Verification ROI Audit · June 2026

First Reliance Bancshares

First Reliance built a 9-branch statewide footprint from a Florence base, with heavy CRE exposure in some of the fastest-growing SC markets. Loan growth running at 10.9% annualized means more files, more complex commercial borrower profiles, and more pressure on the verification layer that sits between application and close.

All figures are estimates built from public data (FDIC, HMDA, CRA filings). Read the full methodology

$1.12B
Total assets
1.25%
ROA
3.77%
NIM
10.9%
Loan growth (Q1 annualized)
$0K
estimated annual value of automated verification at First Reliance (expected case)
$126KConservative
$226KExpected
$355KOptimistic

Where the time goes today

Roughly 530 files a year need borrower verification at First Reliance: identity, income, employment, assets, and property, collected today through document requests and follow-up calls.[3]

That is 0 staff hours a year in the expected case, recovered as origination capacity rather than headcount reduction.[1]

Value by lending line

Different files carry different verification loads. Commercial files (beneficial ownership, guarantors, business financials) take the longest; consumer files the least. Expected-case annual labor value:[1][2]

The full math

LineConservativeExpectedOptimistic
Staff time savings[1][2]$124K$219K$345K
Pull-through revenue (3-13 added closings)[4]$2K$6K$10K
Total estimated annual value$126K$226K$355K

The growth side: new residents, captured digitally

Roughly 3,000 new households move into First Reliance's footprint every year, and about 30% of movers open an account with a new bank. They shop with their phones. A white-label, fintech-grade intake flow (the same 5-minute experience RAVEN runs for verification) turns that migration into a lead channel the bank owns instead of renting.[6]

AnnualConservativeExpectedOptimistic
Digital leads captured45120270
Funded loans from those leads536135
Value (loan profit + avoided lead spend)$6K$64K$308K

This is new revenue, not savings, so it is shown separately and excluded from the headline number above. The younger and newly arrived households a digital flow captures are exactly the relationships a branch network alone does not reach.

See these numbers against your actual workflow

A 20-minute call with a live verification using test data. You'll see the borrower flow and the loan-officer dashboard end to end, and we'll pressure-test every assumption above with your real volumes.

Beyond the dollar math

Nine branches, eight cities, one verification standard

Each market carries different employer types: government in Columbia, healthcare and tech in Greenville, hospitality in Myrtle Beach, manufacturing in Florence. A single borrower verification stack replaces eight locally-accumulated workflows with one audit trail and one borrower experience, regardless of which branch originates the file.

CRE at 59% means the heaviest files dominate the pipeline

Commercial real estate verification carries the highest hours-per-file load in banking: beneficial ownership, guarantor identity, business financials, and entity structure. At 59% of an $801M book growing at 10.9% annualized, that is roughly $87M in new CRE originations per year running through the same manual collection process.

Deposit pressure makes efficiency the whole game

Deposits fell 8.1% annualized in Q1 while loans grew 10.9%. Every basis point of NIM compression from funding costs has to be offset somewhere. Recovering verification labor on the CRE and mortgage pipeline is capacity that does not show up on the expense line and does not require paying up for deposits.

We also published an independent analysis of First Reliance's performance and market:

Read: The Bank That Didn't Wait for the Battery Plant

Methodology & footnotes

1

Hours saved per file. Published verification-automation case studies (Blend Labs, 2025) report 15-16+ staff hours saved per mortgage file across loan officers, processors, underwriters, and compliance. We model mortgages at 6-14 hours, commercial files (which add beneficial ownership, guarantor identity, and business financials) at 8-16 hours, and simpler consumer or HELOC files at 2-6 hours. The expected case sits well below published benchmarks on purpose.

2

Loaded staff cost. The $38-48/hour range blends Bureau of Labor Statistics OEWS rates for South Carolina loan officers (~$30/hr), processors (~$28/hr), underwriters (~$55/hr), and compliance staff (~$50/hr), including benefits. Most verification labor falls on processors and loan officers, which is why the blend sits closer to the lower rates.

3

Verification volume. Mortgage counts come from HMDA Modified LAR filings via FFIEC, which report actual originations. Commercial, HELOC, and consumer volumes are estimates derived from FDIC call report loan mix and branch footprint; they are not reported figures and could vary materially. The 60-day pilot exists to replace these estimates with the bank’s own measured numbers.

4

Pull-through improvement. The MBA reports roughly 68% industry-wide mortgage application abandonment. We model a 1-5 percentage-point improvement applied to originations (not the larger application pool, which would produce a roughly 3x bigger figure), at the MBA-reported $785 average profit per closed loan. Published case studies report 10-15 point gains; our optimistic case is one-half to one-third of that.

5

What this is not. These figures are directional estimates built from public data and industry benchmarks. They are not a quote, a guarantee, or an analysis of the bank’s internal workflows, and recovered hours are modeled as redeployed origination capacity rather than headcount reduction. Banks already running highly automated verification will see less; banks running fully manual document collection will see more.

6

New-resident lead generation. TD Bank research reports roughly 30% of consumers open an account with a new bank after moving (and movers 55+ switch at a higher rate than millennials), while 91% of consumers say digital capability matters in choosing where to bank (MX, 2025) and more than half of online banking applications are abandoned mid-flow (The Financial Brand; Innovatrics). We model a bank with a white-label, fintech-grade intake flow capturing 1.5-9% of new-to-market households as started applications, converting 12-50% of those to funded loans (expected case: ~55% completion times the MBA-reported ~55% depository pull-through). Value per funded loan combines the $785 MBA average profit with $500-1,500 of avoided lead-acquisition spend, the going rate per funded loan from purchased shared and exclusive lead channels. New-household counts are derived from Census county population estimates and are not bank-reported figures. This line is shown separately and is not included in the headline savings number.

Data sources: FDIC BankFind (Cert #76181); First Reliance Bancshares Q1 2026 earnings release; Visbanking call report data; Florence County Economic Development (AESC project status); Zillow Florence SC market data; MBA Quarterly Mortgage Bankers Performance Report (2025); BLS OEWS (2025).