Banking on AI: The Journey from Transaction to Interaction
By : Abhinav Pragya
Global Head - Digital CX
Customer experience (CX) is a key differentiator for banks in today’s competitive and digital-first market. Customers expect convenient, trusted, intuitive, and most importantly personalized services across channels. According to a McKinsey survey of US retail banking customers, banks with high customer satisfaction scores saw deposits grow 84 percent faster than lower rated banks. Satisfied customers are also more likely to buy additional products and stay loyal to their banks.
One of the main challenges that banks face is that customers have different financial goals, risk profiles, and communication preferences. To address this challenge, many banks are turning to Artificial Intelligence (AI). In this post, we explore five ways in which AI is transforming CX in retail banking.
1. Chatbots Get An AI Boost
Chatbots have become the preferred tool for first level customer service, with the intention of providing a standardized experience and short waiting times. However, legacy chatbots have their own issues, such as:
- Difficulty understanding complex or nuanced queries
- Limited knowledge of local financial regulations
- Heavily reliant on clean and accurate training manuals on the bank’s products and policies
To overcome this limitation, banks are upgrading their chatbots with contextual intelligence, allowing them to handle complex queries and provide accurate responses straight away. Some have also evolved beyond ‘chatbots’ to virtual assistants’. For example, Bank of America’s Erica proactively informs customers when they are eligible for the bank’s rewards programme, while Capital One’s Eno alerts customers about unusual charges and sends reminders about trial subscriptions.
2. Seamless Data-Driven Personalization
Another way that AI can enhance CX is by creating personalized digital experiences for customers based on their interactions, historic usage patterns and latent needs. AI can analyze customer data from various sources, such as transactions, interactions, and feedback to micro-segment customers into groups based on their needs and behaviours.
When a Wells Fargo customer buys a travel ticket, the AI may recommend setting up a ‘travel plan’ to calibrate the customer’s account for transactions in other geographies. Leveraging the financial data banks have on their customers, AI can make meaningful product and service recommendations, and provide personalized tips to help customers manage their finances better. Thus through personalization AI is being used to build trust and relevance.
3. Accelerating Financial Inclusion
According to the World Bank, about 1.4 billion adults remain unbanked, meaning they do not have an account at a financial institution or through a mobile money provider. Moreover, many people who have bank accounts do not use them regularly or effectively, due to various barriers such as cost, convenience, trust, or literacy.
AI can help banks overcome these barriers by making their digital channels more accessible and user-friendly for customers by reducing customer effort. The introduction of multilingual and voice-based processes powered by Large Language Models (LLMs) can greatly increase interactions in areas with low literacy. Banks can also use AI to comb through alternative data beyond traditional credit scores — ranging from mobile phone usage, social media activity, and audio/text data.
4. Boosting Loyalty
With the assistance of AI, banks can design hyper-personalized offers and improved loyalty programs for their customers. Using AI intervention, South Korea-based Hyundai Card was able to forecast customer behaviour and identify customers eligible for additional credit lines at their time of need.
AI is also particularly useful in determining the optimal timing, channel, and content of marketing campaigns to increase conversion rates and customer satisfaction. An example of this is demonstrated by Bank of Ameria’s Erica assistant. Besides guiding customers to join the bank’s rewards programme, it also nudges them when they are within $10,000 of the next rewards tier, ensuring customers are aware of available opportunities.
An effective consumer product or loyalty programme also gives banks a unique community-building opportunity. By deploying AI on first party-data collected from loyalty programmes, banks can effectively segment customer cohorts and leverage opportunities to give each cohort the benefits they aspire to. Depending on cohort, these can range from better forex rates, premium credit cards, or additional perks at premium airport lounges, fostering the sense of being part of a privileged circle.
5. Building Better Partnerships
AI can play a pivotal role in helping banks and their partner organizations — such as insurance companies and investment product providers — offer useful collaborative products. Financial services company BBVA has already worked with Google Cloud to make an AI model capable of predicting income and expense streams. These kind of modelling capabilities allow banks to work with partner organizations and cross-sell the right products at the right time. Getting meaningful recommendations instead of unpersonalised offers increases the likelihood of engagement and conversion, elevating the customer experience.
While this data gives banks the ability to offer better products to customers, trust and privacy are important factors to be considered. 79% of customers surveyed by Salesforce claimed to be increasingly protective of their personal data. This data makes a strong case for the use of privacy-preserving AI — which is trained on trillions of anonymous and encrypted data points on customer interactions. Using privacy-preserving AI allows banks and partners to continue to work together to offer relevant services without compromising customer trust and safety.
AI Adoption: The Early Mover Advantage
AI is transforming CX in retail banking by enabling banks to anticipate customer needs, personalize their offerings, and automate their processes. After years of focusing on a digital-first customer strategy, the next logical step for retail banks in improving customer experience is adopting an AI-first strategy. The personalisation, relevance, and privacy offered by AI-powered solutions is already starting to help customers make better money decisions.
In many Western and Asian countries, increasingly Banks are viewing AI as a means to measure, monitor and maximise customer lifetime value (CLTV).
Given the pace at which AI is progressing, it is important that banks consider a robust, long-term AI strategy with a deep customer focus. As AI adoption in retail banking increases rapidly, banks that move first stand to greatly enhance CX and gain a competitive edge.
