AI is playing a larger role as customers are increasingly expecting more personalised experiences and customer-centric innovations from businesses.
Financial institutions have been leveraging artificial intelligence (AI) to develop these customised products and deliver tailored services to their customers.
Customising product and service recommendations
Algorithms can be used to analyse vast amounts of customer data, including behaviour patterns and transaction history, to understand unique customer preferences and suggest customised product recommendations. Behavioural analytics are also extremely useful in gaining insights into customers’ financial goals and spending habits to personalise marketing campaigns and promotions to match customer interests and needs.
Financial institutions have been increasingly adopting AI-driven solutions for personalisation, enhancing their customers’ digital experiences. For example, in March 2023, Visa partnered with AI and big data company Crayon Data to enable card issuers to use AI-driven insights that enhance customer engagement through hyper-personalization. Crayon Data’s AI platform gathers data from across diverse lifestyle categories to construct a graph-based entity-affinity model known as a ‘Tastegraph’. This model is then linked with Visa’s customer behaviour data, enabling access to a wide range of choices and personalised recommendations.
Improving customer assistance using AI chatbots
AI-powered chatbots and virtual assistants can also be used by financial institutions to offer personalised customer support. Using machine learning, chatbots can continuously improve their responses to customer inquiries and tailor interactions based on individual customer preferences. Chatbots can also provide 24/7 support to customers through digital channels, meeting customer expectations for immediate and convenient service.
Banks and insurers alike have been adopting virtual assistants to provide personalised guidance to their customers, improving their customer relationships while streamlining their operations. For example, insurance company Lemonade has been using chatbots to offer quotes and resolve claims quickly via the company’s online platforms. The Lemonade app uses chatbots, AI Jim and AI Maya, to greet customers and answer their queries by analysing customer data, eliminating the need for middlemen. AI Maya aids customers that are purchasing policies, catering to each customer in a personalised manner. AI Jim deals with claims handling and observing the incident via video and pictures.
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Creating customer profiles for risk assessments
Big data visualization can aid financial institutions in applying AI to conduct better risk assessments and credit scorings. Using data points like credit history and financial transactions, AI algorithms can assess an individual’s creditworthiness. Automating the credit scoring process enables banks to provide personalised loan offers, interest rates, and credit limits according to the customer’s risk profile. In the insurance sector, AI-powered data analytics and risk assessment tools allow insurers to create real-time profiles of their customers. Ultimately, this helps design products that more closely fit customers’ needs and behaviours. Providing customizable coverage rather than a one-size-fits-all approach will help insurers with customer retention.
Overall, AI is an important technology for financial institutions to use in order to automate processes and provide personalised customer services. This technology will help to enhance the customer experience and increase loyalty.