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Connor Heaton, SRM’s AI Visionary, Talks About the Game-Changing Impact of AI in Financial Services

Hello Connor, could you share your journey into AI and what led you to your current role at SRM?

When considering my path to education and career, AI was one of the big domains (alongside biotechnology/genetics) which looked like they had the potential to transform society in my lifetime. I studied cognitive science and decision theory in university in part to stay close to developments in AI, and I steered my consulting career towards AI and automation during my time at Deloitte. I helped to build and scale Deloitte’s federal automation practice, and SRM brought me on initially to do much the same thing for them, which put me in a perfect position to expand SRM’s AI practice to focus on LLMs (large language models) and other transformer-based AI technologies when ChatGPT’s launch kicked off the current wave of interest and investment in the space.


Read This Article: FinTech Interview with Connor Heaton


Generative AI is Rapidly Transforming Technology – What Does This Mean for Financial Services?

Generative AI is reshaping the technological landscape, and its influence on financial services is profound. While AI has been a part of finance for some time, the advent of generative models like ChatGPT marks a transformative leap, comparable to the shift from mainframes to PCs or from flip phones to smartphones. Large Language Models (LLMs) are democratizing advanced AI capabilities, making them more cost-effective, accessible, and user-friendly. This is unlocking a wide range of automatable tasks and laying the groundwork for a dynamic ecosystem of AI-driven solutions.

For financial institutions, LLMs are already delivering significant value across various domains, including software development, marketing, customer support, internal operations, and knowledge management. Over time, the influence of AI is expected to revolutionize nearly every role within financial institutions. Job responsibilities will evolve to leverage AI tools, with employees transitioning into roles that involve supervising and collaborating with AI systems.

Challenges and Opportunities with Generative AI in finance

Financial institutions have long relied on AI for diverse tasks, but generative AI, particularly LLMs, introduces new opportunities and challenges. Key opportunities include access to advanced AI capabilities that enhance speed and efficiency. For example, companies like Klarna are using AI in their contact centers to achieve the productivity equivalent of hundreds of agents.

Generative AI also enables innovative applications that are relatively new to the financial sector, particularly for community financial institutions. These include:

  • Scaled personalization and marketing
  • Intranet and knowledge search through conversational interfaces
  • Image identification and data extraction
  • Automated workflow documentation

However, integrating generative AI into finance comes with challenges. For instance, the risk of "hallucinations"—AI producing confident yet incorrect outputs—poses compliance and reputational risks without proper oversight. Additional concerns include data privacy vulnerabilities, AI bias, and navigating a constantly evolving regulatory environment, all of which require strong governance frameworks.

Moreover, questions remain about the broader impact of AI on jobs and the extent to which financial processes and products will need to be reimagined to maximize the benefits of this technology.

Generative AI represents both an exciting opportunity and a complex challenge for financial institutions as they work to harness its potential responsibly.

Read This Article Too:

Tech Bloat in Financial Services: A Roadmap to Efficiency and Innovation



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