Model Risk Management with Domino

Domino's Enterprise MLOps Platform supports your robust Model Risk Management processes with a system of record, full reproducibility, and integrated model monitoring.

Why Domino for monetization and productization of data, insights, and models

Domino provides a system of record.

SYSTEM OF RECORD

A single system for all your models

Documentation, code, and model inventories inevitably get out of sync when spread across systems. Regulations like SR 11-7, CCAR, CRD IV, and GDPR require a holistic approach to model risk management that spans development and usage. Domino tracks the provenance of a model from idea to impact, showing who worked on it, what they did, how they deployed it, and how it is used in production.

Reproducibility screen

REPRODUCIBILITY ENGINE

Quickly reproduce and validate work

Model validation teams spend the vast majority of their time gathering documents to piece together how a model was built and performs. Domino's Reproducibility Engine automatically tracks changes to code, data, tools, and packages through continual version control. These are captured in Durable Workspaces that allow data scientists and validators to instantly recreate the exact experiment environment used to create a model, even if tools and developers have changed in the interim. The discussion functionality centralizes conversations previously buried in thousands of emails.

Out-of-the-box support for Feast– the emerging, open-source standard for feature stores – increases the reproducibility and reusability of features. You have a single source of truth for calculating important features, driving reuse and consistency.

INTEGRATED MODEL MONITORING

Efficiently track all aspects of model performance

Many organizations struggle to effectively monitor models in production and efficiently remediate issues to keep models at peak performance.

Domino's integrated model monitoring provides a “single pane of glass” for observing traffic, drift, and health trends for all production models with out-of-the-box and custom metrics. You will be automatically alerted when drift, divergence, and data quality checks exceed thresholds. When retraining is needed, it's easy to drill down to model features to modify, retrain and redeploy models quickly.

This lets you see all production assets generated within Domino in a single location, acting as a model inventory. See all usage metrics, versions, and error rates for all data science models that have entered production inside your organization.

Explore Model Risk Management Resources

Case Study

How Allstate Maintains Reproducibility for Auditors

Read the case study

Case Study

Data Science at a Fortune 500 Global Financial Services Leader

Read the case study

White Paper

Model Risk Management in Domino

Read the whitepaper

Talk to a product expert

Watch a demo or talk to an expert to take the first step toward exploring how Domino can unleash data science in your organization.