How AI is transforming customer management in banking sector

There has been considerable rise in the implementation of artificial intelligence (AI) and machine learning (ML) tools in the BFSI sector.

This intelligent technology is helping the banking industry overcome customer service challenges and improve its operations and services. Its application and use cases are seen in more areas especially in the banking sector.

The Stamford firm’s 2019 CIO Survey of more than 3,000 executives in 89 countries found that AI implementation grew a whopping 270 percent in the past four years, and 37 percent in the past year alone.

“The data-intensive nature of the BFSI sector makes it imperative to utilise AI to sift through large volumes of data and customise offerings for the customers. Industry players are using emerging technologies such as AI, ML, natural language processing (NLP), virtual assistants and deep learning to enhance their capabilities,” says Faisal Husain, Co-founder and CEO, Synechron.

“Despite being around for many years, AI is mostly present in the form of chatbots for conversational banking or as robo-advisors in wealth management. Globally, we are seeing a convergence of AI with blockchain to automate back-office operations and customer management. Furthermore, the wealth management industry is leveraging AI and ML algorithms to detect stock market movements on a real-time basis and manage client portfolios,” he added.

Light Information Systems, which has developed NLP Bots, has implemented AI within banks across several use cases such as marketing, risk mitigation, customer care, employee care, etc.

Throwing more light on the common uses of AI in banks, Animesh Samuel, Co-founder & Chief Evangelist, Light Information Systems, says the AI tools play an important role in Visitor Management, Targeted Advertising, Risk Mitigation, Customer Care and Employee Care.

Talking of visitor management, he explains that AI assistants are helping customers with various aspects such as requesting appointments after pre-sanctioning a loan based on a document uploaded.

“When it comes to customer care, AI helps solve several customers’ queries relating to their transactions, loan status, balances, procedures, branches, etc. that we’ve helped automate,” he adds.

According to S. Sundararajan, Executive Director at i-exceed, “At a high level, AI plays a big role in classification, clustering, regression, and dimensionality reduction of immense sets of data to build models designed to perform specific tasks.”

• Build Natural Language Processing (NLP) engines and create chatbots
• Enable contextual banking by offering coupons and discounts based on customers spend analysis and usage patterns
• Identify likely Loan delinquencies based on current and historical data
• Automate the initial interactions in IVR calls till human intervention is required
• Analyse collated customer inquiries received by call centres to gain deeper understanding of the trends in customer behaviour
• Device systems to address situations better
• Segment and analyse customers’ banking patterns to offer insights / products / services
• Improve response times and engagement levels
• Develop voice-based interactivity systems etc.