Model Risk Management

Still investigating model drift manually?

Full-spectrum model risk intelligence. Ituring mrm detects issues weeks before traditional methods – complete investigation in 30 minutes, not 3 weeks.

Monitor models from any platform. Built for regulated industries with complete transparency and traceability to support your audit processes.

Fast Detection and Investigation

While Others Hunt for Weeks, You Know in Minutes

iTuring Model Relevancy Score

iTuring Model Relevancy Score

iTuring Model Relevancy Score

Complete Investigation Reports

*3 Spots Left This Week

Enterprise model risk teams report dramatic investigation acceleration and complete audit documentation with iTuring MRM.

Our Investigation Process

How Investigation Intelligence Works

Detect

iTuring Model Relevancy Score flags issues. (Weeks before traditional methods)

Analyze

Three-layer drift analysis runs. (Model, Feature, Data simultaneously)

Identify

Root cause pinpointed instantly. (Exact features with impact percentages)

Report

Complete investigation generated. (Board-ready evidence in minutes)

All Model Sources Monitored

Zero Surprises. Complete Coverage. Instant Intelligence.

Proactive Detection

Issues identified weeks before performance drops

Complete Documentation

Every action time-stamped and transparent

Custom Configuration

Monitor only what matters for your use case

Monitor Every Model – No Matter Where It’s Built

iTuring Models

iTuring AutoAI models with complete data lineage tracking and baseline comparison analysis

Production Models

iTuring Model Ops deployed models with real-time and batch data monitoring capabilities

External Models

Third-party models from Python, R, SAS - complete drift analysis for any platform

What We Track

Every Parameter. Every Platform. Complete Intelligence.

Model Drift KPIs

AUC, Precision, F1, Recall, Accuracy PSI, EMD, Incidence Rate tracking

Feature Drift KPIs

Fisher Score for numerical features Information Value for categorical features

Data Drift KPIs

Distribution, Missing, Skewness, Variance Mean, Standard Deviation monitoring

Custom Dashboards

Configurable templates and KPI selection Project-specific monitoring views

Alert Management

Configurable thresholds and severity levels Complete alert history with details

Automated Recommendations

Incremental, partial, complete retraining Data-driven remediation guidance

Investigation Intelligence - Know What Shifted, Why It Shifted, Show the Proof

Frequently Asked Questions

What is Model Risk Management and why is investigation speed critical?

Model Risk Management monitors machine learning models for performance degradation and compliance issues. For enterprise teams managing 200-1000+ models, manual investigation taking weeks creates operational risk. iTuring provides investigation intelligence that identifies issues and root causes in 30 minutes.

CI Model Relevancy Score uses advanced statistical analysis to identify model failure patterns weeks before they become visible in standard performance metrics. Combined with three-layer drift analysis, this provides early warning across model, feature, and data dimensions.

Yes. iTuring MRM monitors three model types: iTuring AutoML models, iTuring+MLFlux production models, and External models from any platform including Python, R, SAS, and third-party APIs. Complete investigation intelligence works regardless of model origin.

iTuring completes comprehensive model drift investigation in 30 minutes versus 3 weeks with traditional manual methods. The system analyzes model, feature, and data drift simultaneously, identifies exact root causes, and generates complete investigation reports automatically.

Every investigation action is automatically time-stamped and documented with complete transparency. iTuring provides comprehensive audit trails, drift analysis reports, root-cause identification, and remediation recommendations to support your compliance and audit processes.

Users create monitoring templates by selecting relevant KPIs from model, feature, and data drift categories. Custom dashboards can be configured for specific projects, model types, and monitoring requirements with configurable alert thresholds and periodicity.

iTuring monitors Model Drift KPIs (AUC, Precision, F1, Recall, PSI, EMD), Feature Drift KPIs (Fisher Score, Information Value, Correlation), and Data Drift KPIs (Distribution changes, Missing patterns, Statistical variations) with complete configurability.

Yes. When performance thresholds are exceeded, iTuring automatically provides data-driven recommendations including incremental retraining, partial model updates, or complete model refresh based on drift severity and impact analysis.