Picture this scenario: John has been banking with the same institution for years. Every transaction, from his monthly bill payments to his occasional investments in fixed income products, feeds into an AI-powered system that creates a detailed, single-view profile of John’s financial behavior. This profile highlights not just his spending patterns but also his investment risk appetite, long-term goals, and preferences.
Now, based on the profile generated by AI based on past insights, customer behavior, and various other parameters, every time John logs into his banking app, he gets to see a personalized recommendation tailored specifically to him. It’s either a diversified investment portfolio that aligns with his risk appetite, a CD or High Yield Savings account offering better interest rates for his deposit, or even pre-approved loan options based on his financial history. The app’s AI assistant goes a step further, analyzing his responses in real-time to refine these suggestions, enabling John to make an informed decision—all without ever speaking to a human advisor.
This kind of hyper-personalized banking experience, unthinkable just a few years ago, is now transforming how financial institutions engage with customers. By leveraging AI’s growing capabilities, banks are redefining customer experiences, turning every interaction into a moment of meaningful engagement.
Investing in Use Cases that Transform Unique Financial Journeys
AI continues to show how its capabilities enable personalized service, recommendations, and advice by analyzing behavioral and historical data to craft customized solutions and products that accurately reflect each customer’s financial journey.
Nearly a third – 32% – of financial services providers already use predictive analytics to detect patterns that help predict future behavior, equipping them with insights to develop service propositions that meet individual financial needs and expectations.
With consumers who are increasingly tech-savvy and empowered, banks and financial institutions need to be more than places where people keep their hard-earned money. Customers expect a partner who provides value, enriches their transacting and interacting experience, and supports their financial well-being. Customers expect their financial institutions to provide a tailored, unique, and personalized experience, very similar to some of the experiences provided by the likes of Amazon, Uber, Meta, and many more.
The financial institutions that deliver on these outcomes reap the rewards. Banks who regularly optimize customer experience grow 3.2 times more rapidly than those who don’t.
And, the banks leading the field are the ones harnessing AI.
High-impact emerging use cases in the banking and financial services industry include:
- NLP-based AI is now evolving and will make customers feel heard and valued, as well as display contextual awareness. This will help in areas such as loan restructuring, missed payments, and customers in collections requiring financial assistance. GenAI solutions will help simplify complex content and provide crisp and easy-to-digest summaries, making it easier for customers to understand.
- AI and predictive analytics streamline and fully automate the customer onboarding process by unifying inputs across channels and existing customer relationships and datasets. They also deliver faster KYC checks with better accuracy and compliance. All of these, in turn, reduce the dropout rates and improve the overall customer experience. For customers who switch providers due to poor user experiences, this is a game changer.
- AI can additionally enable self-service to help customers resolve their own support queries quickly and easily, such as account balances, transactions and transfers. Individuals today expect rapid, responsive customer service on the channels of their preference. Gen AI can bridge the gap for banks by facilitating seamless self-service at speed and scale. Not only does this elevate the customer experience, it also enhances efficiencies and cost savings.
The number of use cases around AI augmenting customer service and experience continue to grow every day. Agentic AI, in particular, is emerging as a useful tool in improving customer service. Its ability to autonomously make decisions, perform tasks, and adapt in real-time means that it can provide 24/7 customer support, helping answer queries and troubleshoot even complex cases.
In the financial services sector, this means that banks can make faster, smarter decisions about investments and lending, helping them manage and mitigate risk more effectively.
In this rapidly advancing technological environment, it is becoming increasingly obvious that AI-driven CX is no longer a nice-to-have feature for banks, financial institutions, and fintechs. It is a must have to deliver unforgettable experiences, drive transformative outcomes at scale, and balance costs.
Next-Level Customer Experience in Action
The key to success is more than knowing the potential use cases of AI. Financial services providers can learn from those who have demonstrated effective AI implementation and create value by delivering experiences that go beyond customer expectations.
One such case in point was a leading fintech, digital bank, and peer-to-peer lender that had grown significantly. Their systems and processes couldn’t keep up, though, and the resulting inefficiencies were harming the customer experience.
In addition to integrating and harmonizing business processes, Sutherland helped the company establish Centers of Excellence with a 360-degree customer view, bringing in hyperautomation for their credit review, funding processes and omnichannel support. Through this solution, they achieved a 40% reduction in Total Cost of Ownership while improving CSAT by 25%.
In another example, a leading Private Label Credit Card issuer was struggling to keep up with the ever-increasing fraud and dispute volume and wanted to make their dispute management process more efficient while reducing operational expenditure. Backed by our deep domain expertise in fraud, dispute management and proprietary hyperautomation solution which utilized AI-enabled data extraction, RPA bots, workflows, and a command center to monitor virtual workforces 24/7, Sutherland processed 200% of the transactions while reducing 60% cost for the client with 99.5% accuracy.
The 5 Steps to Take to Adapt to Market Dynamics
With customer needs and expectations constantly evolving—especially in the banking and financial services sector—organizations must proactively innovate to stay ahead. The next frontier of customer experience will demand total customization, highly relevant promotions, and AI-powered contextual understanding. To prepare for this shift, financial institutions should take these five steps:
- Implement Hyper-Personalized AI Models Across the Customer Journey
Integrate AI solutions that deliver personalized recommendations, promotions, and insights across every touchpoint of the banking relationship. - Define ‘Human-in-the-Loop’ Strategies
Clearly determine which customer interactions require human involvement and integrate these seamlessly with AI-driven processes. - Unlock Revenue Through Experience Monetization
Train both agents and AI systems to shift from problem-solving to proactively offering curated experiences that drive customer loyalty and generate revenue. - Adopt No-Code/Low-Code AI Solutions
Invest in tools that simplify deployment, configuration, and regular updates, ensuring agility in responding to market changes. - Proactively Manage Risks and Limitations
Identify potential challenges such as AI-generated inaccuracies (“data hallucination”) and focus on deploying solutions in low-risk, high-value areas.
Delivering next-level experiences against a backdrop of constant change is no easy feat. However, harnessing advanced technologies like AI can both optimize operations and transform your customer’s overall experience, helping unlock value and bottom-line impact.
