Teradata Highlights New Enterprise AI Customer Engagements Across Global Financial Services
Customer results highlight how banks are turning trusted enterprise intelligence into action with AI
SAN DIEGO, July 28, 2026 /PRNewswire/ -- Teradata (NYSE: TDC) today showcased three recent customer engagements that demonstrate how leading financial institutions are unlocking value from AI, leveraging Teradata technology and forward-deployed engineering expertise to detect fraud in real time, democratize institutional knowledge, and enable conversational analytics at enterprise scale. Each engagement shows how AI can move from concept to measurable outcome without compromising the governance, auditability, and trust that regulated environments require.
AI case studies — Industry: Financial services & banking
- AI-powered network fraud detection at a leading Asia Pacific bank
Challenge: The most dangerous fraud in banking doesn't look like fraud. Instead, it looks like a perfect customer with strong income and a clean credit history. This bank's traditional credit models analyzed individuals, not relationships, leaving it blind to a sophisticated scheme in which coordinated networks moved money in circular flows to simulate stable, legitimate earnings. Synthetic identity fraud of this kind has surged in recent years, and conventional detection methods had no way to surface it.
AI solution: Using the Teradata platform, the bank shifted from analyzing records to analyzing relationships. Graph-based AI ran directly in-database, mapping the connections between accounts, transactions, and entities to expose the circular money flows that traditional models had missed entirely. The result was real-time detection at enterprise scale.
Outcome: By activating the intelligence that had always existed in the data in real time, the bank stopped significant fraudulent losses, strengthened lending decisions, and established a reusable in-database AI foundation capable of evolving alongside new fraud patterns. - Conversational analytics at enterprise scale for a large European bank
Challenge: With operations spanning 20 countries and 40 data domains, this bank's analytical infrastructure was a bottleneck: valuable intelligence was effectively locked behind a SQL requirement, accessible only to a small population of technical specialists. Business stakeholders who needed trusted answers quickly and in plain language had to wait for data team support. At enterprise scale, that delay had a measurable cost.
AI solution: Teradata built a conversational data layer directly on the Teradata platform, with context-aware models grounded in the bank's own business structure, in-database analytics, and LLMs operating on pre-aggregated data for speed and accuracy. Business users across the bank's 20 operating countries can now query the organization's full data estate in plain language and receive answers grounded in its institutional context, not generic model output. Governed self-service ensures role-based data access is enforced automatically.
Outcome: The activation gap between knowing and acting is now measurably narrower across the bank's entire international operations. A secure, governed, and scalable conversational analytics capability, already a repeatable blueprint the bank is extending to additional domains, is now live across one of Europe's most complex banking environments. - Production LLM-powered institutional knowledge for a major Asia Pacific retail bank
Challenge: This retail bank had accumulated decades of institutional knowledge in its data, systems, and people, but wanted to make that intelligence accessible beyond the specialist teams who could query it directly. The goal was to move from a model where answers required technical expertise to one where any team, in any part of the business, could access the organization's enterprise intelligence in real time.
AI solution: Teradata worked with the bank to build and deploy in-database AI and ML pipelines using SQL. By mid-engagement, the focus shifted from optimization to opportunity: a production LLM-powered chatbot, embedded directly in the retail banking environment, providing secure and live access to the organization's institutional memory via Teradata's MCP server. The Teradata platform ensured the LLM was grounded in trusted, governed data that is scalable and can deliver real impact.
Outcome: The results were faster responses and measurably higher productivity with teams freed up to focus on higher-value work. The bank is now preparing to scale this capability enterprise-wide so users can activate institutional memory across every business unit.
Why it matters
Financial services institutions operate some of the most demanding data environments in the world: decades of customer history, real-time transaction streams, cross-border regulatory requirements, and a zero-tolerance threshold for error in fraud, credit, and compliance. The speed at which institutional intelligence can be turned into action is increasingly what separates industry leaders from those that fall behind.
Teradata AI Services are purpose-built to close that gap by combining expert methodology with the Teradata platform in a sprint-based delivery model. For global financial institutions, that means a structured, accelerated path from proof of concept to production, without compromising the governance, auditability, and trust their regulators and customers expect.
Executive perspective
"Financial institutions hold vast amounts of the world's richest and most consequential enterprise data, yet too often that knowledge isn't put to work when it matters most. These customer engagements demonstrate what's possible when organizations can activate that intelligence with AI across the enterprise: from stopping fraud in real time to making institutional knowledge more accessible and enabling natural-language analytics at global scale. The result is faster, more informed decision-making and measurable business outcomes."
— Mike Hutchinson, Chief Operating Officer, Teradata
About Teradata
Teradata empowers enterprises to turn intelligence into autonomous action, grounding AI agents in deep business context and trusted data. As AI agents multiply, Teradata is the context foundation, governance layer, and performance backbone that companies need now. The Teradata Autonomous Knowledge Platform puts AI into production across cloud, on-premises, and hybrid environments.
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