Exploring the Future of Banking with Generative AI & our Latest Paper

In our fast-evolving digital world, is the financial sector standing on the cusp of a revolutionary transformation? Is generative AI a profound shift that will redefine how banks operate, compete, and serve their customers?

Two of my colleagues, Philippe S. and Vishal Gupta recently wrote and published our latest Samlink Advisory Services white paper - “Generative AI in Banking: A Must for Compliance and Growth”

I must admit to having some strong and personal thoughts and perspectives on GenAI, and in general they are all positive. But in discussion with banks I always say to move slow and focused to ensure they get the best from this shift - and to always think about compliance first!

The banking industry is no stranger to regulatory upheavals. However, the current wave of regulations, driven by the European Commission is almost unprecedented. These regulations aim to create a secure and competitive financial environment but also impose significant compliance burdens on banks. The interplay between these regulations and the adoption of Generative AI is a key focus area.

Generative AI can help banks navigate this regulatory landscape by enhancing productivity and reducing compliance costs. For instance, AI-driven systems can automate complex regulatory reporting, ensuring accuracy and timeliness. But more importantly, AI can help banks turn compliance into a competitive advantage by enabling more agile and efficient operations.

But there are substantial promises getting seen with the adoption of GenAI, which is wider than just the compliance.

In the paper Philippe and Vishal highlight several compelling statistics underscoring the potential impact of Generative AI in banking:

- Generative AI can boost productivity by 14% on average.

- AI tools can help developers complete tasks 56% faster.

- AI-driven improvements in mid and back-office operations could reduce costs by up to 12%.

These numbers point to a future where AI is not merely an adjunct to human capabilities but a core driver of business value and growth.

The Potential Value of Generative AI

While predictive AI has already proven its worth in areas like fraud detection and risk assessment, Generative AI takes things a step further. It can create new content, such as code, reports, and even customer interactions, based on learned patterns. This opens up a plethora of applications, from automating customer service to generating personalized financial advice.

Consider the example of code generation. Generative AI can not only identify and fix bugs but also generate new code snippets, thus accelerating development cycles and reducing human errors. Similarly, in customer service, AI-driven chatbots can provide real-time, personalized responses, enhancing customer satisfaction and loyalty - it feels like almost yesterday I was presenting on the future of conversational AI driving key customer interactions as if it was something we would have far into the future. I think this train has accelerated substantially, what do you think?

The Future of Generative AI in Banking

As we embrace Generative AI, it's crucial to address the inherent challenges and risks. Transparency, accountability, data quality, and algorithmic maturity are some of the key concerns that banks need to manage. The regulatory environment, particularly the new AI Act here in Europe, will play a pivotal role in shaping how banks deploy and use AI technologies going forward.

However, I really think the future looks promising. As regulatory frameworks evolve to become more supportive of AI adoption, banks will find themselves in a more secure and standardized ecosystem. This will not only mitigate risks but also foster innovation and competition, where the consumer will be the winner.

But the successful deployment of Generative AI requires a robust ecosystem involving technology providers, data sources, regulators, customers, and partners. Banks need to carefully select their AI partners, ensure data governance, and comply with regulatory standards. Moreover, engaging with customers to understand their needs and feedback will be crucial for developing AI solutions that truly add value.

One of the strategic decisions banks face is whether to use private or public Large Language Models (LLMs). Each option has its pros and cons. Private LLMs offer better data control and customization but come with higher costs and complexity. Public LLMs, on the other hand, are more accessible and cost-effective but pose potential data privacy and security risks. A hybrid approach, leveraging the strengths of both, might be the way forward.

Shaping the Future Together

As we stand at the brink of this exciting transformation, I encourage you to think about the possibilities and challenges that Generative AI brings to the banking sector. How can we leverage this technology to enhance customer experiences, improve operational efficiency, and stay ahead of the competition? What steps can we take to ensure ethical and responsible AI usage?

As is now traditional when we publish a white paper like this, we at Samlink – A Kyndryl Company will be hosting a breakfast seminar, and I invite you to save the date and look out for the registration link.

What? Samlink’s Exclusive Breakfast Seminar on Generative AI in Banking

Where? GLO Hotel Sello, Espoo, Finland

When? September 11th 2024 at 8:30 AM

I invite you to share your thoughts, predictions, and insights on the growth of GenAI in banking. And feel free to reach out and join the conversation.