AI in Fintech Helping Detect Fraud, Assess Risk
AI is being applied in the banking and the financial industry to meet demands of customers in creative ways, with many startups participating with new technologies and ideas. Here is a review of selected efforts involving AI in finance.
Financial services firms have always struggled with massive volumes of records that need to be handled with maximum accuracy. Firms focused on technology applied to finance – fintechs – were perfectly positioned to demonstrate what AI can bring to the table.
“AI has been a game-changer for FinTech. Few verticals are such a perfect match for the improved capabilities brought by the AI revolution like the financial sector,” stated author Dr. Claudio Buttice in a recent account in techopedia.
Spending by banks on AI and machine learning was expected to reach $5.6 billion in 2019, according to an estimate from McKinsey.
AI is increasingly being applied to fraud detection, including the fight against account takeovers (ATOs), a cybercrime of identity theft that causes an estimated $4 billion losses each year. Some 40 percent of all frauds that occurred in ecommerce in 2018 were attributed to hijacking of identities virtually. Smartphones are considered the weak link, with mobile phone ATO incidents up 180 percent from 2017 to 2018.
Startup Datavisor offers the Global Intelligence Network to prevent these cyber threats. The platform collects an enormous volume of data including IP addresses, geographic locations, email domains, mobile device types, operating systems, browser agents, and phone prefixes from a database of over four billion users. The database is analyzed to help detect suspicious activity, prevent incidents and help to remediate account takeovers.
Founded in 2013 in Mountain View, Datavisor has raised $54.5 million so far. CEO and founder Yinglian Xie was recently quoted in a piece in Pymnts.comthat the recently approved government Paycheck Protection Program (PPP) is a perfect opportunity for fraud, with businesses seeking a share of the $350 billion in funding in a mad rush.
“That’s what makes PPP a particularly good target for so many types of fraud,” Xie stated. “It’s targeted at small businesses who are applying by the millions all at once with the kind of surge of applications online far beyond what banks would process on a day-to-day basis. And with everyone encouraged to apply online, many banks weren’t ready from an infrastructure perspective on the back end, which delayed the launch or meant it launched with various bugs.”
AI is also being employed in the fight against money laundering, a big challenge for banks worldwide. The criminals use sophisticated methods to try to bypass rules employed by many financial institutions, so they remain undetected.
Reliable predictions are difficult, with available public datasets too small; the number of false positives today is considered unacceptably high.
