Overdraft & NSF Event Data
Buy and sell overdraft & nsf event data data. Insufficient fund events, overdraft patterns, recovery timing — neobank AI needs real overdraft behavior data.
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Find Me This Data →Overview
What Is Overdraft & NSF Event Data?
Overdraft and non-sufficient funds (NSF) event data captures the behavioral patterns, timing, and financial impact of insufficient fund events across consumer checking accounts. This dataset includes overdraft fee amounts, frequency of events, recovery timing, and demographic breakdowns of consumers experiencing these events. Neobanks, fintech lenders, and risk management platforms use this data to model consumer cash flow volatility, predict likelihood of overdraft events, and design products that reduce financial friction for underbanked populations. The market represents a significant cost burden on consumers—in 2023, consumers paid approximately $7.7 billion in overdraft and NSF fees, with heavy concentration among a small subset of account holders.
Market Data
$12.1 billion
Total overdraft & NSF fees paid in 2024
Source: ElectroIQ
~26.5% of consumers incurred at least one fee
Consumers paying overdraft/NSF fees in 2024
Source: JDSupra analysis
9% of users accounted for nearly 80% of total fee income
Concentration of fee burden
Source: ElectroIQ
$26.77
Average overdraft fee
Source: Bankrate
$16.82
Average NSF fee
Source: Bankrate
Who Uses This Data
What AI models do with it.do with it.
Neobanks and fintech
Develop cash flow modeling and overdraft prevention features; design transparent fee structures that undercut traditional banks; predict and prevent insufficient fund events before they occur.
Credit risk and lending platforms
Model consumer financial volatility and creditworthiness; segment borrowers by overdraft event frequency and recovery patterns; price loans and credit products based on observed cash flow behavior.
Consumer finance regulators
Monitor overdraft fee impact across institutions; measure compliance with CFPB overdraft pricing rules; identify concentration risk among heavy reliant financial institutions.
Banks and credit unions
Benchmark overdraft fee income against peers; understand revenue concentration and customer segmentation; design overdraft programs that balance profitability with consumer financial health.
What Can You Earn?
What it's worth.worth.
Consumer-level event data
Varies
Pricing depends on event granularity (transaction-level vs. aggregate), historical depth, and geographic/demographic segmentation.
Institutional fee revenue data
Varies
Aggregated overdraft and NSF fee revenue by bank or credit union size; market intelligence for competitive analysis.
Predictive behavioral models
Varies
Pre-built datasets linking overdraft events to recovery timing, income level, and subsequent account closure; ready for ML training.
What Buyers Expect
What makes it valuable.valuable.
Event-level detail
Transaction date, overdraft amount, fee charged, days to recovery, account closure indicator, and triggering transaction type.
Temporal consistency
Multi-quarter or multi-year observation windows to capture seasonal patterns, repeated overdraft behavior, and long-term recovery trends.
Demographic segmentation
Income bracket, age, geography, and account tenure linked to overdraft event frequency and severity; essential for bias detection and fair lending compliance.
Institutional context
Bank or credit union identifier, asset size category, and fee structure to enable comparative analysis and regulatory benchmarking.
Companies Active Here
Who's buying.buying.
Build overdraft-prevention features and cash flow forecasting tools; attract underbanked segments by offering fee-free overdraft coverage.
Model credit risk and set pricing based on overdraft event history; underwrite small-dollar loans to consumers with volatile cash flow.
Monitor competitive overdraft fee benchmarks; optimize fee income in light of CFPB pricing restrictions; understand customer concentration risk.
Track overdraft fee revenue trends and peer performance; assess reliance on overdraft income relative to other revenue streams.
FAQ
Common questions.questions.
What is the difference between overdraft and NSF fees?
Overdraft fees are charged when a bank covers a transaction despite insufficient funds; NSF (non-sufficient funds) fees are charged when a transaction is declined. Banks typically charge $26.77 for overdraft and $16.82 for NSF. About 90% of banks still charge overdraft fees on checking accounts, while NSF fees are becoming less common, with 39% of checking accounts no longer charging them.
Who pays the most overdraft and NSF fees?
Heavy overdrafters represent a highly concentrated cohort: approximately 9% of users account for nearly 80% of total overdraft and NSF fee income. About 34% of households earning less than $65,000 incurred overdraft or NSF fees, and consumers with frequent overdrafts have credit scores averaging 100 points lower than those with no overdrafts (637 vs. 744).
Why do neobanks and fintech companies need overdraft event data?
Neobanks use overdraft event data to build predictive models of cash flow volatility, develop overdraft-prevention features, and design fairer fee structures that undercut traditional banks. Fintech lenders use the data to assess credit risk and price loans based on observed financial behavior rather than credit scores alone.
Has the overdraft fee market changed due to regulation?
Yes. The CFPB issued an overdraft rule in December 2024 requiring large financial institutions to lower overdraft fees or follow stricter guidelines. Overdraft and NSF fee revenue declined 23% between 2022 and 2023. New regulations on NSF fees are expected to save consumers up to $5 billion annually, though overdraft fees remain common and largely unaffected by the current regulatory cap.
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