Arthur State Bank
Arthur State Bank runs a respectable digital-banking stack for existing customers (Jack Henry’s Banno) but offers almost no self-serve front door for new lending. Only mortgages have an online application, and it lives on a separate, dated third-party domain. Every other product (auto, personal, RV, watercraft, and all business lending) ends at “contact a loan officer.” The infrastructure to do better is already in place; what’s missing is a single, branded, verify-as-you-go intake.
The borrower journey today
How a prospective borrower actually moves through Arthur State’s digital properties right now, line by line.
What we’d change
One digital front door for lending, and it’s the hardest product
Mortgage is the only line a borrower can start online. The faster, higher-volume consumer products (auto, personal, HELOC) and all business lending have no apply button. Demand that arrives at 9pm on a phone has nowhere to go but a “call us” message, which is exactly where abandonment happens.
The mortgage POS breaks brand continuity
The “Apply Now” button hands the borrower to mortgagewebcenter.com, a legacy Finastra Mortgagebot portal on a different domain with a different look. At the single most important conversion moment, the customer leaves Arthur State’s brand for a generic vendor screen.
You already own the platform to fix this
Arthur State is on Jack Henry for digital banking. A white-label intake that syncs applications straight into the Jack Henry core is an incremental addition to a stack you already run, not a rip-and-replace. The gap is intake and verification, not infrastructure.
No verification layer means manual document chase
Because intake is a phone call or a lead form, identity, income, employment, and property all get collected the slow way afterward: document requests, VOE calls, and follow-ups. That’s staff time per file and days of delay before a borrower hears anything back.
What it could look like
Below is a live, interactive white-label demo in Arthur State’s own branding: one front door, every product, with identity, income, and property verified automatically. Try it, or open it full-screen.
Today vs. with RAVEN
| Today | With RAVEN white-label | |
|---|---|---|
| Products you can start online | Mortgage only (1 of 6) | Every product, one front door |
| Brand experience | Hands off to a third-party domain | Arthur State branding end to end |
| Borrower effort | Long forms + document uploads | Name, email, and a secure connect |
| Identity / income / property | Collected manually after the fact | Verified automatically in ~90 seconds |
| Rate visibility | None until an officer follows up | Optional instant estimate from your rate card |
| Into the core system | Re-keyed by staff | Synced to Jack Henry automatically |
| After-hours demand | “Contact a loan officer” | Captured, verified, and queued |
What your loan officer receives
The instant a borrower finishes that flow, a fully verified application lands in the RAVEN dashboard and syncs to Jack Henry. No rekeying, no document chase, full audit trail.
Jordan Carter
What automated verification is worth at Arthur State
Eighteen branches across five CRA assessment areas means five loan-officer pools, each verifying borrowers with whatever workflow accumulated locally. One verification stack changes the math on every file, in every market, at once. All figures below are estimates built from public data (FDIC, HMDA, CRA filings). See the methodology.
Where the time goes today
Roughly 458 files a year need borrower verification at Arthur State: 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
| Line | Conservative | Expected | Optimistic |
|---|---|---|---|
| Staff time savings[1][2] | $101K | $180K | $284K |
| Pull-through revenue (2-10 added closings)[4] | $2K | $5K | $8K |
| Total estimated annual value | $102K | $184K | $292K |
The growth side: new residents, captured digitally
Roughly 1,500 new households move into Arthur State'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 above) turns that migration into a lead channel the bank owns instead of renting.[6]
| Annual | Conservative | Expected | Optimistic |
|---|---|---|---|
| Digital leads captured | 23 | 60 | 135 |
| Funded loans from those leads | 3 | 18 | 68 |
| Value (loan profit + avoided lead spend) | $4K | $32K | $155K |
This is new revenue, not savings, so it is shown separately and excluded from the headline number above.
Beyond the dollar math
Five assessment areas, one audit trail
Each branch today verifies with its own accumulated workflow. A single 5-minute borrower flow with an examiner-ready audit trail simplifies the next CRA exam across all five assessment areas at once.
Mortgage is half the loan book
With ~50% of the portfolio in 1-4 family residential and 208 conventional originations in 2024, mortgage is the engine, and it is the product fintechs have automated most aggressively.
ROA protected by capacity, not headcount
A 1.17% ROA, top half of SC community banks, does not survive adding underwriting headcount to chase growth. Recovered verification labor is origination capacity that does not show up on the expense line.
Want this with Arthur State’s real products and rates?
We’ll wire your actual product lineup, your rate card, and a Jack Henry sync into a private demo, then pressure-test every number above against your real volumes.
We also published an independent analysis of Arthur State's performance and market:
Read: The Bank That Depression BuiltMethodology & footnotes
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.
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.
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.
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.
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.
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.
Digital audit sources: arthurstatebank.com (/loans, /mortgage, /faq), my.arthurstatebank.com (Banno), FDIC BankFind cert #15085. Brand color #006242 and tagline extracted from the bank’s site. Reviewed June 2026.
ROI data sources: FDIC BankFind (Cert #15085); Arthur State Bank CRA Public File (rev. March 2024); 2024 HMDA Modified LAR via FFIEC; MBA Quarterly Mortgage Bankers Performance Report (2025); BLS OEWS (2025).