The use of artificial intelligence (AI) in the financial services sector is on the rise, with many firms looking to AI to improve productivity and operational efficiency. However, according to Edward J Achtner, head of generative AI at HSBC, many companies are failing to deliver tangible results despite making bold claims about the benefits of AI.
Speaking at the CogX Global Leadership Summit in London, Achtner highlighted how HSBC has embraced AI technology, with over 550 use cases across its business lines. These range from using machine learning tools to combat money laundering and fraud to supporting knowledge workers with generative AI systems.
One key partnership HSBC has is with Google, focusing on using AI to enhance anti-money laundering and fraud detection. Achtner emphasized the importance of approaching the risks associated with generative AI differently from other types of AI, as it presents both significant opportunities for productivity gains and new risks.
Other leaders in the financial services sector, such as Sebastian Siemiatkowski, CEO of Klarna, have also touted the benefits of AI in improving efficiency. Klarna has used AI to offset losses in productivity resulting from a reduction in its workforce, with plans to further reduce headcount. However, Nathalie Oestmann of NV Ltd cautioned against viewing AI-driven workforce reductions as a purely negative development, suggesting that companies like Klarna are incorporating AI to become more valuable.
Despite the potential of AI to transform the financial services industry, leaders like Ranil Boteju of Lloyds Banking Group stress the importance of proceeding with caution. Lloyds is exploring the use of AI in automating back-office functions, improving customer service, and generating responses to client queries. Boteju highlighted the need for guardrails to be in place before scaling AI tools to ensure customer protection.
Overall, the consensus among AI leaders in the financial services sector is that while AI holds great promise for improving efficiency and productivity, careful implementation and ongoing learning are essential. By embracing AI technology responsibly and continuously evolving their practices, financial firms can adapt to the new AI era and drive positive change in the industry. In a recent interview with CNBC, Bahadir Yilmaz, chief analytics officer of ING, shared his thoughts on the impact of AI in the banking sector. Yilmaz stated that while ING recognizes the potential of AI, the firm is taking a more cautious approach compared to other companies like Klarna. He emphasized that ING is primarily using AI in its global contact centers and for software engineering purposes.
Yilmaz explained that ING does not feel the need to brand itself as an “AI-driven bank” and believes that AI is a powerful tool that can be used selectively to solve specific problems. He highlighted that not all processes in banking require AI and that it is not necessary to apply AI to every aspect of the business.
Johan Tjarnberg, CEO of Trustly, a Swedish online payments firm, also shared his views on AI in payments. Tjarnberg acknowledged the potential of AI as a technology lever in the payments industry but noted that Trustly is focusing more on the fundamentals of AI rather than on revolutionary changes like AI-led customer service.
One area where Trustly is leveraging AI to enhance customer experience is in subscription services. The company is developing an “intelligent charging mechanism” that aims to optimize the timing of payments for subscription platform users based on their financial history. Tjarnberg mentioned that Trustly has seen a 5-10% improvement in efficiency as a result of implementing AI within the organization.
Overall, both Yilmaz and Tjarnberg highlighted the significant impact of AI in the financial sector but emphasized the importance of a strategic and measured approach to its implementation. While AI has the potential to revolutionize banking and payments, companies like ING and Trustly are focused on leveraging AI in targeted areas to enhance customer experience and operational efficiency.
