Hong Kong News

Nonpartisan, Noncommercial, unconstrained.
Thursday, Mar 28, 2024

Online lenders enlist AI-driven behavioural analysis in the fight against fraud

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.

Teradata, a San Diego-based data analytics company, offers AI-driven fraud detection solutions to banks. One of its clients, Denmark’s Danske Bank, employed AI software to cut the number of false positives generated by human-written rules engines by 60 per cent, and increase detection of real fraud by 50 per cent.

Lexin’s self-developed Hawkeye platform, which every day can detect more than 500 potential fraudsters involving 3 million yuan (US$426,000), is an example of how the broader financial-services industry is using machine learning to detect patterns that could signal criminal behaviour.

Algorithms can detect an illicit loan application by scanning for anomalies in certain behaviours and analysing digital information ranging from a device’s geolocation to biometric authentication. For example, the AI platform would send an alert if multiple loan applications pop up from the same device at an unusual time of day, such as dawn, when legitimate customers would not normally apply for loans, said Shi.

Some instalment payment applications could also be flagged as potential fraud if the buyer does not do any price comparisons online, and instead purchases the most expensive one.

In addition, as most online fraud involves identity theft, it can often be detected if the applicant does not fill in personal identification data smoothly, indicating they have not memorised the stolen ID.

Lexin’s other business, an e-commerce platform that offers instalment loans for product purchases, is also the target of scammers. In one new scam, a fraudster gains the confidence of target by convincing them to make small purchases from the Lexin platform on their behalf, offering to pay more money in return. Then the scammer does the same with a more expensive product, like an iPhone or iPad, and does not repay. The targeted “buyer” is left with the responsibility of paying off the rest of the loan.

If multiple similar cases like this are reported over a concentrated period of time, Lexin will push out warnings to its customers through its app.

“As fraudsters adopt new ways for online fraud, new scenarios are added to our system and the platform can issue a warning if similar behaviour appears,” said Shi.

In recent years, financial institutions have started using machine learning to prevent fraud, with some banks deploying the technology in direct response to the rise of more sophisticated cybercrimes.

“Nevertheless, the rate of AI and machine learning deployment as a fraud management measure remains relatively low,” Chris Holmes, senior vice-president of marketing consultancy KAE, said in a report. “We expect that this will not be the case for long, and that deployment in this area will rise significantly in the next two to three years.”

In October, Mastercard introduced its Threat Scan service which can identify vulnerabilities in merchants’ authorisation systems by applying an array of test scenarios that simulate fraudulent attacks.

Rival Visa is rolling out a platform that uses AI algorithms to help detect and prevent credit-card fraud.

“Financial firms detect online fraud by analysing behaviours,” said Shi, regardless of whether the approach used is low tech or high tech. “In the future when AI is more deeply employed, fraud may be detected by analysing facial emotions or voices. We will have a more natural interaction with the AI machines in the finance industry.”

Ping An Insurance, China’s second largest insurer by premiums, is already using face and voice recognition systems to protect its policyholders from fraud.
Newsletter

Related Articles

Hong Kong News
0:00
0:00
Close
It's always the people with the dirty hands pointing their fingers
Paper straws found to contain long-lasting and potentially toxic chemicals - study
FTX's Bankman-Fried headed for jail after judge revokes bail
Blackrock gets half a trillion dollar deal to rebuild Ukraine
Steve Jobs' Son Launches Venture Capital Firm With $200 Million For Cancer Treatments
Google reshuffles Assistant unit, lays off some staffers, to 'supercharge' products with A.I.
End of Viagra? FDA approved a gel against erectile dysfunction
UK sanctions Russians judges over dual British national Kara-Murza's trial
US restricts visa-free travel for Hungarian passport holders because of security concerns
America's First New Nuclear Reactor in Nearly Seven Years Begins Operations
Southeast Asia moves closer to economic unity with new regional payments system
Political leader from South Africa, Julius Malema, led violent racist chants at a massive rally on Saturday
Today Hunter Biden’s best friend and business associate, Devon Archer, testified that Joe Biden met in Georgetown with Russian Moscow Mayor's Wife Yelena Baturina who later paid Hunter Biden $3.5 million in so called “consulting fees”
'I am not your servant': IndiGo crew member, passenger get into row over airline meal
Singapore Carries Out First Execution of a Woman in Two Decades Amid Capital Punishment Debate
Spanish Citizenship Granted to Iranian chess player who removed hijab
US Senate Republican Mitch McConnell freezes up, leaves press conference
Speaker McCarthy says the United States House of Representatives is getting ready to impeach Joe Biden.
San Francisco car crash
This camera man is a genius
3D ad in front of Burj Khalifa
Next level gaming
BMW driver…
Google testing journalism AI. We are doing it already 2 years, and without Google biased propoganda and manipulated censorship
Unlike illegal imigrants coming by boats - US Citizens Will Need Visa To Travel To Europe in 2024
Musk announces Twitter name and logo change to X.com
The politician and the journalist lost control and started fighting on live broadcast.
The future of sports
Unveiling the Black Hole: The Mysterious Fate of EU's Aid to Ukraine
Farewell to a Music Titan: Tony Bennett, Renowned Jazz and Pop Vocalist, Passes Away at 96
Alarming Behavior Among Florida's Sharks Raises Concerns Over Possible Cocaine Exposure
Transgender Exclusion in Miss Italy Stirs Controversy Amidst Changing Global Beauty Pageant Landscape
Joe Biden admitted, in his own words, that he delivered what he promised in exchange for the $10 million bribe he received from the Ukraine Oil Company.
TikTok Takes On Spotify And Apple, Launches Own Music Service
Global Trend: Using Anti-Fake News Laws as Censorship Tools - A Deep Dive into Tunisia's Scenario
Arresting Putin During South African Visit Would Equate to War Declaration, Asserts President Ramaphosa
Hacktivist Collective Anonymous Launches 'Project Disclosure' to Unearth Information on UFOs and ETIs
Typo sends millions of US military emails to Russian ally Mali
Server Arrested For Theft After Refusing To Pay A Table's $100 Restaurant Bill When They Dined & Dashed
The Changing Face of Europe: How Mass Migration is Reshaping the Political Landscape
China Urges EU to Clarify Strategic Partnership Amid Trade Tensions
The Last Pour: Anchor Brewing, America's Pioneer Craft Brewer, Closes After 127 Years
Democracy not: EU's Digital Commissioner Considers Shutting Down Social Media Platforms Amid Social Unrest
Sarah Silverman and Renowned Authors Lodge Copyright Infringement Case Against OpenAI and Meta
Why Do Tech Executives Support Kennedy Jr.?
The New York Times Announces Closure of its Sports Section in Favor of The Athletic
BBC Anchor Huw Edwards Hospitalized Amid Child Sex Abuse Allegations, Family Confirms
Florida Attorney General requests Meta CEO's testimony on company's platforms' alleged facilitation of illicit activities
The Distorted Mirror of actual approval ratings: Examining the True Threat to Democracy Beyond the Persona of Putin
40,000 child slaves in Congo are forced to work in cobalt mines so we can drive electric cars.
×