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    Domino for Financial Services

    Model faster, reduce risk, manage compliance

    Enterprise MLOps: Boost model velocity, ease compliance

    Data science drives competitive advantage and profitability, but it has to exist within the complex financial regulatory frameworks.  You have to scale data science and reduce the time to market, while also knowing what your models are doing at all times in order to safely depend on them. 

    Domino’s Enterprise MLOps platform helps quants and data scientists at the world’s largest financial services institutions:

    • Personalize customer interactions and offers to build better relationships and drive profitability
    • Identify, test, and manage risk across the entire portfolio, including use cases such as credit risk, capital planning, anti-money laundering, and regulatory compliance.
    • Detect identity and payments fraud in real-time.
    • Analyze macroeconomic trends
    • Quickly detect trade signals 

    Why financial institutions depend on Domino

    Domino is a force multiplier for your data science. You can select the best tools for the job and seamlessly integrate them into your complex data science ecosystem. The Domino Enterprise MLOps platform is used by leading financial institutions worldwide to industrialize data science and quantitative research.

    Jacob Grotta

    “We’ve been able to standardize the data, the know-how, and the ways of collaborating amongst ourselves and with our customers so that they can see the work we’re doing, as we do it. Domino accelerates our speed to delivery, providing a much faster and better return on our modeling investment.”

    Jason Grotta
    Managing Director of Risk and Finance Analytics
    Case Study

    Data Science at a Fortune 500 Global Financial Services Leader

    Learn how this global financial services organization is transforming every part of its business using data science—from underwriting to customer service to human resources (HR).

    Read the case study
    Case Study

    Driving Customer Value and Efficiency by Transforming Model Development and Deployment

    Learn how a more than 50% reduction in the time to move models into production enables Moody’s Analytics to get information into the hands of clients faster.

    Read the Moody's case study

    Recommended resources

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    Change Management: Winning Over AI Skeptics in Banking & Beyond

    Chun Schiros, SVP, Head of Enterprise Data Science Group at Regions Bank, reveals how her team is leveraging AI solutions to optimize the banking experience. She also shares her change management tips for driving adoption of machine learning among data skeptics.

    See why leading rating agencies and banks run on Domino