For Lenders & Fintech

Your AI makes credit decisions. Can you defend them?

If a model decides who gets credit and at what price, regulators treat it as your decision — explainable, fair, and documented. iDharma independently audits lending AI so you can show your board, your partner bank, and your examiner exactly where it stands.

Sample Risk Snapshot Preview
GovernanceMedium
Data provenanceHigh
Bias & fairnessLow
SecurityMedium
ComplianceHigh
ECOA / Reg B Fair lending EU AI Act NIST AI RMF ISO/IEC 42001
Why this matters now

Lending AI is where enforcement is already live

Regulators aren't waiting for new AI laws to act on lending models — existing fair-lending and consumer-protection rules already apply to them.

Existing rules already cover your models

Adverse-action notices, disparate-impact analysis, and model documentation obligations apply to AI and alternative-data models today — under the rules lenders already answer to.

Regulators are acting on AI lending practices

Enforcement actions have targeted lending AI for unexplainable decisions and proxy discrimination. Our Insights teardowns cover real, cited cases.

Read the teardowns →

Your partners are asking first

Partner banks, warehouse lenders, and enterprise customers increasingly require evidence of model governance in diligence. An independent read is how you answer without opening your entire model stack.

What we examine

Built for how lending AI actually fails

The five audit dimensions, applied to the failure modes credit models are known for.

Read our methodology →

Fairness & disparate impact

Whether outcomes differ across protected groups, whether alternative data acts as a proxy for them, and whether anyone tested for it before launch.

Explainability & adverse action

Whether you can give the specific, accurate reasons for a decline that notices require — from the model as it actually runs, not a simplified stand-in.

Data provenance

Where training and input data came from, whether you have the right to use it, and what bias it carries in with it.

Model governance

Who owns the model, what changed and when, how overrides work, and whether any of it would survive an examiner's questions.

Security & manipulation

Whether the model or its pipeline can be gamed — manipulated inputs, adversarial patterns, or drift nobody is watching.

The cost of not knowing

Turn a vague fear into a number — yours

We won't tell you what your exposure is — we'd be guessing, and your compliance team would know it. Instead, our free calculator lets you build the number yourself: your models, your deal values, your remediation costs. One input stays honestly blank — the share of models with an undetected issue. That's the number an audit answers.

Open the Cost of Not Auditing calculator
How it works

From request to board-ready report

01

Request

Tell us about your lending AI — scorecards, ML models, or vendor tools. Nothing is charged.

02

Scope & fixed quote

We agree systems, depth, and price before any work begins. You approve the scope first.

03

Audit (1–4 weeks)

An iDharma-verified expert reviews your models against our published methodology — at the speed lending teams actually ship.

04

Report & walkthrough

A prioritized findings report your risk committee, partner bank, or examiner can read — with 14 business days of written follow-up.

Who this is for

For the person accountable when the model is wrong

In lending, AI decisions carry named owners. These are the people who have to answer for them — and what an independent audit puts in their hands.

01
Chief Risk Officers

An independent read on model risk you didn't have to produce yourself.

Trigger · a peer lender lands an enforcement action
02
Compliance & fair-lending officers

Evidence of testing and documentation, mapped to the obligations you already carry.

Trigger · an exam or internal review is scheduled
03
General Counsel

A defensible, third-party record of diligence — before a regulator or plaintiff asks for one.

Trigger · a complaint or demand letter arrives
04
Founders & CTOs at fintech lenders

Pass partner-bank diligence without giving every counterparty your model internals.

Trigger · a bank partnership or funding round opens diligence

Recognise yourself in one of these? Start with the free 60-second read.

Where you stand

Know exactly where your lending AI stands.

An independent iDharma audit shows where your models are accurate, fair, secure, and compliant — and what to fix first.

Accurate № 01
  • Performs the way it’s claimed to
  • Where it quietly doesn’t — surfaced
  • Judged on the borrowers who matter
Lending AI audit · iDharma
Fair № 02
  • Outcomes hold up across protected groups
  • Alternative data checked as a quiet proxy
  • Proxy risk called out in plain English
Lending AI audit · iDharma
Compliant № 03
  • Mapped to ECOA
  • Mapped to the EU AI Act
  • What a partner bank or examiner will actually hold you to
Lending AI audit · iDharma