AI Fraud Detection Pilot Due Diligence: 12 Questions Banks Should Ask
A practical AI fraud pilot due-diligence checklist for banks: 12 questions on baseline, historical evidence, review capacity, controls, authority and vendor claims.
AEGI Insights
Practical guidance for evaluating AI and risk-workflow changes before production commitment.
Methods, market signals and evidence-oriented guidance for financial institutions deciding whether one proposed change deserves the next controlled stage.
Bring One WorkflowKnowledge surface
Evaluation methods, governance context and market research.
AEGI Insights is designed to grow with the research programme. Current articles cover controlled evaluation, fraud and risk workflows, assurance and Southeast Asian regulatory practice; future market research can use the same canonical publishing system without creating a second content silo.
AEGI October 2026 Engineering Evidence: Synthetic Fraud Review and Recovery
October 2026 evidence update: AEGI's bounded synthetic Fraud workflow, Core research recheck, Ops review and recovery tests, plus the limits of draft and non-production results.
AEGI Shield Fraud Workflow: Browser-Verified Synthetic Execution and the Path to Controlled Evaluation
October 2026 engineering update: AEGI tested its bounded synthetic Fraud review workflow through authenticated HTTP, Chromium, pinned Core research verification and version-consistent audit export. This is not customer pilot or production validation.
Position Paper: Shared Credit-Fraud Risk Context as a Review Layer — Not a Replacement Model
AEGI Labs' public position on why related credit and fraud intelligence can be reviewed together without collapsing model ownership, bank authority or evidence boundaries.
Position Paper: Governing the Decision Between AI Output and Production Change in Banking
AEGI Labs' public position on a recurring banking AI problem: how to determine whether one proposed model, signal or workflow change deserves to progress without confusing recommendation with authority.
AEGI BAF-003 Evidence Note: What 494 → 544 at Fixed Review Capacity Shows — and Does Not Show
A public evidence note on AEGI's frozen BAF-003 Shared-Context evaluation: fixed capacity, measured queue-composition difference, reproducibility, and the limits of what can be claimed.
When Is an AI or Risk Workflow Ready for Controlled Evaluation?
A practical readiness checklist for deciding whether a banking AI, fraud or risk workflow can be evaluated as one bounded change rather than becoming an open-ended build project.
What Data Does AEGI Shield Need? From Public-Safe Scoping to Bank-Controlled Replay
AEGI Shield does not start by asking for a bank's full dataset. This article explains the staged data boundary for one controlled workflow evaluation.
What Does AEGI Core Verify — and What Does It Not Verify?
AEGI Core is an evidence-assurance layer, not a model validator or business-truth engine. This article explains the boundary in public-safe terms.
ONE BOUNDED QUESTION