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Generative AI: managing unreliability in financial services

Last updated 10 April 2024
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Recently, we took part in a webinar entitled ‘Generative AI: Managing Unreliability in Financial Services’ in partnership with Finextra. Boost.ai’s Head of Financial Services, Grete Øvrebø, was joined by Nitendra Rajput, Senior Vice President, AI Garage at Mastercard, and Yannick Lallement, Chief AI Officer at Scotiabank, as well as moderator and Head of Research at Finextra, Gary Wright.

The webinar offered a variety of insightful moments, and we wanted to share some of the key points with you in this blog. Here are our key takeaways from a fascinating discussion on the future of CX in financial services:

Understanding Generative AI

Since the launch of ChatGPT, the profile of generative AI has grown exponentially across all sectors, including in the financial services industry. Its potential impact and capabilities have sparked important discussions on how to leverage its power whilst maintaining control and using it responsibly.

Generative AI represents the second wave of AI, with the first wave focusing on building initial AI algorithms. The power of generative AI lies in its ability to analyze digital footprints, enabling a better understanding of customers. Nitendra used the analogy of a footprint in the sand - from just one set of footprints, generative AI can work out the age, height and weight of a person, as well as the speed at which they are traveling! The same can be said for the way customers interact with brands online, leaving digital footprints as they navigate websites. By understanding these digital footprints, financial institutions can gain insights into customer behavior, preferences, and needs.

Concerns and Mitigation Strategies

Maintaining data privacy and security is a primary concern for any institution operating in the financial ecosystem, as is the risk of misrepresentation or inaccuracy, causing problems for customers. It was emphasized that data privacy and security challenges are not unique to generative AI but have been present arguably since the advent of cloud technology. The difference with AI is the concerns around accuracy, but the underlying factors remain the same. Trusting the vendor and taking the time to do your due diligence is crucial in addressing these concerns.

The Importance of Humans in the Loop

A common theme throughout the discussion was the need for a human in the loop. By having a human element in the AI process, organizations can ensure that mistakes are detected, potential risks are mitigated, and customer inquiries are handled with the combined efficiency of human and machine. Human agents can focus on higher-value inquiries and sensitive cases, while generative AI assists with repetitive tasks and augments customer service. The most successful use cases are those that highlight the respective strengths of humans and AI and where people are working hand in hand with automation.

The Need for a Holistic Approach

Financial organizations possess different pieces of the overall puzzle when it comes to understanding their customers. No single entity has access to the entire customer picture. Generative AI helps fill these gaps by generating insights and assumptions from customers' digital footprints. This creates a more comprehensive and enriched customer profile, enabling organizations to better serve their customers' needs and build lasting relationships.

Building Trust and Addressing Governance

Building trust with consumers is a crucial aspect of deploying generative AI in financial services. Consumers need to understand the benefits of AI and have confidence in how their data is managed. This requires a collective effort involving AI experts, regulators, and government bodies to establish a framework and governance structure that promotes industry trust. At the moment, there are a lot of unknowns around AI, so education and knowledge sharing are critical.

Closing thoughts

In her closing remarks, Grete noted that ‘if ChatGPT is a hammer, everyone seems to think the world is made out of nails’. It is a powerful tool, but we should use it together with other technologies to get the most value out of it. This is true for generative AI as a whole, it presents both opportunities and challenges for the financial services industry. It is important for organizations to embrace this technology responsibly, with a focus on data privacy, accuracy, and the role of human agents. By addressing concerns, establishing governance frameworks, and maximizing the potential of generative AI, financial institutions can harness its power to drive innovation, enhance customer experiences, and achieve digital transformation.

Find out how boost.ai can help you harness the power of generative AI through virtual agents by getting in touch today!

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