--- title: "How Rising Interest Rates Affect Bank Net Interest Margins" description: "A practitioner's guide to how rising interest rates reshape bank net interest margins." canonical_url: https://www.bankregreports.com/blog/rising-rates-bank-net-interest-margins/ source: BankRegReports published: "2026-10-14" updated: "2026-10-14" --- If you have sat in an ALCO meeting during a rate-hiking cycle, you already know the dynamic is messier than the textbook suggests. The standard story (rates go up, bank margins expand) is true enough in the first few quarters. Then deposit repricing catches up, and the margin story gets complicated fast. Understanding exactly how and when that compression happens requires clean, granular data. That is what this post is about: the mechanics of the rate-margin relationship, and how to pull the data you need to analyze it yourself using the [BankRegReports](https://www.bankregreports.com) platform.
Distribution of net interest margins across U.S. banks
Net interest margins across the U.S. banking industry.
## The Basic Mechanics of NIM and Rate Sensitivity Net interest margin is net interest income divided by average earning assets, a simple ratio that hides an enormous amount of structural complexity. A bank's sensitivity to rate changes depends on the mix and repricing tenor of its assets and liabilities, gaps that ALCO teams spend considerable effort measuring and hedging. When the Federal Reserve raises the federal funds rate, the transmission to bank margins works through several channels simultaneously: **Asset repricing.** Variable-rate loans (commercial lines, adjustable-rate mortgages, most commercial real estate construction facilities) reprice upward almost immediately. Fixed-rate portfolios (term loans, agency MBS, long-duration investment securities) do not reprice until they mature or prepay. A bank with a short-duration asset book benefits quickly; a bank that extended duration into long treasuries to pick up yield in 2020-2021 is underwater on those bonds and earns the old coupon until maturity. **Liability repricing.** This is where the lag lives. Core deposits (checking accounts, savings accounts) are famously "sticky" in the early innings of a tightening cycle. Depositors do not immediately demand higher rates. That lag is the source of the margin expansion that shows up in the first four to six quarters after lift-off. Eventually, though, deposit betas move. Customers notice their money-market fund is yielding 5% and their savings account is yielding 0.4%. Deposit migration accelerates, and the cost-of-funds curve steepens sharply. **Balance sheet mix.** Banks that funded themselves heavily with brokered deposits or wholesale funding have no beta lag; those liabilities reprice at or near the federal funds rate immediately. Community banks with deep core deposit franchises have a genuine structural advantage in a rising-rate environment, at least early in the cycle. ### Deposit Beta: The Variable That Determines Everything Deposit beta (the fraction of a rate change that passes through to deposit costs) is the single most important variable in forecasting what a rising rate environment does to a specific institution's NIM. A bank with a 20% cumulative deposit beta will pass through 20 cents of every dollar of Fed tightening to depositors. A bank funding itself with brokered CDs might have a beta close to 100%. The tricky part is that deposit beta is not constant. It tends to be low in the first 100-200 basis points of a cycle, then accelerates as the cycle matures and alternative investments become undeniable to retail customers. This non-linearity is why simple asset-sensitivity disclosures in 10-Ks frequently underestimate the eventual margin compression. ## What Does the FFIEC Call Report Data Actually Show? The FFIEC Call Report (FFIEC 031/041/051) is the most complete public source for bank-level income statement and balance sheet data, filed quarterly by every FDIC-insured institution. The official source is the [FFIEC](https://www.ffiec.gov). Schedule RI contains interest income and interest expense broken down by asset and liability category. Schedule RC-K gives average balance data needed to compute yields and costs properly. The UBPR (the Uniform Bank Performance Report) goes a step further, publishing pre-computed ratios including NIM, cost of funds, and yield on earning assets for every filer going back decades. These are derived directly from Call Report filings, so they are regulatory-grade numbers, not analyst estimates. The challenge has always been accessing and normalizing this data. The raw FFIEC files are tab-delimited flat files with MDRM codes as column headers. Parsing them, handling restatements, joining across quarters, and mapping codes to human-readable labels is non-trivial work. Enterprise data platforms charge significantly for cleaned versions of this data. BankRegReports makes the same underlying FFIEC, FDIC, Federal Reserve NIC, Y-9C, NCUA 5300, and SEC EDGAR data available through a clean API at a fraction of the cost. ## The 2022–2024 Tightening Cycle: A Case Study in Lag The Fed's 525-basis-point tightening cycle from March 2022 through July 2023 is the best natural experiment in deposit repricing dynamics in a generation. What the Call Report data shows when you look at it closely: **Quarters 1-4 (2022 Q1–Q4):** NIM expanded meaningfully for most asset-sensitive institutions. Variable-rate assets repriced. Deposit costs moved modestly. The benefit flowed almost entirely to the asset side. **Quarters 5-8 (2023 Q1–Q4):** Deposit betas accelerated. Money-market competition intensified. Banks that had been booking the margin expansion began to see costs rise faster than asset yields. Institutions with longer fixed-rate asset portfolios (particularly those that had extended duration in 2020-2021) saw margin compression even as rates stayed elevated, because their asset yields were locked in at lower coupons while their funding costs rose. **The securities portfolio overhang.** Several institutions booked large unrealized losses on held-to-maturity and available-for-sale portfolios. While these do not directly flow through NIM (they are mark-to-market through OCI for AFS, not through income), they constrain strategic flexibility and, in extreme cases, contributed to the bank failures we saw in early 2023. The FFIEC data captures all of this with quarterly granularity at the institution level. You can identify which institutions had the most favorable asset repricing, which had the stickiest deposit bases, and which are still carrying the legacy yield drag from pre-2022 fixed-rate commitments. ## Why Clean Regulatory Data Matters for This Analysis The difference between doing this analysis well and doing it badly comes down to data quality. MDRM codes change over time. Items migrate between schedules across filing cycles. Institutions restate prior quarters. The FFIEC publishes these changes, but tracking them across 4,000+ active filers over 20+ years is the kind of work that takes real infrastructure to do correctly. [BankRegReports](https://www.bankregreports.com) handles the normalization layer (MDRM code mapping, restatement tracking, period alignment, and unit standardization) so you can work at the analysis level rather than the data-janitor level. The same pipeline that produces the UBPR ratios in the API also ingests the raw Call Report schedules, Federal Reserve NIC entity data, FDIC institution profiles, NCUA 5300 credit union filings, and SEC EDGAR disclosures. Everything is queryable through a single consistent API. ## Getting Started Rate sensitivity analysis, deposit beta estimation, NIM decomposition by asset class: these are the core tools of bank ALM work, and the data to do them right is now accessible without an enterprise contract. Whether you are building an ALCO dashboard, running a peer benchmarking study, or modeling deposit beta for a specific institution, BankRegReports gives you the underlying regulatory data, clean, normalized, and ready to use. ## About this document This is the markdown twin of the page named in `canonical_url` above. Source filings are public record; the cleaning, normalization, cross-source linkage, and derived metrics are BankRegReports' own. Attribute with a link to the canonical URL. Markdown twins are published for editorial content only. Institution data pages do not have them. For data at scale use the API, which is documented at https://www.bankregreports.com/api/ and specified at https://www.bankregreports.com/openapi.json. It returns typed JSON with explicit units and periods, and one call replaces hundreds of page fetches. ## Sitemap - [Glossary](https://www.bankregreports.com/glossary/): every metric, with formula and thresholds - [Blog](https://www.bankregreports.com/blog/): analysis and explainers - [API documentation](https://www.bankregreports.com/api/): the programmatic way to get this data - [XML sitemap](https://www.bankregreports.com/sitemap.xml): the complete crawlable index