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AI in Financial Services

Definition

Financial institutions use AI for fraud detection, risk analysis, customer service, document processing, research and operational automation, with strong model-risk and governance requirements.

Where financial institutions use AI

Banks, insurers and investment firms use AI for fraud detection, credit and risk analysis, customer service, document processing, anti-money-laundering support, research and operational automation.

Why models face stricter controls

Financial decisions can affect access to credit, money movement and regulated reporting. Institutions therefore need validation, model-risk management, explainability appropriate to the use case and human oversight for consequential decisions.

Generative AI in finance

LLMs are increasingly used to search policies, summarize research and draft communications. They are usually connected to approved internal data rather than trusted as standalone sources of current financial truth.

Related terms, defined

Robotics, Finance & Governance Asset Tokenization Asset tokenization represents claims on financial or physical assets as digital tokens on programmable platforms. BIS work treats tokenization as a change in representation, transfer and settlement infrastructure—not as a form of artificial intelligence. Robotics, Finance & Governance AI and Tokenized Financial Assets AI and tokenization are distinct technologies that can interact. AI can support monitoring, compliance, analysis or operational automation around tokenized markets; tokenization itself is a ledger and market-structure technology. Robotics, Finance & Governance The NIST AI Risk Management Framework The NIST AI Risk Management Framework is a voluntary framework organized around governing, mapping, measuring and managing AI risk. NIST's Generative AI Profile extends that framework with risks and suggested actions specific to generative systems. Robotics, Finance & Governance AI Governance and Regulation AI governance is the set of policies, ownership, controls, documentation, evaluation and monitoring used to manage AI systems; regulation is one external component of that broader governance system. Robotics, Finance & Governance AI Roadmap 2026: Agents, Multimodality, Efficiency and Robotics As of 2026, first-party releases and independent measurement show several major directions: more tool-using and agentic systems, stronger multimodality, smaller efficient models, longer context, model routing, open-weight competition and closer integration between foundation models and robotics.

Reference guide and primary sources

Wikipedia is used here as a terminology and history reference guide. Current model versions, institutional statistics and product-specific claims are also linked to first-party or institutional sources because those details can change faster than encyclopedia articles.