Advanced AI-based analytics makes credit and debit cards smarter


Banking and fintech companies have been using artificial intelligence (AI) for a few years to improve credit and debit card fraud detection, analyze defaulting patterns, warn users against overspending, and even help determine their expenses. Some companies have also started using predictive analytics to improve how credit and debit cards are used in real time.

For example, Philadelphia-based fintech company, which launched its “Unicorn Card” two years ago, uses a credit optimization tool. The card was authorized by the Visa payment network and issued by the Wilmington Savings Fund Society, FSB. The credit optimization tool uses an artificial intelligence algorithm to improve the user’s debt-to-credit ratio, which accounts for up to 30% of a FICO score that assesses a person’s creditworthiness in the United States. United. Apple also uses AI to determine a user’s credit limit on the Apple Card.

Closer to home, Gurugram-based financial technology company OneBanc has developed a card to connect various banking systems. The company, which has 60 companies among its partners to provide cards to employee payroll accounts, says the card consolidates all of the employee’s payments into one. OneBanc’s card uses the company’s smart platform to include employee benefits such as meal balances on a single card. When the card is swiped, it makes a real-time decision on which balance to use to make the payment.

OneBanc has already partnered with RuPay and Visa, and said its “AI card” will hit the market in the next four to six weeks.

Vibhore Goyal, Founder and Managing Director of OneBanc, explained that the problem with the bank at the moment is that different systems like credit cards, prepaid cards etc. are not connected. According to him, when banks issue credit cards on fixed deposits (FD), for example, the system is manually programmed to prohibit customers from going over the limit. “These two systems do not talk to each other. It is a manual process to settle the bill from the FD to the credit card, even if there is a default, he said. “Our AI-powered systems allow this fragmented banking system to communicate in real time,” he added.

The map can also connect to a company’s human resources (HR) and financial platforms and make recommendations based on these. For example, it can recognize a recurring payment that a user makes every month and start suggesting that payment at the prescribed time on a monthly basis.

Goyal also said AI helps improve card security. The AI ​​card has no magnetic stripes, but embeds card data on a Europay, Mastercard, Visa (EMV) chip. When transactions are made, the AI ​​records location data and takes into account information such as travel information, job profile, etc. of a user to detect possible fraud.

Similarly, Bengaluru-based Scienaptic AI said in January that payments provider Uni Cards would use its AI algorithms to provide a “refined application process” for its users. “Our credit decision platform enables Uni Cards to experiment, test and learn faster, and over time, build the best decision strategies for their customer segments, balancing growth and profitability,” said Pankaj Kulshreshtha, chief executive of Scienaptic.

According to Mihir Gandhi, Partner, Payments Transformation at PwC, a few large private sector banks in India have already worked on using AI to predict the most suitable payment methods to make a payment.

“Even if you look at non-financial companies, like for example Amazon, that log my payment information. When I make a transaction on Amazon, it suggests a preferred payment option,” Gandhi said.

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