AI’s Transformative Role in Finance: Insights from Industry Experts

Generative AI has taken center stage in discussions about its potential to reshape the financial industry. While many hail it as a superpowered technology stack capable of revolutionizing finance, a recent panel at the AI in Financial Services Forum in London offered a different perspective, as highlighted in Fintech Global News. The panel, titled ‘Revolutionising Financial Services,’ was chaired by Viktoria Ivan, a senior data scientist at Ebury, and featured notable figures like Andrew Allright from State Street EMEA, Tim Mason from Deutsche Bank, Dion Kraanen from M&G, and Ash Garner from Tomoro.

During their 45-minute discussion, the panel explored how technology is reshaping financial services, with a particular focus on the transformative potential of generative AI.

Generative AI has garnered immense attention over the past year, with businesses worldwide eager to integrate it into their operations. A Salesforce report revealed that 61% of workers are either using generative AI or have plans to implement it. One exciting use case that has gained traction is its ability to enhance customer-facing services. According to the same Salesforce report, 68% of respondents believe that generative AI can improve customer service.

Ash Garner from Tomoro shared a compelling example from an Australian bank that used generative AI to personalize customer communications. Instead of sending standardized messages, the bank employed a large language model to tailor messages based on individual spending habits, personality, and location. The result? A remarkable 100-150% increase in customer engagement with educational content.

Dion Kraanen from M&G also emphasized the importance of personalization with generative AI, especially in the context of investment apps. He highlighted the potential for generative AI to engage users in meaningful conversations about their preferences, such as sustainability and ESG factors, enabling deeper personalization beyond simple checkbox forms.

Deutsche Bank’s Tim Mason discussed the various use cases his firm is exploring with generative AI, including improving chatbots for both retail and corporate clients. Understanding and interpreting the vast volume of emails and documents received by the bank each year has become more efficient thanks to language models, leading to happier customers.

State Street’s Andrew Allright outlined two primary use cases for generative AI at his firm: chatbot models for client communication and interactive reports that provide users with an overview of operations. These applications enhance communication and decision-making for global companies.

The panel also delved into the internal benefits of generative AI. When asked about use cases for reducing costs and improving processes, panelists provided valuable insights. Tim Mason stressed the importance of using language models to understand unstructured content, such as emails and documents, which can significantly streamline workflows. Ash Garner highlighted Tomoro.ai’s work in helping clients assess unstructured data, transforming it into coherent information and knowledge graphs.

Dion Kraanen envisioned the next level of generative AI, where it can synthesize data sets, providing unique insights that users couldn’t gather themselves. However, he noted that this capability requires a combination of large language models and other machine learning algorithms working in harmony.

The panelists agreed that generative AI excels as an orchestrator of other systems, rather than as a standalone solution. It can effectively coordinate predictive machine learning models, CRM solutions, and knowledge bases, enhancing organizational processes.

Despite its potential, generative AI is not without challenges. Tim Mason expressed concerns about the technology’s misuse, particularly in customer chat, where it might produce inappropriate language or tones. Hallucinations, where the AI generates false or fabricated information, pose a significant risk to trust and brand reputation. Proper training and tone assessment are essential to mitigate these risks.

The AI in Financial Services Forum provided valuable insights into the transformative role of generative AI in finance. While it holds immense promise for enhancing customer experiences and streamlining internal processes, organizations must navigate challenges to harness its full potential responsibly.