In the financial services industry, there has been a long-standing effort to automate various processes, including back-end compliance and customer service. However, the emergence of generative artificial intelligence brings both new possibilities and potential challenges for financial services firms. According to Saby Roy, a technology consulting partner at EY, many organizations are currently exploring ways to put AI into practical use.
Applications of AI in Financial Services
AI is already being used to enhance the customer experience in financial services. While consumers are familiar with basic chatbots on bank and retailer websites, these chatbots have limited functionality. Financial institutions hope that generative AI can replace these systems with alternatives that can respond to complex requests, learn how to cater to specific customer needs, and improve over time.
Rav Hayer, a managing director at Alvarez & Marsal’s digital practice, mentions the increasing interest in using generative AI in chat channels for customer service. Conversational finance is a popular topic of discussion among clients.
Another area where AI has gained traction is lending. AI systems are employed to analyze documentation and expedite the assessment of a consumer’s creditworthiness for products like mortgages. Stuart Cheetham, CEO of MPowered Mortgages, explains that they have 15 live AI models on their platform, each performing different functions to evaluate statements and make informed decisions.
However, Cheetham emphasizes that their system is not fully automated, and human involvement is still necessary for making final decisions. Consumer protections under the General Data Protection Regulation prevent the use of opaque AI systems in decision-making processes.
On the other hand, AI is also being utilized in the investment field, enabling fund managers to convert raw data into actionable insights for smart investment decisions. Hal Reynolds, co-chief investment officer at Los Angeles Capital, praises AI for providing a more forward-looking view and improving information understanding.
Financial firms are also harnessing generative AI to combat financial crime, especially in the domains of anti-money laundering and “know your customer” protocols. The applications of AI in this area are extensive but crucial.
Gains from the Use of AI
AI, according to Guðmundur Kristjánsson, founder and CEO of Lucinity, offers significant time savings. Lucinity uses AI to support bank staff in detecting money laundering and illicit activities. Their system, Luci, quickly processes transaction alerts and provides text summaries for agents to assess. This accelerates the resolution of cases and enables them to address more potential issues.
Kristjánsson acknowledges the rapid pace of AI innovation and the growing accessibility of AI tools. Lucinity, a small fintech company, is able to reap the benefits of AI thanks to these advancements. Larger players in the industry, such as Mastercard, are also utilizing AI to combat fraud. Mastercard’s new Consumer Fraud Risk system provides banks with real-time scores to identify fraudulent transactions on the UK’s Faster Payments network.
Risks from the Use of AI
While AI offers numerous benefits, experts express concerns about the potential risks it poses, particularly in enabling financial crime. Hayer highlights the possibility of fraudsters leveraging generative AI to enhance their attempts at data and money theft, such as through better impersonation tactics.
Past instances of automated tools have faced controversy due to failures, like wrongful arrests caused by limitations in facial recognition technology. For Hayer, it is crucial for institutions to carefully consider the risks as well as the opportunities presented by AI. Governance and risk management must accompany AI implementation to avoid unintended consequences and destructive outcomes.
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