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Aloan
All industries

For credit unions

AI commercial underwriting for credit unions and member business lending

Grow MBL volume without hiring three more commercial underwriters. Aloan automates spreading, global cash flow, and credit memo generation for credit unions running member business lending under NCUA Part 723.

NCUA Part 723 alignedMember Business Lending workflowsSits on Symitar, Corelation, FIS, FiservStandardized memos for board credit committee

Why credit union commercial lending is different

Credit union commercial sits inside its own regulatory and capacity envelope

Credit union member business lending operates under a tighter regulatory perimeter than community bank commercial lending. The 12.25% MBL aggregate cap (NCUA Rules and Regulations Part 723) creates quality-not-quantity pressure; the relationship-and-mission framing of member business lending shapes the credit thesis; and most credit union commercial teams are smaller than their community bank counterparts. AI underwriting has to respect those constraints — not assume the credit union is just a small bank.

MBL cap

NCUA Part 723 caps aggregate Member Business Loan exposure at 12.25% of assets for federally insured credit unions, with exemptions for low-income designated credit unions and CUSOs. The cap focuses underwriting attention on credit quality per dollar of MBL deployed.

Regulator

NCUA for federally chartered and federally insured credit unions; state regulators for state-chartered credit unions. Exam emphasis on MBL credit administration is intense — Part 723 documentation expectations shape every commercial credit file.

Deal mix

Credit union commercial portfolios skew toward owner-occupied real estate, small business C&I, equipment, and SBA. Often built around member relationships and local economies. Self-employed and small-business borrower analysis dominates the workflow.

Team size

Most credit unions running commercial in-house have 1–4 dedicated underwriting staff. Many outsource to a CUSO precisely because they cannot justify hiring a dedicated commercial credit team for sub-cap MBL volume.

Why Aloan

Built for credit unions running real MBL volume with small teams

Aloan was designed for the operational reality at most credit unions: small commercial team, NCUA exam pressure, member-driven deal flow, and a board credit committee that wants standardized memos.

01

NCUA Part 723 documentation built in

Cash flow analysis, collateral evaluation, and credit memo content align with NCUA's MBL underwriting expectations. Source-cited output simplifies the file review at exam — every number traces back to its source document, and the credit decision authority remains with the credit union officer.

02

Member business lending without the staffing model

A 1–2 person credit team can plausibly run member business lending in-house with Aloan handling the spreading, multi-entity reasoning, and memo drafting. The credit union can grow MBL volume without hiring a three-person commercial team.

03

Standardized board memos

Every credit memo lands in the credit union's standardized format, ready for board credit committee review. Reduces the back-and-forth between credit officer and committee, and makes board reporting on MBL portfolio activity meaningfully cleaner.

04

Works with participation loans

Many credit unions participate in commercial credits to deploy capital efficiently against the MBL cap. The Aloan-generated analysis is sharable with participating institutions, which removes the typical re-underwriting friction in participations.

05

Self-employed and small-business borrower analysis

The credit union member who runs an LLC, files a Schedule C, owns half of an LLC partnership, and personally guarantees the loan — that profile dominates credit union commercial. Aloan was built for it: 1040, Schedule C, K-1 tracing, personal financial statements, all reconciled into a clean global cash flow.

06

Volume-based pricing that fits sub-cap MBL economics

Pricing is tied to deal volume rather than seat licenses. Credit unions running 50–300 MBL credits per year do not pay enterprise-platform pricing. Most credit unions see ROI on the first 30–50 deals processed.

Built for the exam cycle

NCUA-aligned from day one

Aloan was built for regulated lending. The platform aligns with NCUA expectations on MBL underwriting documentation, third-party AI vendor risk management, and credit decision authority.

NCUA Part 723 — Member Business Loans

Cash flow analysis, collateral evaluation, repayment ability, and credit memo content align with the documentation NCUA expects in the MBL file. The source-cited audit trail makes the file walk-through at exam meaningfully faster.

NCUA Letter to Credit Unions on AI vendor risk

Aloan provides the model documentation, validation evidence, and ongoing monitoring that NCUA expects when a credit union adopts a third-party AI vendor. SOC 2 Type II coverage is in place; underlying infrastructure (Vertex AI and AWS Bedrock) is also SOC 2 Type II.

Credit decision authority retained by the credit union

Aloan is decision support, not a decision engine. The credit officer reviews, edits, and approves every output. This matters for NCUA: the credit union retains the lending authority that NCUA holds it accountable for, and the documentation reflects that.

CFPB 1071 small business data collection

Federally insured credit unions originating covered small business credit are subject to CFPB 1071. Aloan produces the application-and-decision documentation trail that simplifies 1071 audit response and supports defensible fair lending review.

Read the full Examiner Readiness Guide for SR 11-7, OCC Bulletin 2023-17, and OCC 2025-26 details.

What changes day one

What changes when AI takes the keystroke work off the credit team

These are the day-to-day shifts credit union commercial teams report after Aloan goes live.

