Technology
Beyond chatbots: Elevating financial services with conversational utility
Global Banking and Finance Review
Company
By Richard Winston, the Global Industry Lead of Financial Services at Slalom
In the competitive and rapidly evolving industry of financial services, one thing has remained steadfast as an essential pillar for sustained success: exceptional customer experience (CX). Beyond simply facilitating transactions, financial institutions understand that the quality of their customer service can make or break their reputation, customer loyalty, and, ultimately, their bottom line, but they haven’t always gotten it right. In fact, 89% of customers will switch to a competitor following a negative experience. So, in an industry where products and services often seem interchangeable, now more than ever, CX is the key differentiator.
Customer expectations have evolved, and a friendly interaction alone no longer satisfies; personalization is crucial to loyalty and even more so for attracting new customers, as 80% are more inclined to make purchases when brands offer personalized experiences. They have seen the power of generative AI and now expect it in everyday life. However, the application of AI is less expected in industries where data security is crucial, such as financial services—though players in this space who have implemented it well are truly standing out. With this in mind, financial executives are exploring the art of the possible with emerging technologies like never seen before. Leading the way in the industry, Bank of America, Wells Fargo, BlackRock, and Citigroup have all either launched or announced initiatives focused on generative AI.
The transformative potential of conversational AI
Conversational AI is emerging as a key innovation, poised to transform how financial institutions interact with clients. This form of AI can simulate human conversation using natural language processing. This advanced technology goes several steps beyond a typical chatbot, which relies on predefined conversation flows to communicate with users. With the conversational utility layered in, the experience feels different, and the impact is much more significant.
In financial services, conversational AI-driven personalization transcends traditional customer service by crafting unique, responsive experiences for each individual. Through extensive data analysis, AI delivers customized financial advice, anticipates needs, and offers timely suggestions, deepening and enriching the client relationship.
Chatbots equipped with generative AI and voice assistants are the enabling interface for this personalization with real-time, natural language interactions. These systems can handle inquiries, execute transactions, and offer financial guidance efficiently around the clock. This capability not only enhances accessibility and convenience for customers but also significantly reduces operational costs for banks.
Moreover, conversational AI can continuously learn from interactions, improving its responses over time and providing insights into customer behavior and preferences. This intelligence allows financial institutions to tailor their products and services more effectively, ensuring they meet their customers’ evolving and potentially unmet needs.
The benefits of conversational AI include:
Delivering conversational AI outcomes
As with all technology investments, ROI is a significant driver for leaders, so how do you measure the impact of a conversation? One key statistic to focus on is net promoter scores with your customer base, followed by retention and net new customer acquisition numbers. These three indicators trending upward will prove the investment is a success, and stakeholders will be more likely to approve future investments in AI as they see the trickle-down to bottom-line impact. The question then becomes: how do you capture the insights required to deliver the outcomes?
AWS and Slalom have partnered to create Lightflow, a banking CX engine that enables insights for financial institutions and drives high-quality, hyper-personalized customer experiences. By integrating with AWS services, Lightflow offers a unified, real-time view of customer data that can increase operational efficiency.
This engine utilizes advanced conversational AI, machine learning, and chatbot capabilities to enhance cross-channel customer interactions and engagements, increasing satisfaction and loyalty. These AI-driven chatbots can deliver highly personalized banking experiences, understand and predict customer needs, and automate routine inquiries, enabling banks to offer more informed, 24/7 customer support and tailored financial services.
This fusion of customer data and conversational AI empowers financial institutions to redefine customer service, making it more interactive, responsive, and aligned with individual customer preferences and behaviors. The Lightflow platform signifies a key advancement in hyper-personalization, providing a comprehensive solution for enhanced customer engagement in the financial services industry.
What’s next for financial services and AI
As we look to the future, AI will continue to amaze.
One example of where conversational AI could expand is into digital wallet capabilities, allowing these systems to manage customer transactions such as payments, transfers, and investments directly. This evolution would offer a seamless banking experience, simplifying financial management to conversational interactions. Such AI systems would execute transactions and proactively optimize finances according to user preferences and goals, essentially serving as an intelligent financial assistant.
Furthermore, as AI gains a better understanding of patterns and behaviors, it could evolve into a proactive financial advisor, automatically adjusting your financial strategy to optimize savings, investments, and spending. This AI could anticipate needs, manage risks, and even negotiate better rates or opportunities on your behalf, essentially becoming an autonomous guardian of your financial well-being.
Indeed, while fully autonomous financial advisors may be on the distant horizon and customers may initially hesitate to embrace handing their investment strategies over to AI, the ongoing improvements in AI capabilities will significantly change the financial services landscape. This technology performs best with hard data, so that is where we expect to see the most innovation to date.
For now, AI is proving to be an admirable co-pilot to our customer service agents, advisors, and managers, helping to pave the way for seamless experiences. Early adopters of this technology stand to differentiate themselves by offering unprecedented levels of personalized service, and according to the Harvard Business Review, “The winners will be the largest firms able to invest in the computing power and data to create differentiated strategies.” As trust in AI’s decision-making grows, these pioneering institutions could be the leaders in customer satisfaction, loyalty, and financial innovation, setting new industry standards for personalized financial management.
In essence, the role of artificial intelligence and conversational AI in personalizing financial services marks a leap towards more responsive, efficient, and customer-centric banking. As these technologies advance, they promise to unlock new levels of service personalization, transforming the financial landscape and setting new standards for customer engagement.
Author Bio:
Richard Winston is the Global Industry Lead of Financial Services at Slalom. He leads the financial services industry team and helps clients, markets, and alliance partners across banking, insurance, and capital markets navigate the future of banking innovation and AI technologies.
Customer experience (CX) refers to the overall perception a customer has of a brand based on their interactions throughout the customer journey.
Conversational AI is a technology that enables machines to simulate human-like conversations using natural language processing, enhancing customer interactions.
Generative AI refers to algorithms that can create new content or data, such as text or images, based on patterns learned from existing data.
Operational efficiency is the ability of an organization to deliver products or services in the most cost-effective manner without compromising quality.
Risk management in finance involves identifying, assessing, and prioritizing risks followed by coordinated efforts to minimize, monitor, and control the probability of unfortunate events.
Explore more articles in the Technology category
