Improving financial health: a win-win situation for banks and their customers
By Uday Akkaraju, CEO of BOND.AI
Today, 66% of Americans in the United States have financial health problems and 14% are considered downright vulnerable – in other words, the majority of people living in the United States cannot plan their lives in full. financial freedom.
At the same time, financial institutions collect their customers’ transaction data, make loans and set interest rates – holding the assets for people’s financial health: their economic data.
Here’s why and how banks should use customer data, tailor their offerings to customers’ financial needs, and in turn generate higher revenue.
The challenges of financial health
The most pressing issues for people struggling financially are payday loans and their high interest rates. On average, payday lenders charge $520 in fees to borrow $375. Having to opt for non-traditional means of financial support, they ironically have to pay more than others when they borrow money, while their financial room for maneuver is less. By paying attention to just a handful of metrics, banks are excluding millions of low-income and middle-class customers from improving their financial health – and the cycle continues.
Standardized products also prevent consumers from improving their financial health. Financial institutions offer a range of standard products and loans and use basic data analytics to set interest rates or deposit payments. And even retailers that offer more diverse credit options to consumers, like Buy Now Pay Later (BNPL), are now having significant problems with their credit programs because most users are in debt and unaware of their financial situation.
But what if the solution could lie in the collection of financial data and its more relevant analysis?
How consumer data can help improve financial well-being
To overcome the precarious financial situation of modern Americans, banks must stop looking at past credits, years of financial history, or debt-to-credit ratios to combat skewed credit scores and interest rates. Behavioral data, such as spending habits and economic patterns, will provide a more accurate picture of people’s ability to repay their loans or use their credit cards responsibly. Low income does not necessarily represent a consumer’s ability to pay bills on time – it requires deeper knowledge to adjust to a fair credit score.
Artificial intelligence (AI) data analysis can categorize customer profiles based on their behavior and financial capabilities. By continuously updating these customer profiles, the algorithm will understand patterns and deviations and give recommendations to consumers as well as banks. Suppose a customer’s account shows diaper purchases and high credit card spending – they may have a new family member. To support them, their bank may offer a higher credit card limit or extend the repayment term. Personalized products appeal to customers.
But even the smartest analytics couldn’t paint a full picture of a consumer’s financial and health needs — after all, a consumer’s personal preferences don’t necessarily show up in transactional data. Technologies such as conversational chatbots take the pulse and provide deeper insights into financial aptitude. Advanced conversational AI can communicate with customers and ask questions like, “Tomorrow you get $2,000. You can spend it on a language course, a new TV, or a new pair of eyeglasses. do you choose?”
Why customer-centric thinking is the only solution
In the financial world, customer retention, acquisition and satisfaction are not only linked to quick and easy transactions, but to the experience of optimizing one’s financial situation. Banks with a customer-centric business model will create solid long-term value by building customer engagement and trust. The science is simple: a bank that reminds people of their debts every day leaves them with a bad conscience and negative feelings. A bank that actively helps find the best financial tool to meet economic challenges and is sensitive to individual obstacles is a bank that a customer is unlikely to trade for a competitor.
Today’s challenges require modern technologies and an openness to disruptive thinking. Financial institutions that overcome outdated methods of data collection and analysis and focus their business model on the customer will attract a much larger audience and improve the economic situation of their customers. By doing so, banks will also improve their bottom line – and improving financial health will become a win-win situation for everyone.
This article was submitted by an external contributor and may not represent the views and opinions of Benzinga.
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