For Data Scientists & ML Engineers · Regional Banks
Regional Banks Data for Data Scientists
Regional Banks data for data scientists: 5 datasets on one shelf. Every one delivered as API, files, or warehouse rows.
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API, files, or your warehouse. Daily, weekly, or hourly.
Why regional banks rewards data-science workflows
Quality averages 8.2 out of 10 against the 7.81 catalog-wide mean, though only 3 of 5 (60%) score 8 or higher, a hair under the catalog's 62.8%. Cadence skews fast for a supervisory slice: 2 of 5.6% catalog-wide, and 4 of 5 refresh at least weekly against 27.8%.
Which financial time series can you backtest on?
Two series families carry the backtest load. Federal Reserve H.8 - Assets and Liabilities of Commercial Banks publishes weekly aggregate loans, securities and deposits split by bank-size bucket as bulk CSV (via the Fed's DDP/FRED channels) alongside XML and RSS, handing lending-cycle models decades of history in one download.
How do you build a failure-prediction label set?
Supervised work on bank distress starts from one small file. The FDIC Failed Bank List publishes every failure since 2000 as a CSV - also reachable as JSON through the BankFind API - and its intended role is a label column: join failures onto a bank-quarter panel built from BankFind's quarterly financials and train default-risk classifiers. Because the list updates statically rather than on a feed, treat it as a slowly changing dimension you re-pull after each supervisory action rather than something you stream.
What do data scientists ask about regional banks data?
These five questions cover what modelers actually ask about the pairing; each answer is grounded in the 5 qualifying records above.
Straight answers
Which financial time series API works for backtesting regional bank models?
Pair it with Federal Reserve H.8, whose weekly aggregates by bank-size bucket arrive as bulk CSV through DDP/FRED with XML and RSS alternatives, for decades of aggregate history.
Where do you get training data for bank-failure prediction models?
Build the target from the FDIC Failed Bank List - its CSV of every failure since 2000 is meant to be joined onto other bank panels as a label column for default-risk classifiers. Generate features from BankFind Suite's quarterly financials and branch locations, then enrich with OCC enforcement events as leading indicators of distress.
Rows before rollout
Sample rows from any shelf entry — the field dictionary and coverage notes ride along. If the shelf misses what you need, say so; sourcing requests are half our job.
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