$2.5M
US settlement — a transaction-risk model blocked legitimate customers via a demographic proxy
MA AG, 2025
Fintech & Digital Payments AI Compliance · EU AI Act · 1–4 weeks
AI in credit, debit, and digital transactions — independently audited
Fraud-scoring and payment AI decide millions of transactions a day. Fair-treatment, AML and EU AI Act duties still apply.
NIST AI RMF
ISO/IEC 42001
EU AI Act
HIPAA
SOC 2
India DPDP
Where this sector stands
Fintech at a glance
Active
AML and fair-treatment enforcement on payment AI ongoing — regulators and private litigants stepping up
Post-April 2026
Dec 2027
EU AI Act high-risk obligations apply to AI that scores or blocks transactions — Annex III, from 2 December 2027
Verify with EU AI Office
Free, no signup — five questions and a real, specific finding about your AI in 60 seconds.
Get your free Risk Snapshot →What we audit
AI systems in scope for Fintech
Every system below is covered in a standard iDharma engagement. Complex or multi-system deployments are scoped on request.
See how it works
Transaction fraud & risk scoring
Real-time fraud, chargeback, and transaction-risk models — false-positive rate by demographic, explainability, and fair-treatment testing.
Payment authorization AI
Card, debit, and digital-wallet authorization decisions made in milliseconds — decision reconstruction, audit trails, and customer-impact review.
AML transaction monitoring
Anti-money-laundering and suspicious-activity models — accuracy benchmarking, alert quality, and BSA/AML documentation.
Digital-wallet & BNPL decisioning
Wallet onboarding, limit-setting, and buy-now-pay-later approvals — proxy-discrimination risk and adverse-action compliance.
Regulatory frameworks
What we audit against
Every iDharma Fintech engagement maps simultaneously against the frameworks below — producing one gap register, not 3 separate reports.
EU AI Act — High-Risk
AI that scores, limits, or blocks access to payment services can fall in scope — conformity assessment, technical documentation, and human-oversight obligations apply.
Key obligationsAML / BSA Obligations
Transaction-monitoring and suspicious-activity models must be explainable and defensible. Opaque alerting that cannot be justified creates regulatory exposure.
Key obligationsFair-Treatment & Adverse-Action Rules
Declining or restricting a customer's transactions can trigger notice and non-discrimination duties — including indirect discrimination via proxy variables.
Key obligationsOne engagement.
Three frameworks.
Mapped together.
Measured once.
Our methodology
How an iDharma audit works
We do not accept vendor documentation as evidence, and we do not produce checkbox compliance reports. Every audit gives you a named auditor, a cited methodology, and a straight answer on where your AI stands.
We test transaction and fraud models for proxy discrimination against protected classes — not just the obvious proxies.
We reconstruct real-time authorization decisions on a sample of your production traffic — vendor accuracy claims are not taken at face value.
We evaluate alert and decline explanations against the model's actual logic to verify they are accurate and defensible.
We produce documentation structured to satisfy both EU AI Act technical-file requirements and US model risk management (SR 11-7) expectations.
More sectors
Explore other domains
Fintech
AI in credit, debit, and digital transactions — independently audited
Learn more →
Finance
AI in banking, lending, and investment — audited against the EU AI Act
Learn more →
Healthcare
AI in diagnosis, triage, and care — audited against FDA SaMD and HIPAA
Learn more →
Insurance
AI in underwriting, pricing, and claims — high-risk under the EU AI Act
Learn more →
Get started
Deploying AI in payments or transactions?
Start with the free Risk Snapshot to understand your fraud-model and fair-treatment exposure before a regulator does.
Your situation
“AI is already making fintech decisions — with no independent proof it holds up.”
In 1–4 weeks
One prioritised gap register mapped to the frameworks you answer to — signed by a named auditor.
Scoped before you pay — nothing is charged until you approve what the engagement covers.
From Insights
Related reading
AI Model Risk Management for Lenders: What Counterparties Ask For
Partner banks, examiners and enterprise counterparties converge on four questions about AI in credit. What each one is really testing, and what an honest answer looks like.
Read the guide
INSIGHTS
Startups, Meet Your AI Stack: Budget‑Friendly Tools That Scale
For early-stage founders, building an AI-powered toolkit doesn’t have to break the bank. From ideation to growth mode, here’s how startups can tap into affordable, effective AI tools to autom
INSIGHTS
The Missing Link in Corporate AI Training
In today’s fast-paced AI era, companies are investing more in training—but why is most of it still missing the mark?
STANDARDS EXPLAINED
Colorado SB 26-189: Four Duties, and the One Nobody Budgets For
Notice before, disclosure after, human review on request, records for three years. Three are policy changes. The second is an engineering project, and it arrives late.
