders enlist AI-driven behavioural analysis in the fight against fraud
- A survey conducted by PwC found that in 2018, 49 per cent of respondents said their companies were victims of fraud, up from 36 per cent in 2016
An online buyer picks the most expensive product in the catalogue without doing a price comparison, carries out the transaction very early in the morning, and hesitates when typing in personal details.
This type of behaviour would raise a red flag among those tracking online fraud, and while this work has been done manually by specialist staff, financial institutions are increasingly turning to AI to help.
“Behavioural data analysis by artificial-intelligence tools is more efficient to detect fraud than manually-based approaches,” said Shi Hongzhe, technology head of the US-listed consumer finance platform Lexin, which launched an AI-driven risk management platform aiming at detecting and preventing loan fraud.
“Many fraud cases cannot be identified by man-made rules,” he said.
Loans used to be approved largely based on the amount requested and the standing of the borrower, but the increasing rate of online fraud has forced the finance industry to look beyond its traditional methods of determining the reliability of a borrower. A survey conducted by PwC found that in 2018, 49 per cent of respondents said their companies were victims of fraud, up from 36 per cent in 2016.
The application of AI, specifically predictive machine learning algorithms, can help detect and stop fraudsters by analysing their mobile online interactions, including the speed in which they type in personal data and the time of day they visit websites.