Epsilon marks 30 years as banks rush to fix capital markets data for AI

Epsilon Technologies Group is highlighting three decades of capital markets data infrastructure as regional banks and other financial firms move into AI. The pitch: AI only works if trade, risk and accounting data are governed, connected and trusted first.

Why it matters: - Capital markets firms are pushing into AI while still dealing with disconnected trade, risk and accounting data. - Manual reconciliations, shadow feeds and custom code can raise cost and risk and leave business units with competing versions of the truth. - Epsilon Technologies Group says a governed data foundation is the difference between faster AI decisions and faster mistakes.

What happened: - Epsilon Technologies Group marked 30 years building trading, risk and accounting data infrastructure for regional banks, GSEs and Federal Home Loan Banks. - The company is positioning that work as a response to a problem many capital markets firms are now confronting more openly as they adopt AI. - Epsilon said its approach connects governed, structured data environments across trading, valuation, risk and accounting.

The details: - Epsilon’s services include strategy, architecture and integration, governance, reporting and cloud data warehousing. - The firm says those services are delivered by people with direct capital markets experience. - Epsilon says its data model can be configured for new products instead of requiring custom code. - The company says institutions get one governed source of business logic instead of duplicated shadow feeds. - Epsilon says clear ownership of data and rules helps create a trusted source of truth across the business. - The company says its products and services are meant to support AI and analytics on top of that foundation. - Epsilon says its licensed products include ETS, Principia Analytic System and pasVal. - Epsilon also offers consulting services in implementation, advisory, AI, analytics, risk management, accounting and data modeling.

Between the lines: - The message is less about AI software and more about infrastructure discipline. - Epsilon is arguing that many institutions are trying to layer AI onto fragmented systems that were never built for shared governance. - The company is also tying its long-standing platform to regulatory momentum that favors common identifiers, consistent schemas and defined data. - New federal data standards under the Financial Data Transparency Act are set to take effect Oct. 1, 2026. - FHFA has also proposed expanding Federal Home Loan Bank board expertise to include AI, technology and modeling.

What's next: - Epsilon says the capital markets industry is catching up to data standards the company has been building toward for years. - The company expects institutions to keep investing in governed data models as AI use expands. - Epsilon is directing readers to more information about its products and services.

The bottom line: - Epsilon’s core pitch is simple: AI in capital markets will only scale if the underlying data, rules and ownership are already clean, shared and governed.