CATONSVILLE, Md. – Data analytics are proposed as the answer to many challenges in credit unions: now the technology is also being pitched as a means to
addressing consumer dissatisfaction with and government scrutiny of overdraft fees.
New research also indicates analytics can be better used to predict consumers likely to overdraft in the future.
Consumers paid more than $35 billion in overdraft fees in 2017, with credit unions seeing the largest percentage increase.
Now, a new study to be published in the December edition of the INFORMS journal Marketing Science, titled “Analyzing Bank Overdraft Fees with Big Data” and is authored by researchers from New York University and Carnegie Mellon University, offers insights into why consumers act as they do (beyond simply not having funds).
What Study Found
“(The study) found consumers tend to heavily disregard potential future consequences when they spend or withdraw from their checking accounts due to impulsive spending habits,” the authors stated.
But the authors of the study also said they found that due to “high bank monitoring fees,” consumers may not be able to accurately track their balances.
“As a result, consumers may sometimes overdraw their accounts because of impulsive spending or withdrawals habits, and lack of accurate and current information,” the authors stated.
The study is based on data from one large U.S. bank, which included more than 500,000 accounts with a history of up to 450 days. This amounted to 200 million relevant observations, the authors said.
Need for ‘Careful Models’
“Substantively, we found that due to the factors that contribute to the overdraft problem, consumers can become dissatisfied and then leave their banks after incurring what they see as unreasonably high overdraft fees,” the report states. “These findings suggest that we must carefully model consumer demand by taking into account impulsive consumer behaviors, their inattention to balances and how they tend to respond when dissatisfied with overdraft fees. This drives us to arrive at some possible solutions.”
A Clear Case
The researchers said the findings make a clear case for the use of data and predictive analytics to better address the problem, with the study including policy simulations that show alternative pricing strategies can help increase bank revenue while improving consumer welfare. This includes fixed bill schedules and overdraft waiver programs that can be applied to individual consumers that exhibit certain overdrafting behaviors, the study states.
“A potential solution for both consumers and banks is to leverage financial transaction data to manage overdrafting and offer new services that use the financial transaction data,” the authors said. “Financial institutions store massive amounts of information about consumers, which is a by-product of the transactions. In this research, we show how this information can be harnessed to predict consumers’ overdrafting behavior.”