Banks with fewer AI experts on staff will need to enhance their capabilities through some mix of training and recruiting—not a small task. Financial services have made considerable progress adopting gen AI in the last two years. While there’s been a sizable focus on efficiency and cost optimization thus far, many FS CIOs are eager to deliver top line growth. To do so, they’ll need to work closely with the business to consider how gen AI can lead to new ways of working, new products and new capabilities that can help accelerate revenues. The future of AI in financial services looks bright and it will be interesting to see where firms go next. Hyper-personalization – Banks and others are leveraging AI and non-financial data to better create and target highly personalized offerings.
This is shifting the paradigm in FS from a reactive service to one that is truly intuitive and responsive. It now handles two-thirds is an invoice the same as a bill of customer service interactions and has led to a decrease in marketing spend by 25%. Rather than reactively engaging when customers have a request or issue, it could eventually anticipate and proactively reach out to customers before they even know something is wrong. Without the right gen AI operating model in place, it is tough to incorporate enough structure and move quickly enough to generate enterprise-wide impact. To choose the operating model that works best, financial institutions need to address some important points, such as setting expectations for the gen AI team’s role and embedding flexibility into the model so it can adapt over time. That flexibility pertains to not only high-level organizational aspects of the operating model but also specific components such as funding.
The Future Of AI In Financial Services
Much has been written (including by us) about gen AI in financial services and other sectors, so it is useful to step back for a moment to identify six main takeaways from a hectic year. With gen AI shifting so fast from novelty to mainstream preoccupation, it’s critical to avoid the missteps that can slow you down or potentially derail your efforts altogether. The question now is what will financial services do next and how soon will they apply AI across the entirety of their organizations and more broadly with customers.
One emerging trend is the use of AI in environmental, social and governance (ESG) investing. AI can analyze large datasets to assess how to find the present value of an annuity companies’ ESG performance, helping investors make more informed decisions that align with their values. This is particularly relevant as more investors seek to integrate sustainability into their portfolios. One practical application involved a client who frequently needed updates on his investment performance but had a busy schedule that made direct communication challenging.
Among the financial institutions we studied, four organizational archetypes have emerged, each with its own potential benefits and challenges (exhibit). QuantumBlack, McKinsey’s AI arm, helps companies transform using the power of technology, technical expertise, and industry experts. With thousands of practitioners at QuantumBlack (data engineers, data scientists, product managers, designers, and software engineers) and McKinsey (industry and domain experts), we are working to solve the world’s most important AI challenges. QuantumBlack Labs is our center of technology development and client innovation, which has been driving cutting-edge advancements and developments in AI through locations across the globe. Democratizing financial advice to the mass market can be a financial inclusion and growth opportunity for financial services. AI-driven platforms can provide personalized financial education resources, helping individuals improve their financial knowledge and make better financial decisions.
Improving Customer Service With AI
More broadly, gen AI could transform compliance and security measures, enabling firms to meet regulatory requirements more efficiently while reducing the cost and effort involved in combating financial fraud and managing risk. Learn why digital transformation means adopting digital-first customer, business partner and employee experiences. Elevate your teams’ skills and reinvent how your business works with artificial intelligence. Guardrails to ensure ethics, regulatory compliance, transparency and explainability—so that stakeholders understand the decisions made by the financial institution—are essential in order to balance the benefits of AI with responsible and accountable use. By establishing oversight and clear rules regarding its application, AI can continue to evolve as a trusted, powerful tool in the financial industry. 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.
The Benefits And Risks Of AI In Financial Services
Doug Dannemiller is the investment management research leader at the Deloitte Center for Financial Services. He is responsible for driving the Center’s research platforms and delivering world-class research for our clients. Dannemiller has more than 20 years of experience in research, what is profit and loss suspense account and how it is treated strategy, and marketing in the investment management and wealth management industries.
This proactive approach not only protects clients’ assets but also enhances their trust in financial advisory services. Generative AI (gen AI) burst onto the scene in early 2023 and is showing clearly positive results—and raising new potential risks—for organizations worldwide. Two-thirds of senior digital and analytics leaders attending a recent McKinsey forum on gen AI1McKinsey Banking & Securities Gen AI Forum, September 27, 2023; more than 30 executives attended. Said they believed that the technology will fundamentally change the way they do business. The pressing questions for banking institutions are how and where to use gen AI most effectively, and how to ensure the applications are fully adopted and scaled within their organizations. AIways-on AI web crawlers – These web crawlers continuously gather and analyze data from various web sources and public records.
- Jim is the managing director of the Deloitte Center for Financial Services, where he is responsible for defining the marketplace positioning and development of the Center’s eminence and key activities.
- Explore what generative artificial intelligence means for the future of AI, finance and accounting (F&A).
- For example, I have used AI-powered financial planning software to help clients visualize different retirement scenarios.
- Capabilities such as foundation models, cloud infrastructure, and MLOps platforms are at risk of becoming commoditized, given how rapidly open-source alternatives are developing.
- They can use AI-driven insights to inform their company strategy and improve market predictions.
- Similarly, transformative technology can create turf wars among even the best-intentioned executives.
Daniel Pinto, JPMC’s President and COO, recently estimated that gen AI use cases at the bank could deliver up to $2 billion in value. Explore what generative artificial intelligence means for the future of AI, finance and accounting (F&A). Learn wny embracing AI and digital innovation at scale has become imperative for banks to stay competitive.
