AI Governance for Regulated Financial Institutions

Monitor, explain, and govern AI systems with confidence.

Clarigent AI helps banks, insurers, and regulated enterprises manage AI risk through explainability, concept drift detection, model monitoring, and audit-ready governance.

Built for trustworthy financial AI.

Clarigent AI focuses on the reliability, transparency, and operational control required when machine learning systems influence high-stakes financial decisions.

Explainable AI

Generate local and global explanations using feature attribution and interpretable model insights.

Concept Drift Detection

Track shifts in data and model behaviour to identify when explanations and predictions may become unreliable.

Model Monitoring

Monitor model health, prediction quality, data changes, and governance events across production workflows.

Audit Trails

Maintain structured logs of decisions, explanations, model versions, and governance actions.

Regulatory Readiness

Support transparency, accountability, and review processes for regulated AI deployments.

Financial ML Focus

Designed around credit risk, fraud detection, risk scoring, and enterprise AI governance use cases.

From model performance to explanation reliability.

Financial institutions need more than accurate predictions. They need consistent, auditable, and trustworthy explanations that remain meaningful as data and business conditions change over time.

XAI Explainable AI for decision transparency
Drift Detection of changing data and model behaviour
Audit Governance evidence for review and accountability

Building the future of AI governance.

Clarigent AI is currently under development in Auckland, New Zealand. For research, collaboration, or early pilot discussions, contact us.