Generative AI: Managing unreliability in financial services

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On-Demand

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Online

Generative AI: Managing unreliability in financial services

What are the key challenges for financial institutions aiming to deploy AI tools in customer facing positions? How can institutions reduce risks associated to AI unreliability?

  • How can financial institutions leverage generative AI without increasing their risk profile?
  • Why is the reliability of generative AI models a concern for banks?
  • What benefits can financial organisations expect to receive from well managed generative AI solutions?

Artificial Intelligence (AI) has recently surged as a leading topic of interest across the globe thanks to the influx of accessible AI tools like ChatGPT. The sudden interest is bolstering financial institutions’ interest in investing in the solutions that generative AI models offer. However, generative AI tools are not 100% reliable in the information they provide, and banks cannot risk offering such tools in customer-facing positions.

Misrepresentation, inaccuracy and bias are key concerns of unchecked AI, so firms must ensure they are taking the necessary steps and preventative measures to mitigate these risks. If developed correctly and reliably, AI tools can shape the future of enhanced customer experience and catalyse financial institutions’ digital transformation.

The future of generative and conversational AI can minimise the amount of work involved in customer experience by creating assistant bots that can respond to queries and provide automatic translation. To build and deploy ethical and precise AI models, financial organisations must concentrate on implementing robust prevention measures, and should consider working with technology providers which can assist these efforts.

Sign up for this Finextra webinar, hosted in association with boost.ai, to join our panel of industry experts who will explore the challenges of deploying generative AI products.

 

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