Model Governance Strategy Definition & Implementation​

The Client faced challenges meeting regulatory requirements for Model and Data Governance and engaged RGP to assist in upgrading the forecasting engine that calculated Liquidity Coverage Ratios and Net Stable Funding Ratios. A secondary effort focused on establishing data and model governance to meet regulatory and accounting needs. RGP worked with key client stakeholders to define roles and responsibilities, creating a formal team structure and governance process. RGP also captured data requirements and documented data lineage and transformations to support the forecasting engine upgrade.​

RGP deployed a team of data experts and consultants to advise on business and technical requirements for model governance strategy. The team collaborated with stakeholders to define roles and responsibilities for data stewards, owners, custodians, and consumers of forecasting data. They also leveraged RGP’s expert network to develop a tailored perspective on data domains specific to the Client’s requirements for loans and securities. Data lineage, including hops and transformations, was captured for high-priority forecasting data elements, and data quality rules and ETL controls were created to validate data transfers from source to target.​

RGP helped the Client prioritize data assets, improve quality, and establish governance, ensuring accurate reporting and supporting business decisions and regulatory compliance.​