AI Agent Auditability & Decision Ledger for Financial Services
Tenet AI is the decision ledger platform for AI agents in financial services. It captures every reasoning step, replays decisions deterministically, and generates audit trails that satisfy EU AI Act, SOC 2, MiFID II, and Basel III requirements — integrated in 2 lines of code via Ghost SDK. Financial services AI teams use Tenet to prove exactly why their credit scoring agents, fraud detection systems, and automated underwriting tools made each individual decision — with cryptographic tamper-evidence that satisfies regulators, auditors, and legal challenge.
Why Fintech Teams Use Tenet AI
Financial AI agents making credit decisions, fraud detection calls, trade recommendations, and insurance underwriting determinations operate under strict regulatory oversight. EU AI Act Annex III explicitly classifies credit scoring, insurance pricing, and financial service routing as high-risk AI systems requiring complete decision documentation. MiFID II mandates 5-year retention of investment recommendation records. GDPR Article 22 requires explanation of automated credit and insurance decisions. OCC SR 11-7 and Basel III model risk management guidance require documented evidence of model behavior in production. Tenet captures the intent, context snapshot, chosen action, and full reasoning chain for every agent decision — cryptographically immutable using SHA-256 hashing and Ed25519 signing, and deterministically replayable against new model versions before deployment. The unit is the individual business decision, not an aggregate metric or trace span.
Credit Decisioning AI and Regulatory Audit Requirements
Credit scoring and lending decision AI systems are explicitly classified as high-risk under EU AI Act Annex III category four, covering access to essential services including credit. Regulators require complete decision provenance — not the aggregate model accuracy, but the specific factors weighted for each applicant, the model version active at decision time, the policy context applied, and the reasoning chain that produced the outcome. When a loan applicant challenges a denial or a regulator requests documentation for a specific credit decision, aggregate model performance metrics are not the answer. Tenet captures this decision-level evidence with under 5 milliseconds of overhead, without requiring changes to existing credit model architecture. ECOA Reg B adverse action notification requirements are directly served by Tenet records — the reasoning chain provides the specific factors required by regulation. CFPB AI examination guidance specifically calls for AI decision traceability, which Tenet provides by design.
Fraud Detection AI: Why Decision Records Matter
Fraud detection agents that block transactions, freeze accounts, or trigger Suspicious Activity Reports create significant adverse action liability. Customers can challenge fraud flags under FCRA and Reg E. Regulators can request documentation for specific alerts. Financial regulators — OCC, FDIC, Federal Reserve — expect model risk documentation covering individual AI-driven decisions, not just aggregate precision and recall metrics. Standard monitoring tools show aggregate false positive rates but cannot explain why a specific transaction was flagged or a specific account was suspended. Tenet records the exact reasoning chain behind every fraud detection decision — the features that triggered the alert, the model version, the policy threshold applied, and the contextual factors weighed. This creates a defensible, auditor-ready record for every adverse action that an AI fraud agent takes.
Compliance Coverage: EU AI Act, SOC 2, MiFID II, GDPR
EU AI Act obligations for fintech AI: Article 11 technical documentation requirements, Article 12 automatic logging obligations for high-risk AI, Article 13 transparency and deployment instructions, Article 14 human oversight measures, and Annex IV documentation format for audit submissions. SOC 2 Type II Trust Services Criteria: CC7.2 anomaly detection and monitoring of AI decision patterns, CC6.1 access control documentation, CC4.1 change management records for model version updates. MiFID II: 5-year retention for investment recommendation records, audit trail requirements for algorithmic trading decisions. GDPR Article 22: individual explanation right for automated credit and financial decisions, human review mechanism requirement. OCC SR 11-7 model risk management: conceptual soundness documentation, ongoing monitoring, outcomes analysis, independent validation evidence. ECOA Reg B adverse action notification documentation with specific factor identification.
Behavioral Drift in Financial AI: The Silent Compliance Risk
Financial AI agents can exhibit behavioral drift — where the reasoning behind credit approvals, fraud flags, or underwriting decisions changes gradually without any code or model deployment event. For financial services, this creates fair lending liability (an agent that drifts toward systematically different reasoning for protected class applicants), adverse action documentation failures, and model risk management gaps that persist undetected until a regulator or legal challenge surfaces them. Aggregate model metrics remain stable while decision-level reasoning changes: an agent maintaining 94% credit approval accuracy can simultaneously begin weighting applicant attributes differently for specific demographic groups, showing no alert in any population-level monitoring system. Tenet detects behavioral drift at the decision level by replaying past credit or fraud decisions against the current agent state and producing a Semantic Diff — exactly which reasoning steps diverged and for which decision types. No code changes required to detect or diagnose the drift.
Integration with Fintech AI Stacks
Tenet integrates via Ghost SDK in 2 lines of Python or Node.js code. It works with any AI agent framework — LangChain, AutoGen, CrewAI, OpenAI Assistants, custom agents built on any LLM provider. On-premise VPC deployment keeps financial data and customer PII inside your infrastructure perimeter, satisfying data residency requirements for EU, UK, and US financial regulators. Decision records are stored in an append-only ledger and queryable via REST API, enabling integration with existing compliance management systems, GRC platforms, and regulatory reporting workflows. The Ghost SDK uses fire-and-forget writes — the agent is never blocked by Tenet logging. Average overhead is under 0.3ms, with p99 under 5ms.