Banking’s Generative AI Future | Part 1 | Mambu’s Banking Insights for Growth

Want to know how AI can augment your bank and whether or not it will steal your job?

In this edition of Banking Insights for Growth, produced in partnership with Mambu, our expert panel discusses the latest myths around AI, as well as current use cases and risks that Generative AI brings to the financial services industry. It’s the topic everyone’s talking about and in part one of two, we’re delivering actionable insights for you to take away.

For anyone looking to gain more insight on this topic, Mambu have also created a 6 step insider’s checklist of considerations for any financial institution planning to, or thinking about implementing AI tools within their organisation. Based on insights from this very interview it’s a definitive resource that will help guide all important decisions in this area. Head to their website to read the full thing.

Read on for an in depth overview of what was discussed.

Countering the myths around AI

In Mambu’s Banking Insights for Growth series we aim to deliver actionable insights on the latest trends set to transform banking. To do that of course, we needed a panel of experts who can speak directly from their experience in the field. Fortunately, we have just that.

In this episode we have Richard Kalas, Client Solutions Director at GFT, Kamalesh Rangasayee, Director of Security Engineering and Operations at Mambu, Annette Harris, Head of Financial Services from Microsoft Netherlands, and Kerim Bertrand, Senior VP Growth for Western Europe at VeriPark.

A big focus was countering some of the prevailing myths around AI and Generative AI more specifically. Kalas kicked us off by addressing the notion that large language models (LLMs) are automatically equipped to solve value-generating challenges independently. In reality they require a robust software development lifecycle that then needs to be implemented effectively, indicating that AI’s value lies in its integration within a structured development framework. Rangasayee echoes this, adding that prompt-based answers from predictive AI do not reflect true understanding, as these models predict rather than comprehend intent.

Evidently, all of this requires a skilled team of engineers, data scientists, compliance officers and more, hopefully easing the concern that AI is here to take our jobs, something Harris was quick to pick up on. Instead, she posits that AI will free humans from mundane tasks, enabling them to focus on higher-level, strategic activities.

Streamlining tasks and augmenting efficiency

This concept of collaborative intelligence—where AI and humans join forces—is central to realising AI’s full potential.

Comparisons were made between the current developments and the rise of ATMs, which enhanced branch banking rather than rendering it obsolete. This adaptability and leveraging of AI for improvement is crucial for the banking sector.

Ultimately, the panel expressed excitement about AI’s potential to streamline tasks and augment employee efficiency. The ultimate goal, Bertrand argued, is to enhance customer experience, where employees, empowered by AI, deliver superior service. This dual approach – combining human empathy with AI efficiency – should create a comprehensive service model.

The question is what are the practical applications of AI in banking? Some are being revealed already. Our experts suggest that it offers significant opportunities in code verification and risk reduction through data analysis. However, Harris also pointed out that we are only beginning to explore AI’s potential and we have to do it responsibly.

The importance of responsible AI

Responsible AI is a critical topic that gets brought up here. Harris emphasised the need for industry collaboration to deliver safe, responsible AI products and establishing guardrails is essential to ensure ethical AI deployment.

In that vein, Kalas discusses improving customer service through multiple control planes, preventing AI from making difficult decisions autonomously. This layered approach ensures that human oversight remains integral to the decision-making process. Then of course, there’s the upcoming EU AI Act, which will be in force from 2nd August 2024, and which Rangasayee stresses companies need to be prepared for if they aren’t already. After all, compliance is not just about adhering to laws but also positioning businesses to leverage AI effectively.

Another important and prescient point in this conversation concerns human intuition and empathetic decision-making. In other words, AI can handle tasks that don’t require intuition, while humans manage more nuanced decisions. This delineation is vital to avoid discrimination and ensure fair treatment.

There’s some great stuff here and plenty more where that came from! Be sure to stay tuned right here for Part 2 of this bumper conversation on AI and even more from Mambu’s Banking Insights for Growth series, coming soon.