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Financial services professionals are exploring the use of generative AI technologies to help them be more effective in their jobs.
Generative AI technologies—such as intelligent chatbots, large language models, and prompt engineering tools—have clear applications in financial services. Generative AI can help banks, wealth management firms, and other financial services firms automate many reporting tasks, analyze vast document databases more rapidly, and speed development of programming code and complex content deliverables. When incorporated into digital assistants, chatbots, and self-service applications, the technology can also provide a user-friendly natural-language front end for customer engagement, fraud prevention, credit risk assessment, regulatory compliance, and other mission-critical applications.
However, financial services firms must make sure that they don’t skimp on implementing the necessary guardrails to mitigate the business risks associated with generative AI. James Kobielus, TDWI senior research director, will discuss the opportunities that generative AI presents for financial services firms while providing guidance for implementing guardrails in several key areas:
- Maintaining high predictive accuracy on generative AI models that are deployed into production applications in financial services
- Training generative AI models on high-quality financial services data while protecting intellectual propriety and customer privacy
- Providing a subject-matter-expert “human in the loop” on all production generative applications to verify the trustworthiness of AI-generated answers
- Eliminating hallucinations, toxicity, bias, and other issues with generative AI model outputs that are deployed into production applications
- Ensuring that financial services firms build, train, deploy, and manage generative AI applications in full compliance with transparency, explainability, and other requirements in applicable regulatory mandates