Model and Data Governance

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A Pragmatic Model Risk Management Partner

SMEs, quants, and tools to support your model risk program

RiskSpan model validation analysts, managers, and subject matter experts have been validating models for well over a decade.

We know what works and what doesn’t when it comes to devising effective challenges, evaluating conceptual soundness, verifying data sources and process, and constructing benchmarking, back-testing, outcomes analyses, and sensitivity testing.

Proprietary Data, Analytical Tools, and Machine Learning Models

RiskSpan’s suite of models and machine learning applications function as ready-made benchmarks for a wide range of model validations.

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A Broad Range of Validation Experience

Our SMEs and analysts are experienced in validating over 50 types of models, including market risk, credit, prepayment, AML, and ALM.

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Comprehensive Model Validations

Full- and Limited-Scope

Conceptual Soundness

Expert in evaluating and assessing model design, input assumptions, data quality and sufficiency, and developmental evidence.

Process Verification

Practiced in reverse engineering modeling processes, ensuring models operate as intended, and applying benchmarking methods.

Outcomes Analysis

Specialized in determining and applying the most suitable statistical evaluation metrics for robust, defensible back-testing.

Data Governance

Trust your data

Data governance processes support a new culture in the industry around accountability for data quality and availability.

RiskSpan’s team of model and data experts can help you and your team ensure that the data assets that drive your models and forecasts have integrity, are appropriately available, usable, and secure.

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Model Inventory Made Simple

Customizable Model Risk Management Software

RiskSpan’s Model Risk Management Module facilitates planning activities and stores model documentation and validation reports in a simple, clean, and easy-to-use interface.

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