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Predicting Low Balances Will Stop Overdraft Fees, This Startup Says

By Joseph Walent
May 4, 2017
in Analysts Coverage
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Leverage of big data and machine learning are generating advances in the field of predictive analytics, which, as the article points out, creates a new model for personal financial management solutions. The featured program’s leverage of predictive tools stands out as having the capability of anticipating situations where a household budget may be deficient and effectually provides a short-term interest free bridge loan, and thereby helping a FI customer a way to avoid overdraft fees and other “penalty” expenses.

Although it’s hard to quantify the revenue all banks make on overdraft fees, the Consumer Financial Protection Bureau estimates banks with $1 billion or more in assets totaled $11.42 billion on overdraft and nonsufficient-funds fees in 2016 (the second year banks with $1 billion or more had to make the data publicly available). The agency estimates that consumer overdraft and NSF fee revenues total as much as $17 billion annually.

Mercator Advisory Group anticipates the viable market for such budget protection services will become increasingly vibrant in the coming years as more financial institutions shift from transactional to a fiduciary and advisory focus. The integration of a kind of insurance against a fee into the portfolio of available outside services will be more commonplace. While the fee will exist as a reminder to live within one’s means, the safeguarding against a gap penalty free when needed will also engender a trust and rapport between FI and customer, while the warning of potential timeframe where the gap is likely to occur provides the customer with advance knowledge and the opportunity to adjust spending. Maintaining a dialogue of timely and relevant advice and suggestions will be one way FIs stay relevant to their consumers in the coming financial evolutions.

Overview by Joseph Walent, Associate Director, Customer Interactions Advisory Service at Mercator Advisory Group

Read the full story here

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