AI that can face your examiner and your board.
KYC, AML, BSA, and fair-lending compliance demand more than a model that scores well in testing. They require explainable decisions, full audit trails, encrypted data pipelines, and disparity monitoring. Most AI platforms do not have any of those. MetaSys builds them in from the first architecture session.
We have shipped AI underwriting systems processing 3,000 or more applications per day for financial services clients. The work is in production, not a pilot.
AI in financial services has to be accurate, explainable, and auditable. Most is not.
The gap between what AI vendors promise and what federal and state examiners expect is wide. Here is where most fintech and lending AI falls short.
Most AI is a black box regulators cannot touch
A model that returns a score with no explanation is not deployable in a regulated lending or AML workflow. CFPB adverse-action requirements, fair-lending scrutiny, and BSA examination all require you to show your work. Most off-the-shelf AI cannot do that.
Audit trails are an afterthought, not a feature
When your examiner asks for every decision made by your underwriting model over the past 18 months, including the input features, model version, and timestamp, can you produce that? Most teams cannot. MetaSys builds that logging in from day one.
PII flowing through AI pipelines is a compliance liability
Name, SSN, account number, and transaction data touching an AI pipeline without field-level encryption, access controls, and data residency controls is a CCPA and GDPR exposure. Regulators and plaintiffs look at how data moves, not just where it lands.
Fair-lending risk is invisible until it is not
Disparate impact does not require intent. A model trained on historical data can encode proxy discrimination without a single protected class variable in the feature set. Without active disparity monitoring, you will not know until an examiner tells you.
Four systems built for regulated financial workflows.
We build production AI for fintech lenders, credit platforms, and bank technology teams. These are the four areas where we have the deepest patterns and the most production experience.
Underwriting automation
We build end-to-end underwriting pipelines that ingest application data, run bureau pulls, score the application, and surface a decision with full SHAP-based explanation. Every step is logged. Human-in-the-loop review gates are configurable by risk tier.
See underwriting case studyFraud detection
Real-time and batch fraud scoring across transaction streams, account applications, and identity verification. Models are trained on your data, monitored for drift, and tuned continuously. Alert workflows route to your ops team with full feature context.
Agentic AI SystemsKYC and AML automation
Identity verification pipelines with document OCR, liveness checks, watchlist screening, and PEP matching. AML transaction monitoring with configurable rule layers and ML-based anomaly detection. SAR-ready case documentation built into the workflow.
AI Intelligent AutomationCompliance automation
Automated adverse-action notice generation, HMDA data preparation, CRA tracking, and regulatory reporting pipelines. We connect your decisioning systems to your compliance outputs so manual reconciliation is not your team's problem.
Data and AI PlatformsEight practices built into every financial AI system we ship.
These are not add-ons or optional modules. They are the architecture of every engagement we take on in financial services. See also: Data and AI Platforms and our fintech industry page.
Explainable decisions
SHAP values on every model output. Examiners and internal compliance teams see exactly which factors drove each decision, in plain language.
Full decision audit log
Input features, model version, output score, reviewer action, and timestamp written to an immutable append-only store. Reproducible on demand.
PII encryption at field level
Sensitive fields encrypted with AES-256 before storage. Keys managed separately per client. No plaintext PII at rest in the AI pipeline.
Role-based access control
Least-privilege access enforced at the API and data layer. Every access event logged. Suitable for SOC 2-aligned environments.
CCPA and GDPR-aware architecture
Data processed in your chosen cloud region. Right-to-erasure workflows supported. We design the data flow so jurisdictional compliance is tractable.
Fair-lending disparity monitoring
Approval rate and pricing disparity tracked by protected class proxies against ECOA and fair-lending thresholds. Alerts when drift exceeds your configured tolerance.
SOC 2-aligned practices
Access control, encryption, audit logging, vulnerability management, and incident response built into every engagement. We support your audit evidence requirements.
Human-in-the-loop review gates
High-risk or edge-case applications route to human reviewers with full model context. Every override is logged. Supports your model risk management framework.
Production results from a live underwriting system.
AI Underwriting at Scale for a Consumer Lending Platform
A consumer lending platform needed to process a high volume of applications without growing its underwriting headcount. Manual review was the bottleneck, and the existing scoring rules were producing inconsistent decisions that created fair-lending exposure. MetaSys replaced the rule-based system with an ML underwriting pipeline with SHAP-based explanations, full decision logging, and automated adverse-action notice generation.
“MetaSys built the data and AI infrastructure our wealth management practice needed to scale without hiring a team of engineers. The systems they delivered are clean, well-documented, and genuinely production-grade. They understand the compliance requirements of financial services and they build accordingly.”
Nick Burton
Legacy Wealth Holdings, US
What compliance buyers ask us most.
More questions? Visit our full FAQ or see our fintech and banking industry page.
Bring your compliance use case. Walk away with an architecture and a plan.
We scope every AI engagement in financial services the same way: a working session to map the workflow, the data, the regulatory exposure, and what production looks like. You get a clear picture of what we would build, how it handles compliance, and what it takes to get there.
30-minute call, no commitment. Most clients hear back within one business day.