  • A 1–2 person credit team can run MBL in-house at volume that previously required a CUSO or three-person team
  • Member turnaround on commercial credit decisions drops from 2–3 weeks to 3–5 days
  • Spreading and memo prep on a typical owner-occupied CRE deal drops from 4–6 hours to 30–45 minutes of review
  • Board credit committee packets land standardized — no more reformatting between analyst and committee
  • NCUA exam walkthrough of MBL files takes minutes per credit instead of hours of analyst preparation
  • SBA 7(a) and 504 underwriting becomes economically viable for the credit union for the first time
  • Self-employed member loans (1040 + Schedule C + K-1s + personal guarantor) reconcile cleanly without the analyst rebuilding it in Excel
  • Senior credit officers stop doing keystroke work and spend their week on member-relationship and credit-judgment work

FAQ

Common questions

How does Aloan handle Member Business Lending (MBL) requirements?

Aloan automates the underwriting analysis required by NCUA Part 723 — including the cash flow analysis, collateral evaluation, and credit memo documentation that the regulator expects in the file. The platform produces standardized memos that align with the credit union's board-approved MBL policy and lending limits, and the source-cited audit trail simplifies NCUA exam review of MBL files. The platform does not enforce MBL limits or aggregate exposures across the portfolio (those live in the LOS or core), but it makes per-deal MBL underwriting meaningfully faster.

Can a credit union use Aloan for commercial loans up to the 12.25% MBL cap?

Yes. Aloan handles the full range of member business loans — from small owner-occupied real estate and equipment finance through multi-entity CRE deals up against the 12.25% MBL aggregate cap. For credit unions that have received an MBL exception or operate under the low-income designation that exempts them from the cap, the platform scales without per-deal configuration changes. The underwriting workflow is the same regardless of where the loan sits relative to the cap.

How does NCUA exam treat AI-generated credit memos?

NCUA examiners treat AI-generated underwriting analysis the way they treat any other underwriting output: they evaluate whether the analysis is reproducible, whether the credit decision authority remains with the credit union, and whether the documentation supports the lending decision. Aloan addresses all three. Every figure cites its source document. The credit officer reviews and approves every memo. Model documentation aligns with NCUA Letter to Credit Unions guidance on third-party risk management for AI vendors. Credit unions deploying Aloan have not seen exam findings tied to the AI output.

Does Aloan support participation loans across multiple credit unions?

Yes. Many credit unions participate in commercial credits originated by other credit unions, regional banks, or CUSOs — particularly to deploy capital efficiently against the MBL cap. Aloan produces the standardized analysis and credit memo that the participating credit union needs for its own credit committee and exam file. The same Aloan output can be shared with all participating institutions, which removes the typical re-underwriting friction in participation deals.

How does Aloan compare to running commercial through a CUSO?

Many credit unions outsource commercial underwriting to a CUSO precisely because they can’t justify hiring a dedicated commercial credit team. Aloan changes that math. With AI handling the spreading and credit memo work, a 1–2 person credit union team can plausibly run commercial in-house at the volume that previously required CUSO support. Credit unions that prefer the CUSO model still benefit — the CUSO can adopt Aloan to deliver faster, more standardized output to its member CUs (see the CUSO industry page).

Can Aloan handle the broad member business mix typical at a credit union?

Yes. The typical credit union commercial book leans heavily on owner-occupied real estate, small business C&I, equipment, and SBA — the deal types where member relationships and local economic ties are the credit thesis. Aloan handles all of these, including the common challenge of analyzing self-employed borrowers and small operating companies whose tax returns are intertwined with their personal financials. Multi-entity tax return handling and global cash flow analysis are core capabilities.

How does Aloan integrate with credit union core systems?

Aloan is core-agnostic. The platform sits in the underwriting analysis layer and integrates with whichever core or LOS the credit union uses — Symitar, Corelation KeyStone, FIS Cleartouch, Fiserv DNA or XP2, or others. Aloan delivers the spread, analysis, and credit memo output that gets attached to the loan record in the credit union's existing system. No core replacement required.

What does Aloan cost for a credit union under $1B in assets?

Pricing is volume-based, not seat-based, which works well for credit unions where one or two analysts handle the entire commercial pipeline. Most credit unions in the $250M–$1B range land in a low five-figure annual price point with no implementation fee. The relevant ROI math is the underwriting hours freed up per credit — most credit unions break even on the first 30–50 commercial credits processed.

Does Aloan help with the talent shortage in credit union commercial lending?

Yes — directly. Commercial credit officers with 10+ years of experience are scarce and expensive, and the credit union industry has been particularly squeezed. Aloan does not replace that experience, but it removes the keystroke labor (spreading, document organization, memo drafting) so the senior credit officer can focus on the credit decision and member relationship. A credit union that previously needed three commercial underwriters can run with one senior CO and an Aloan deployment, with output quality that holds up in front of NCUA.

Other institutions

See Aloan for other institution types

See Aloan run on a real credit union member business credit

Bring a representative MBL file — owner-occupied real estate, member with three LLCs, the works. We will show you the spread, the global cash flow, and the draft memo with your credit union's standard format applied.