Enterprise Fraud Risk Program Request for Information

The Teacher Retirement System of Texas (TRS) has issued a Request for Information (RFI) for an Enterprise Fraud Risk Program, seeking comprehensive enterprise fraud management solutions to detect and prevent fraudulent activities across multiple domains. The RFI targets solutions capable of addressing fraud risks in member services, investment operations, and administrative functions including procurement, financial, and human resources. TRS is specifically looking for commercial off-the-shelf (COTS) solutions with minimal customization or modular solutions that can integrate with their existing Microsoft Azure data and AI platform. Respondents must provide detailed submissions encompassing solution architecture, functional and non-functional capabilities, integration approaches, data governance and security protocols, compliance alignment, reporting, analytics, and AI capabilities. The technical requirements mandate support for a modern data architecture using medallion architecture principles, RESTful APIs, Apache Delta Lake, Apache Kafka, and emerging AI standards. The RFI deadline is January 15, 2026, at 3:00 p.m. Central Time, with explicit clarification that this is not a Request for Proposal and no contract will be immediately awarded.

The RFI does not specify any specific set-aside designations or restrictions on responding organizations, and vendors are not penalized for non-response and can participate in future solicitations. No incumbent vendors are identified, and no specific award values or budget ranges are disclosed at this planning stage. The solution must demonstrate capabilities in fraud prevention, detection, mitigation, investigation, analytics, policy, and prosecution across employee, vendor, and third-party fraud domains. Non-functional requirements emphasize real-time processing scalability, explainable machine learning, immutable audit logs, role-based access controls, and disaster recovery capabilities. Respondents should include comprehensive case studies, implementation experiences across various fraud domains, and pricing model information. The technical infrastructure requires compatibility with TRS's existing systems, including integration with Microsoft Azure, support for advanced data processing technologies, and alignment with modern AI and data governance standards.