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    Data Warehouse

    Moody's Analytics provides a powerful data management platform to help financial institutions effectively manage risks and regulatory compliance. The Data Warehouse Solution integrates seamlessly into core business systems to help institutions with end-to-end risk management and regulatory compliance management.

    Managers are challenged with delivering efficient and effective risk management to maximize profits and deliver regulatory compliance. They must identify opportunities quickly and exit those which do not meet their requirements. They also must perform asset and liability management (ALM), liquidity risk management, and compliance for Basel I, II, and III, IFRS 9, and many others.

    Moody's Analytics data management platform streamlines and automates businesses' enterprise risk management and regulatory compliance. The solution smoothly integrates into a bank's core applications and consolidates data across business silos. Once consolidated, data can be used to perform regulatory compliance and reporting, stress testing, ALM, and economic capital assessments, thus aligning risk management across the business. Insights derived from consolidated data help banks achieve strategic objectives and reduce the cost of capital. 

    Automate and streamline enterprise risk management

    Our data warehouse solutions allow bank managers to integrate across multiple business units, taking a holistic approach to risk management and reporting, economic capital, stress testing, liquidity management, and regulatory capital. This capability allows managers to reconcile complex and conflicting business drivers and issues, enabling them to create optimal solutions that meet the strategic objectives of the business.

    Enhance data quality management

    Accurate, up-to-date, and correctly formatted data is central to effective enterprise risk management. Our solution applies data quality management tools during data consolidation, results calculation, and reporting, so missing data, out-of-date results, and incorrectly formatted data points can be identified and addressed quickly. This capability allows banks to automate risk management and be confident that their data quality standards, cost management, and commercial objectives have been met.

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