The ability of Global Systemically Important Banks - those banks whose failure would materially affect the global financial system - to identify risk concentrations and to aggregate their risk exposures in a timely fashion is now recognized as an important step for safeguarding the stability of the financial system and avoiding future crises. Regulators representing the G20 countries are in the process of providing guidelines to banks on best practices for risk data aggregation, together with initial reporting requirements and timetables. The goal of large banks to deliver the required information in a timely fashion poses numerous technical and logistical challenges, largely due to their dependence on silo-specific legacy information systems and the widespread use of manual processes for risk data aggregation. This paper addresses the challenges of risk data aggregation in Global Systemically Important Banks, particularly in terms of meeting the regulatory schedules for gathering, validating, and reporting the information. It introduces an innovative data model and middleware approach to address these requirements in an efficient, flexible, and scalable manner. The approach can accelerate development of a bank-wide exposure-reporting solution that meets regulatory requirements while leveraging existing investments and infrastructure of the reporting bank.