By Sagar Shankaran, Founder of CallSphere
Community bank annual credit reviews move one file at a time. Agent Teams drafts spreads and exception lists in parallel so the analyst reviews instead of digs.
Key takeaways
A $780 million bank in farm country has 117 commercial and agricultural relationships above the $250,000 threshold that the loan policy says get a full annual review. One credit analyst does them. A part-time loan review officer takes the largest twenty. At an honest two and a half hours per file — pull the returns, spread them, run global cash flow, check the covenants, chase the exceptions, write the memo, propose the risk rating — that is roughly 293 hours of work.
An analyst who gets thirty genuinely productive hours a week out of a forty-hour week finishes in just under ten weeks. Which is why annual reviews at most community banks are never actually annual. They are done in a burst before the exam, or they are done in the same January-to-March window when every ag operating line renews and every borrower wants an answer before they buy seed.
The work is not hard. It is serial. One file, then the next file, then the next, by one person, in order.
For one $1.4 million operating line to a fourth-generation grain and cattle operation, the analyst does this: pull two years of Form 1065 partnership returns and the personal 1040s with Schedule F and Schedule E for both partners. Spread them in Abrigo or in the bank's own workbook. Build global cash flow, because the farm, the trucking side business, and the rental ground all touch the same debt. Compute debt service coverage against every note on the borrower, including the equipment paper at John Deere Financial that is not on your core.
Then the exceptions. Is the current-year financial statement in, or is the tickler still open. Is the hazard insurance certificate expired. Is the property in a Special Flood Hazard Area, and if so is the flood policy current — because a lapse there is not a footnote, it is a finding. Is the UCC-1 within five years of filing or does it need a continuation. Is the appraisal old enough that policy requires an update. Are the borrowing base certificates in for the last two quarters.
Every one of those answers lives somewhere already — in LaserPro documents, in the imaging system, in the core, in a PDF the borrower emailed in April. The analyst's real job is to go get them, one at a time, and then form an opinion. Only the last part requires the analyst.
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The change that matters here landed in 2026: Agent Teams, released as a research preview alongside Claude Opus 4.6, plus similar multi-agent setups elsewhere. Instead of one assistant working through a job in order, several work on different parts of the same job at the same time and their results are merged at the end. Paired with models that can take an entire loan file at once — all three tax returns, the note, the security agreement, the last two annual review memos — the practical effect for a bank is throughput on batch work that used to move one file at a time.
The point is not that the machine is smarter than your credit analyst. The point is that twelve files can be in progress simultaneously instead of one, so the analyst's ten-week season becomes a three-week review of work that is already drafted.
flowchart LR
A["Credit analyst releases 117-file annual review batch"] --> B["Agent 1: tax returns spread, global cash flow"]
A --> C["Agent 2: covenant and borrowing base check"]
A --> D["Agent 3: insurance, flood, UCC-1 lapse dates"]
A --> E["Agent 4: appraisal age and collateral file gaps"]
B --> F["Merged draft memo plus exception list per relationship"]
C --> F
D --> F
E --> F
F --> G["Analyst reviews, sets risk rating, signs"]
The analyst releases the batch Wednesday night. Thursday morning there are 117 draft packets in the queue. Each one has the spreads done and tied to the returns, global cash flow computed with the outside debt included, a debt service coverage number with the math shown, and a one-page exception list: "hazard insurance expired 3/14; flood policy current through 11/1; UCC-1 filed 4/2021, continuation due within 6 months; 2025 tax return not received, extension on file; borrowing base certificate missing for Q1."
The analyst does not accept any of it blind. She opens the first packet, checks the spread against the actual return on the second screen, disagrees with how the depreciation add-back was treated on the trucking entity, corrects it, and moves on. Forty-five minutes a file instead of two and a half hours, because the fetching is done and the arguing is what is left.
By the second week the loan assistant is working the exception list rather than the analyst, calling insurance agents for updated certificates and borrowers for the missing returns. That work was always going to happen in April. Now it happens in January, which is the difference between an exception report that shrinks and one that does not.
The savings here are not really dollars. They are weeks in the first quarter. Assumptions stated, substitute your own portfolio counts.
| Line | Before | After |
| Relationships requiring annual review | 117 | 117 |
| Analyst hours per file | 2.5 | 0.75 |
| Total analyst hours | 292.5 | 87.8 |
| Productive hours available per week | 30 | 30 |
| Elapsed weeks of the review season | 9.8 | 2.9 |
| Hours returned to the department | 204.7 | |
| At a fully loaded analyst cost of $46/hour | $9,416 | |
Nine thousand dollars is not why you do this. You do it because 204 hours is roughly what a second credit analyst would have given you at $78,000 a year, and because reviews finished in February instead of May mean risk ratings that reflect the current crop year rather than the last one. When your examiners ask why three relationships slipped from a pass rating to watch, you want the answer to be "we caught it in the annual review," not "we caught it when the line didn't clean up."
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The risk rating is the whole point of the exercise and it is not a calculation. A 1.18 debt service coverage on a dairy with a strong balance sheet, a supportive landlord, and thirty years of history is a different animal from a 1.18 on a startup convenience store with a leased location. Your chief credit officer knows that. The machine does not, and if you let a draft rating flow through unchallenged you have automated your way into a bad loan portfolio.
Three more limits worth writing into the procedure. First, handwritten and scanned documents still cause errors — a faxed insurance certificate with a handwritten policy number will occasionally be read wrong, so exceptions get verified against the source before anyone calls the borrower. Second, anything that leads to a declined renewal or a rate change on a consumer-purpose loan pulls in adverse action notice requirements, and a human writes that notice. Third, do not put borrower tax returns into a general consumer chat product. This belongs in a business account with a written agreement about how your customer information is handled, and your board's vendor management policy applies to it exactly like any other core-adjacent service.
Examiners care that the review happened, that it was independent of the lender who made the loan, and that a qualified person reached the conclusion and signed it. Drafting assistance does not change any of those. What would change them is letting the assistant assign the final risk rating without a human — do not do that, and document that you do not.
Scanned files are the normal case at a community bank and current models read them well, including multi-page returns and stamped documents. The failure mode is not the printed page; it is handwriting in the margin and low-quality faxes. Expect to verify a percentage of what it pulls and build that into the 45-minute review estimate.
Same idea, different batch. New-request underwriting has more back-and-forth with the borrower and more judgment early, so most banks start with annual reviews and the document exception report, where the work is defined, repetitive, and behind schedule anyway.
Less than one day of the analyst's time. Model costs fell roughly tenfold from 2025, which is the reason this is a community bank conversation in 2026 and was a regional bank conversation in 2024.
One side effect worth planning for: an exception list that finally gets worked means a lot of outbound and inbound phone calls to borrowers, insurance agents and accountants during the busiest quarter of your year. CallSphere builds AI voice and chat agents that answer phone lines and web chat, book appointments, and capture what the caller needs — useful for catching the agent who calls back about a certificate at 4:50 p.m. on a Friday when the loan assistant has gone home. It does not underwrite loans and it does not rate credits.
Written by
Sagar Shankaran· Founder, CallSphere
LinkedInSagar Shankaran is the founder of CallSphere, where he builds production AI voice and chat agents deployed across healthcare, hospitality, real estate, and home services. He writes about agentic AI, LLM engineering, and shipping voice agents that handle real calls in production.
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