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AI tool prototypes

The Lab

Working prototypes that blueprint what modern operational risk tooling should look like for mid-tier banks.

Every tool in this lab started as a gap I hit inside a bank: a regulatory expectation with no tooling behind it, a committee process held together by spreadsheets and goodwill, a question from an examiner that took three weeks to answer because the evidence lived in nine places.

The premise is simple. Operational risk tooling stagnated at the register stage while the discipline moved to resilience: services, tolerances, dependencies, testing, evidence. AI makes the missing instruments buildable, but only when the builder understands what a regulator will probe and what effective challenge has to capture. So I build them: as working prototypes and blueprints, not products.

Two builds are live. The rest of AEGIS, the twelve-module suite, is in research, sequenced roughly by how much pain each gap causes. Everything here is published to be examined, challenged, and cited; the full roadmap, with architecture decisions and evaluation notes, is available on request.

Live builds
In research: the rest of the platform
In research

Third-Party Dependency Mapper

Nth-party dependency chains for critical services: who actually sits under your important business services, and where concentration hides.

In research

RCSA Copilot

Drafting and challenging risk and control self-assessments: consistency checks across units, stale-assessment detection, challenge prompts.

In research

RegChange Sentinel

Regulatory-change tracking mapped to obligations and controls, so a new guideline lands as a delta, not a reading assignment.

In research

Impact Tolerance Calibrator

Data-driven impact tolerances for important business services, in the metrics a board can actually approve.

In research

Control Rationalizer

Deduplication and gap analysis across bloated control libraries: which controls actually map to which risks, and which are theatre.

In research

External Loss Intelligence

Mining public loss events and enforcement actions into structured scenario inputs and comparator benchmarks.

In research

Issues Management

One register for self-identified, audit, and regulatory issues across the bank: lifecycle workflows from action plan to validated closure, and issue exposure aggregated across every taxonomy node.

In research

Leading-Indicator Intelligence

Which key risk indicators actually lead losses, and which merely decorate the pack: indicator quality grading, backtested thresholds, and honest early warning.

In research

Tail-Event Modeling for Stress Testing

Frequency and severity modeling for operational loss projection under stress, quantified in the shape the CCAR cycle expects.

In research

Loss Event Classification

Consistent, auditable classification of loss events at the point of capture, so the register feeds analysis instead of rework.

The full roadmap (sequencing, architecture decisions, and evaluation notes) is available on request.

Request the roadmap