Risk
SR 11-7
Model risk guidance is established
The US Federal Reserve and OCC guidance from 2011 expects a model inventory, independent validation and ongoing monitoring for every model in use.
AI Model GovernanceEvery version tracked · One-click rollback
Know what your models are doing and prove it to an examiner
Every model version is tracked, compared and watched for drift once it's in production. If performance slips, you roll back to the previous version in one click. The record is built for model risk reviews under SR 11-7 and the EU AI Act.
Model watch
Models in production
MODELS MONITORED
1284310
NEEDING ATTENTION
2140
Card fraud score
Payment scoring
DRIFT 12··
HealthyScanning
AML alert triage
Monitoring alerts
DRIFT 63··
WatchScanning
Customer risk score
KYC rating
DRIFT 81··
Action neededScanning
Name match model
Screening
DRIFT 22··
HealthyScanning
Claims fraud score
Insurance claims
DRIFT 48··
WatchScanning
Credit early warning
Lending book
DRIFT 15··
HealthyScanning
AI REASONING · Card fraud scoreHealthy · Drift 12
Comparing live performance with the validated baseline…
Stable inputsAlert rate normalValidated May
Performance matches the validated baseline. No action needed.
Every
Model version tracked
1 click
Rollback to the last version
Ongoing
Drift and bias monitoring
Why model risk reviews are painful
Your examiner asks which model made a decision. Can you answer?
Fraud, AML and screening decisions increasingly run on models. Each one has versions, data and thresholds that change. Without a record, nobody can say which version was live on a given day or why it changed.
Risk
SS1/23
The UK has its own principles
The Bank of England's PRA set model risk management principles for banks in Supervisory Statement SS1/23.
Risk
AI Act
AI in finance now has a law
The EU AI Act (Regulation 2024/1689) treats credit scoring as high-risk and sets documentation and oversight duties.
What FluxForce delivers
A live record of every model you run
The agent keeps the inventory, watches each model in production and builds the evidence your model risk team needs.
CAPABILITY 01 / 06
Model inventory
Every model, its owner, use and risk tier.
Every version, with its training data and settings.
Which version was live on any date.
Covers our agents' models and your own.
CAPABILITY 02 / 06
Version comparison
Compares a new version with the current one before release.
Tests on historical and synthetic data.
Shows where the two versions disagree.
Release needs the model owner's approval.
CAPABILITY 03 / 06
Drift and bias monitoring
Watches inputs and outputs for drift.
Checks outcome rates across customer segments.
Alerts the model owner when a limit is passed.
Tracks analyst overrides as an early signal.
CAPABILITY 04 / 06
One-click rollback
Return to the previous approved version in one click.
Rollback is logged with who did it and why.
The rolled-back version keeps its validation record.
Kill switch on every agent.
CAPABILITY 05 / 06
Explainable decisions
Each model decision carries a plain-language explanation.
Shows the factors behind individual decisions.
Readable by validators and examiners.
Linked to the case or alert it affected.
CAPABILITY 06 / 06
Review-ready reports
Model risk reports for SR 11-7 style reviews.
Documentation for EU AI Act obligations where they apply.
Validation history in one place.
Stores evidence in tamper-evident form.
What changes for your team
Model risk reviews with the evidence already gathered
We'll inventory a set of your production models and show you what the record looks like before your next review.
Every
Version on record
What was live, when, and who approved it.
1 click
Rollback
Back to the last approved version, logged.
Ongoing
Monitoring
Drift and bias checked in production, not once a year.
Owner
Approves every release
No model change goes live without a named approver.
Replay
For your examiner
Which model made a decision, and why.
The agents on this work
Three AI agents watching your models
One keeps the inventory and reports, one keeps the record, one tests without touching customer data.
Director AI Governance & Model Risk
Riya Intel
Keeps the model inventory, watches drift and bias, and builds model risk reports.
Model inventory
Drift and bias monitoring
SR 11-7 and EU AI Act reports
Senior AI Audit Trail Specialist
Arin Narrate
Links each model decision to the version and evidence behind it.
Decision-to-version links
Approval history
Audit packs
Senior AI Staging & Simulation Lead
Stella Simulant
Generates synthetic data to test models before release.
Synthetic test data
Scenario testing
No customer data needed for tests
Where it fits
Model governance wherever models make decisions
Banks, fintechs and insurers all run models on regulated decisions. The record they need is the same.
FRAUD, AML, CREDIT
Banking
Focus
Model risk teams
Scope
Validation cycles
Shadow mode to go-live90 DAYS
Results
One inventory across fraud, AML and credit models
Drift caught between validations
Reports ready for model risk reviews
FAST RELEASE CYCLES
Fintechs
Focus
Frequent model updates
Scope
Sponsor bank oversight
Shadow mode to go-live90 DAYS
Results
Every release compared and approved
Rollback ready if a release slips
Evidence your sponsor bank can review
CLAIMS AND PRICING
Insurers
Focus
Claims fraud models
Scope
Fairness checks
Shadow mode to go-live90 DAYS
Results
Bias checks across policyholder groups
Version history for every claims model
Records ready for your regulator
Questions? We Have Answers
Frequently Asked Questions
It covers the models behind our agents, and can register your own models for inventory and monitoring.
No. It alerts the model owner and makes rollback a one-click action. A person decides.
They're structured for SR 11-7 style model risk reviews, with documentation for EU AI Act obligations where they apply.
Outcome rates are compared across the customer segments you define, and differences beyond your limit open a review.
Yes. Synthetic data and scenarios let you test a new version before it touches production.
Which model version made a decision, who approved that version, how it was validated and how it performed in production.
Take the first step
See how an investigation file is built
Pick one alert type. We'll run the agents in shadow mode on your own data and show you the cases they prepare. Your team decides what happens next.
DeploymentDAY 90
Discovery
Shadow mode
Integration
Controlled go-liveDAY 76–90+
Security and governance