AI in Financial Services Deloitte Insights
Making purposeful decisions with an explicit strategy (for example, about where value will really be created) is a hallmark of successful scale efforts. We recently conducted a review of gen AI use by 16 of the largest financial institutions across Europe and the United States, collectively representing nearly $26 trillion in assets. Our review showed that more than 50 percent of the businesses studied have adopted a more centrally led organization for gen AI, even in cases where their usual setup for data and analytics is relatively decentralized. This centralization is likely to be temporary, with the structure becoming more decentralized as use of the new technology matures. Eventually, businesses might find it beneficial to let individual functions prioritize gen AI activities according to their needs. We have observed that the majority of financial institutions making the most of gen AI are using a more centrally led operating model for the technology, even if other parts of the enterprise are more decentralized.
- This enables more personalized interactions, faster and more accurate customer support, credit scoring refinements and innovative products and services.
- Business units that do their own thing on gen AI run the risk of lacking the knowledge and best practices that can come from a more centralized approach.
- Understand what’s top of mind for financial services companies as they decide where to host their AI infrastructure.
- Learn how to transform your essential finance processes with trusted data, AI insights and automation.
Job Displacement And Regulatory Challenges
While smartphones took many years to move banking to a more digital destination—consider that mobile banking only recently overtook the web as the primary customer engagement channel in the United States6Based on Finalta by McKinsey analysis, 2023. Goldman Sachs, for example, is reportedly using an AI-based tool to automate test generation, which had been a manual, highly labor-intensive process.7Isabelle Bousquette, “Goldman Sachs CIO tests generative AI,” Wall Street Journal, top 13 bookkeeping and accounting tips for small business owners May 2, 2023. And Citigroup recently used gen AI to assess the impact of new US capital rules.8Katherine Doherty, “Citi used generative AI to read 1,089 pages of new capital rules,” Bloomberg, October 27, 2023.
AI In Financial Planning And Advisory Services
Moreover, the reliance on AI algorithms raises questions about transparency and accountability. It is crucial for financial advisors to understand the underlying mechanisms of AI tools to explain their recommendations to clients clearly. Additionally, there is a need for continuous learning and adaptation as AI technology evolves to stay ahead of potential biases and inaccuracies in AI-driven decisions. Gen AI, along with its boost to productivity, also presents new risks (see sidebar “A unique set of risks”). Risk management for gen AI remains in the early stages for financial institutions—we have seen little consistency in how most are approaching the issue. Sooner rather than later, however, banks will need to redesign their risk- and model-governance frameworks and develop new sets of controls.
Despite its numerous benefits, the integration of AI in financial services also presents several challenges and ethical considerations. Data privacy is a significant concern, as AI systems require access to vast amounts of personal and financial data to function effectively. Ensuring that this data is securely stored and processed is paramount to maintaining client trust. The financial services industry finds itself undergoing a transformation driven by the rapid evolution of technology, with AI spearheading this revolution. As this monumental shift unfolds, financial services professionals grapple with both the promising advantages and the challenges that come hand-in-hand with this technology.
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Tim Coy is the research manager for the Commercial Real Estate industry within Deloitte’s Center for Financial Services who’s based out of New York City. Prior to Deloitte, he served as a lead researcher for commercial real estate brokerages CBRE and Cushman & Wakefield. You should consult with a licensed professional for advice concerning your specific situation. Undoubtedly, AI’s advancements are reshaping customer experiences and industry landscapes at an unprecedented pace. Our company’s CEO and CTO, Mark J Barrenechea, put it best when he was describing this swift evolution, remarking in an interview for CIO Views, “We have never moved so fast, yet we will never move this slowly again.” Naturally, banks encounter distinct regulatory oversight, concerning issues such as model interpretability and unbiased decision making, that must be comprehensively tackled before scaling any the vertical balance sheet application.
The operating model with the best results
Strengthening confidence and trust among financial advisors and clients will be especially important as economic conditions fluctuate. Gen AI certainly has the potential to create significant value for banks and other financial institutions by improving their productivity. But scaling up is always hard, and it’s still unclear how effectively banks will bring gen AI solutions to market and persuade employees and customers to fully embrace them. Only by following a plan that engages all of the relevant hurdles, complications, and opportunities will banks tap the enormous promise of gen AI long into the future. Banks and other financial institutions can take different approaches to how they set up their gen AI operating models, ranging from the highly centralized to the highly decentralized. AI is also transforming financial planning and advisory services by providing advisors with advanced tools to better understand their clients’ needs and goals.
This view can cover everything from highly transformative business model changes to more tactical economic improvements based on niche productivity initiatives. For example, leaders at a wealth management firm recognized the potential for gen AI to change how to deliver advice to clients, and how it could influence the wider industry ecosystem of operating platforms, relationships, partnerships, and economics. As a result, the institution is taking a more adaptive view of where to place its AI bets and how much to invest. Fintechs remain at the forefront of harnessing gen AI and many of their use cases and solutions are impacting financial services. For example, Synthesia utilizes an AI platform to create high-quality video and voiceover content tailored for financial services, while Deriskly provides AI software aimed at optimizing compliance in financial promotions and communications.
Clear career development and advancement opportunities—and work that has meaning and value—matter a lot to the average tech practitioner. Many fintechs will play an enabling role by helping to democratize gen AI’s capabilities for mid-market and smaller financial institutions, allowing these firms to leverage gen AI in a way that currently is only available to the paycheck protection program largest FS players in the world. Proactive governance can drive responsible, ethical and transparent AI usage, which is critical as financial institutions handle vast amounts of sensitive data.
These robo-advisors consider factors such as market trends, economic indicators and individual client preferences to create tailored investment plans. The center is staffed by a group of professionals with a wide array of in-depth industry experiences as well as cutting-edge research and analytical skills. Through our research, roundtables, and other forms of engagement, we seek to be a trusted source for relevant, timely, and reliable insights. In my practice, I’ve utilized AI tools to monitor client accounts for unusual activity. For example, a client who frequently traveled internationally faced the risk of unauthorized transactions on his credit cards. By implementing an AI-driven monitoring system, we were able to detect and respond to a fraudulent attempt almost immediately, preventing significant financial loss.