Customer Service
AI and Automation Are Transforming CX in Fintech
Building lasting customer relationships has long been a defining characteristic of the banking and financial services industry. Trust is a pivotal element influencing individuals in their choice of financial institutions. Once established, the relationships mostly endure for years unless something goes wrong drastically. However, the scenario is changing, dictated by the demands of a digital era.
Digitisation has had a significant impact on the banking industry. Albeit watchfully, the industry has been adopting digitisation to stay relevant and competitive. Trusted partnerships between financial institutions and their clientele have become crucial for both parties. Credible industry studies say Customer Experience (CX) is the linchpin holding it all together! Over 70% of millennials and Gen Z surveyed for a BAI Banking Strategies Executive Report expressed their readiness to switch banks for better digital capabilities.
And that’s just one part of the story. CX serves as a catalyst for much more than loyalty, and fintech AI is paving the way. According to a McKinsey study, banks high on customer satisfaction also had increased growth, decreased costs, and better total shareholder returns (TSR). Customer experiences have become paramount in banking BPO services, and Chief eXperience Officer (CXO) roles have garnered strategic importance. AI and automation are allies helping CXOs unlock unprecedented customer satisfaction levels and loyalty. A Capgemini study titled, 'How to drive AI at scale to transform the financial services customer experience' revealed that 94% of financial firms consider improving CX as the key objective behind adopting AI initiatives.
The use cases
AI technologies in fintech help improve CX across front, middle and back office operations. In the front office operations, they help expedite customer query resolution, offer product recommendations, facilitate cross-selling, engage in social listening, and enhance in-person branch experiences. Middle office operations benefit from features like voice and facial recognition-based authentication, fraud detection, and more. Most back-office operations, such as loan processing, risk mitigation and analysis, etc., are automated.
Here are some specific areas of CX transformation driven by AI in the fintech industry.
Mitigating delays in customer service
The Capgemini study says 71% of banks have seen up to 20% improvement in the pace of customer support resolution. Conversational AI tools, including chatbots and virtual assistants, replicate human interactions to accelerate issue resolution. Automation of in-app messaging and self-service portals across websites, email, chat, and social media channels mitigate delays in response to customer queries. Humanoids are simplifying critical processes like credit card applications and new account openings. According to the Capgemini study, these two processes are major customer CX pain points.
Some institutions have also implemented product and portfolio suggestions using robotic intelligent financial assistants. AI tools help measure and update CX drivers in real time for faster customer resolution. Automated omnichannel messaging helps these entities create better CX.
Personalisation and reimagined user journeys
Marketers have traditionally used third-party cookies to understand customer behaviour for personalised recommendations. But Google has announced the demise of third-party cookies phased across 2024. Hence, targeted ads and product cross-selling strategies are changing.
Financial institutions are better placed than others to manage the cookieless scenario. They have access to first-party customer data, which they have started mining by leveraging AI to unlock value. Some AI-powered strategies they are implementing are look-alike modelling for propensity audiences and agent-based modelling. ML-driven look-alike models analyse extensive first-party data to create user personas of target customers most likely to purchase products and services.
Media Mix Modelling (MMM), also called marketing mix modelling, helps predict the outcome of various what-if scenarios to make faster and better decisions. These strategies help fintech institutions reimagine user journeys to improve CX. According to a McKinsey article a large North American bank achieved a 25 to 50% increase in customer satisfaction by proactively reimagining key customer journeys.
However, challenges around customer trust in AI need to be overcome.
Reinforcing the trust factor
Relationships in the financial industry hinge on trust. Many customers hesitate to use digital channels since they don’t yet fully trust technology. In the Capgemini study, 52% of customers quoted trust in the transparency and fairness of the AI system as a top consideration for increasing AI interactions. Financial institutions must retain some level of human interaction to maintain that trust. Educating customers on the transparency and ethical aspects of AI is equally essential to build trust. Ironically, AI can drive trust in a few ways also.
AI-powered fraud resolution strategies like warning customers about potential fraud in their accounts are a positive step in this direction. Also, some financial institutions offer highly personalised investment recommendations aligned to the customer goals using robo-advisors. These recommendations based on predictive analytics are helping customers achieve expected returns in an otherwise dynamic market. Such services fortify the trust while improving CX by miles. These little steps will go a long way in creating a customer-centric ecosystem that will help shape the future of AI-driven CX in fintech.
How can Infosys BPM help?
Infosys BPM’s banking services include solutions to transform business models, streamline processes, and augment performances. Our BPM services deliver exceptional business value while reducing costs. We assist businesses in creating enhanced customer experiences by easing their automation journeys based on robust technological foundations.
