How are Indian banks adopting digitisation and AI?
Remember the time when demonetisation in India shook the country, back on November 8, 2016? People across the nation went berserk, standing before ATMs and banks, restless to deposit their notes. Banks have gone digital now. The majority of transactions are online. Can you imagine what it would be like to witness another round of demonetisation in this digital day and age? The days of standing in queues, following the long token process and fulfilling tedious formalities are long gone. The way banks function has been revolutionised with the onset of digitisation and the adoption of technology in banking. With technology, especially fintech banking solutions, customers are empowered with self-service capabilities providing them with operational processes which were otherwise given only when a customer visits a bank branch. The Union government had announced in 2021 that about 72 per cent of financial transactions from public sector banks are done digitally. In 2019-2020, there were 3.4 crore customers active on digital channels; thanks to the COVID-19 pandemic, the customer base almost tripled to 7.6 crores in 2020-2021. Leading the digitisation and adoption of AI in the Indian banking systems are private financial institutions like ICICI Bank, HDFC Bank, Axis Bank, Kotak Mahindra Bank, etc. On the other hand, big nationalised banks like SBI, Canara Bank, Central Bank, etc., too, are travelling with time and slowly taking steps to digitise their banking solutions. In an article by finder.com, it is said that India is set to experience the biggest boom in digital banking adoption in the next five years, with a 21 per cent increase in adults with online-only bank accounts. This means that by 2025, there is an estimate that just under 400 million Indian adults will hold neobank accounts. A recent survey report highlights that an estimated 205 million Indian adults already have a digital-only bank account. This number is predicted to increase to 397 million within the next five years. IDC’s latest report reveals predictions for Indian corporation banking, stating that Indian banks are projected to spend over US$1 billion by 2025 on public cloud initiatives to indicate the importance of the cloud in driving technology transformation. At the policy level, in the Union Budget 2022-23, there has been an increase in capital expenditure to fund various infrastructure projects. Accelerating the process of adoption of the cloud, leveraging AI extensively and efficiency in data management are some of the key technologies that are focused on. Some of the key predictions of IDC include AI in payments: About 40 per cent of payments will be optimised using AI-derived routing models by the year 2025. CBDC impact on cash management: As the rolling out of CBDC is gaining momentum, by 2025, more than 15 per cent of tier I corporate banks will be offering integrated solutions to unlock liquidity from traditional and digital assets. Connectivity platforms: 35 per cent of corporate banks will platformise connectivity by 2023 to deal with the growing channel fragmentation. How is AI used in banking? Artificial intelligence helps banks manage high-speed data to receive useful insights, and features like digital payments, AI bots, and biometric fraud detection systems lead to high-quality services. The COVID-19 pandemic has accelerated the deployment of AI, where organisations are automating day-to-day operations to understand COVID-19 affected datasets and leverage them to improve the stakeholder experience. Here’s a look at the application of AI in the banking sector with some exclusive insights from bankers. Akhil Handa, Chief Digital Officer, Bank of Baroda “The Indian banking industry is at the forefront of digitisation and AI specifically; many use cases are shaping the future of banking. At the Bank of Baroda, we use AI for cash forecasting at currency chests, predictive maintenance of ATMs using external sensors and internal data points of failures. Natural language processing to understand the reasons for the reopening of email complaints by analysing the resolution responses. For training employees, the Bank of Baroda has developed two adaptive learning modules that consider individual officers’ learning rates and learning requirements. This is akin to learning “Segment of One” – in terms of personalisation.” Prashant Joshi, Managing Director and Head Consumer Banking Group, DBS Bank India “At DBS, our brand promise ‘Live more, Bank less’, reflects our belief that in the digital era, we must deliver banking that is so simple, seamless and invisible that customers have more time to spend on other important aspects of life. Our mobile banking application, digibank, by DBS, delivers a paperless, straight-through and intuitive experience across all banking transactions. It provides a host of digital-first features, including 24×7 live chat for daily banking needs and end-to-end wealth management solutions, domestic and international remittance options and clutter-free digital loan approval and repayment process. DBS customers can also complete their digital KYC via a video-based Customer Identification process.” About digibank digibank provides AI-backed Intelligent Banking services to customers, enabling them to manage their finances better, leading to higher engagement, retention, and transactions. Since the AI-powered insights feature within digibank went live in 2020, the bank has seen 47% repeat usage of the feature month-on-month. In fact, digibank is already contributing to about 20% customer acquisition across all our branches, thus complementing the bank’s physical network. According to IBS intelligence, there are five applications of AI in banking: 1. Customer service/engagement (Chatbot) Incorporating chatbots provides very high ROI in cost savings, making them a popular application across many industries. Customers can easily solve their queries on chatbots, like balance inquiries, accessing mini statements, fund transfers, etc. This helps reduce the burden on contact centres, internet banking, etc. 2. Robo advice A Robo-advisor makes an effort to understand a customer’s financial health by analysing the shared financial history and data. The Robo-advisor gives investment recommendations for a particular product or equity based on the analysis and goals set by the client. 3. General Purpose/Predictive Analytics AI’s most popular usage is in general-purpose semantic and natural language applications and broadly applied predictive analytics. AI is leveraged to detect specific patterns and correlations in the data, which was otherwise impossible using legacy technology. These patterns help to identify untapped sales and cross-sell opportunities, or even metrics around operational data, which leads to direct revenue impact. 4. Cybersecurity AI improves the effectiveness of cybersecurity systems where it leverages data from previous threats and then learns the patterns and indicators that may be unrelated to predicting and preventing attacks. AI also helps in monitoring internal threats or breaches and suggests corrective actions, resulting in the prevention of data theft or abuse. 5. Credit Scoring/Direct Lending AI plays an important role in helping alternate lenders determine the creditworthiness of clients by analysing data from traditional and non-traditional data sources. This helps lenders to come up with innovative methods of lending systems that are backed by a robust credit scoring model, even for those individuals or entities with limited credit history. Indian banks have to move with time and help customers to adopt newer technologies with ease. Digitisation and leveraging AI has helped both banks and customers in making the entire banking experience hassle-free.
An estimated 205 million Indian adults already have a digital-only bank account, and this number is predicted to increase to 397 million within the next five years.
An estimated 205 million Indian adults already have a digital-only bank account, and this number is predicted to increase to 397 million within the next five years.
["ai bots", "Cybersecurity", "Predictive AI", "predictive analytics"]
["Go", "artificial intelligence", "AI", "chatbots", "R", "ML", "RAG", "analytics", "ai bots", "Cybersecurity", "predictive analytics", "Predictive AI", "fraud detection"]
["AI", "artificial intelligence", "ML", "analytics", "RAG", "chatbots", "predictive analytics", "fraud detection", "R", "Go"]
Poornima Nataraj has worked in the mainstream media as a journalist for 12 years, she is always eager to learn anything new and evolving. Witnessing a revolution in the world of Analytics, she thinks she is in the right place at the right time.