1st National Bank: Bank Stress & Real-Estate Credit Exposure

Bank stress at 1st National Bank (FDIC Cert #6646) registers 81/100 on DLRadar's scale — a severe reading. The score is derived deterministically from the bank's public FDIC call-report financials — asset quality, capital adequacy, earnings and real-estate loan concentration — then weighted by where it actually lends.

Seven-day momentum reads stable. Direction is the tell: climbing stress signals credit pulling back, which shows up in forced sales months later. The 1st National Bank score updates as fresh FDIC call reports post each quarter, so its 81/100 reading and 4-county footprint reflect the current filing cycle rather than a dated snapshot — and because it uses the same model as every FDIC bank, 1st National Bank is directly comparable to any lender in the country. DLRadar does not model 1st National Bank in isolation: the 125-ZIP footprint is cross-referenced against foreclosure filings, tax-lien activity and ownership churn in each of those 4 counties, so a shift in the bank's severe posture can be read directly against on-the-ground distress. The combination of a severe reading and a compact footprint is what makes 1st National Bank worth watching as a supply signal. 1st National Bank runs a compact, single-state real-estate lending footprint — 4 U.S. counties across 1 state, spanning 125 ZIP codes. It concentrates most in Ohio (4 counties). 1st National Bank's score blends four call-report dimensions — capital, credit quality, earnings and property-loan concentration — into one 0–100 number, weighted by lending footprint, which is why it reads as a market signal rather than a generic solvency grade. County by county, that footprint includes Hamilton County, OH, Montgomery County, OH, Warren County, OH, Butler County, OH, among others DLRadar tracks parcel by parcel.

Why a bank's stress matters for acquisitions: local lending capacity drives transactions. When 1st National Bank tightens in a county it footprints, refinances stall, construction lending pulls back, and owners who cannot roll their debt slide toward delinquency, foreclosure and forced sale. It is an early-warning read, flagging distress before it reaches the MLS.

Across the country DLRadar applies the identical model to every FDIC bank, then ties each institution to parcel-level foreclosure, lien and ownership data where it lends. The result is an early, auditable read on supply, every figure anchored to public data.