IN TODAY’S world, credit is a unique or ‘special’ form of money that is not fully convertible or exchangeable with other forms of currency. People agree that credit is both a resource that allows current needs to be met, but it is simultaneously a liability that requires future repayment, normally with interest. Credit, in this sense, is unique because to some it can be risky as well. Also, in a time of stagnant incomes and expanded access to credit, as is the case today, unsecured debt has become a focal money concern and a stress for many. Credit cards are obtainable to a customer provided s/he has responsibly maintained healthy transactions and has established a profile of timely repayment of loans in the past, failing which the consequences can be severe. Credit scores, a measure of a cardholder’s capacity to repay, determine his/her strength to remain a cardholder.
This short note is intended to apprise the readers in Bangladesh to familiarise themselves with the rapid changes occurring in the credit card industry vis-Ã -vis the implications or consequences on the borrowers or card holders.
Recently, in the western world, a new product in this business has emerged, in that customers can boost their credit scores without ever borrowing or even paying back any money. In the USA, millions have already opened these so-called ‘credit builder’ cards since the first ones came onto the market around the start of the pandemic. Just like with debit cards, customers deposit money into these accounts to pay bills or make purchases, much like with a debit card. This is where the twist is: Fintech (Financial Technologies Institutions overseeing the business) report some of these transactions to the credit reporting companies as credit activity, or borrowing, even though no credit is ever extended to the customer. This new device seeks to smooth out the long-standing built-in-flaws in the credit scoring system. Under normal circumstances, the only path to building a credit score is to borrow money. In other words, people need to take out loans to establish credit scores, but they need credit scores to be approved for loans. Apparently, a contradiction, in and of itself.
Credit-builder’s cards, on the other hand, often do not require credit checks at all, much less a credit score. These cards are designed to mainly report positive data. For example, the cards offered by some companies make it difficult for customers to become delinquent. The credit-reporting companies, such as Experian, Equifax and TransUnion, gather data on individual citizens (now in the US) and turn that into credit reports. Those data points are then fed into algorithmic models, which are designed to predict the likelihood that a borrower will become delinquent on a loan. In this system, the lenders pay for credit data and credit scores, to decide who can get a loan and at what interest rate. Also, the employers might consider these data when deciding whom to employ. Landlords might consider this information when deciding who gets to rent the apartment.
However, this system is now under scrutiny. Regulators consider this system as one that locks out people who have limited credit histories. Consumer advocates are of the view that the scores are unfairly opaque, making it hard for people to even guess why their score might go up or down. Then the banks have their issues too. Banks, for their part, are becoming more sceptical of the usefulness of traditional credit scores. Recently, in fact, banks have started to incorporate more of their own internal data and models into credit decisions. New sources of data include, for example, social media activity, utility bills, rental payments, and the like. Therefore, the trend is evolving for lending institutions to integrate new sources of data for credit worthiness, which is driven by digitalisation.
There is an expectation that both lenders and borrowers stand to benefit from a clearer process of consumer credit risk. Already, the use of artificial intelligence has come to play a role in driving better and more transparent credit decisions. The plummeting cost of computing and the rise in data availability have encouraged the adoption of highly predictive AI and machine learning techniques in credit scoring. However, use of AI raises the question of accountability, thereby making it murky. The ability to explain how AI systems assess data and form decisions affecting the human mind is critical to overcoming this challenge.
In developing nations, it is imperative the banks, financial institutions, and other lending bodies are vigilant about integrating new credit scoring systems to protect their own businesses and that of the borrowers. Both sides must recognise that it is now possible for financial institutions to more easily explain their lending decisions to customers and approve more consumers for credit without taking on additional risks. It is also easier for consumers to capitalise on credit opportunities and forge a path to improved financial health. In developing countries, there is a serious lack of fully grasping the nature of credit card borrowing and its consequences on life. A need has emerged to introduce in our formal education these issues to prepare our young citizens to better handle their financial management matters. Our education planners may proactively take it upon as a professional duty. Clearly, the credit card industry is going through a sprint. In this age and technological innovations, the credit scoring art and science has become a marathon in the end.
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Humayun Kabir is a former senior official of the United Nations in New York.