During the Google Cloud Next 2024 event, I had the opportunity to interview Zac Maufe, the executive at Google Cloud overseeing the financial services industry and the use of generative AI in this sector. Zac pointed out that the use of generative AI in the financial sector mostly serves as a tool to enhance employee efficiency rather than a tool directly used by customers. The two clear use cases are: 1) as a data search tool for customer support staff to quickly access various information or analysts to generate reports from existing data within the organization. 2) as a task delegation tool, for example, when support staff encounter complex customer issues that need to be escalated, generative AI can summarize all the information that frontline staff have gathered from the customers, making the delegation process much quicker.
He discussed the importance of monitoring the use of artificial intelligence in that generally, financial businesses must be able to explain their service strategies. For instance, in cases where exceptions are made for certain customers in terms of penalties, they must be able to justify who gets exempted and who doesn’t. Historically, Google has developed its own AML AI system for money laundering prevention, with the most challenging part of this system being the ability to explain which transactions are categorized as money laundering risks. Similarly, in the case of generative AI, there is a need for the capability to explain the results. However, the tools for explaining generative AI outcomes are still incomplete and require further development.
Regarding the use of generative AI as a tool for call centers, the question arises whether it will increase efficiency to the point of reducing human labor. Zac mentioned that it is still in the initial stages of implementation in this group. While the tool offers significant benefits, employees may end up spending more time interacting with customers. Back in the day, Zac himself worked as an analyst, and part of his job involved reducing questions because answering each question took up a lot of time. He believes that the use of generative AI will increase employee productivity but whether it will increase output remains to be seen.
A report from Klarna mentioned using chatbots to directly answer customer queries, replacing up to 700 employees. On the other hand, Stanford Medicine reported that while generative AI did not reduce working hours for medical staff, it did help reduce their fatigue.
Screenshots of the assistance system by Cymbal Fintech, a hypothetical company, demonstrate the utilization of AI assistants at Google Cloud Next event.
TLDR: The use of generative AI in financial services focuses on enhancing employee efficiency, explaining service strategies, and improving productivity, but its full implementation and development for explaining outcomes are ongoing. Its integration in call centers has shown potential to replace employees in customer query handling, while its impact on work hours and fatigue reduction varies across different industries like healthcare.
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