Artificial Intelligence: Redefining banking

The State Bank of India (SBI), the nation’s largest public sector bank, has been a subject of humour with the infamous ‘lunch break’ and ‘server is down’ memes circulating on social media. But then, ILA doesn’t take lunch breaks. Confused? ILA, SBI’s virtual assistant, can help you activate your SBI credit card, check the summary of the Reward Points and solve other queries too, all from the comfort of your house. The advent of Artificial Intelligence (AI) has revolutionised the banking sector. AI in banking is set to soar, with projections reaching $64.03 billion by 2030. Armed with the ability to process vast data, learn intricate patterns, and make informed predictions, AI has become a reliable friend for financial institutions. In the banking, financial services, and insurance (BFSI) sector, the application of AI and Machine Learning (ML) has not only personalised the customer experience but has also enhanced efficiency and security.

“AI’s transformative impact has been profound since its advent, changing how enterprises, including those in the banking and finance sector, operate and deliver services to customers. The introduction of AI in banking apps and services has made the sector more customer-centric and technologically relevant,” said Sudip Chatterjee, Senior Vice President & Head, Eastern Zone, Branch & Business Banking of a fast growing private sector bank.

Chatbots and virtual assistants

For those not well-versed in financial transactions, understanding loan eligibility and insurance plans can be challenging. Now, standing in long queues or waiting endlessly on calls is no longer necessary. AI chatbots and virtual assistants are here to solve your banking queries. Just ask your questions, and they’ll give you quick, real-time answers. AI has made customer service in banking and finance easy, available 24X7, and way cheaper. Take Axis AHA 2.0, for example. It’s a virtual assistant that speaks English and Hindi. Ask it about your cheque or credit card, and it gives you instant answers.

Personalised financial services

According to a McKinsey report, AI has the potential to unlock a staggering $1 trillion of additional value for banks every year. The power of AI algorithms lies in their ability to analyse vast amounts of data, providing personalised financial recommendations such as tailored investment strategies and savings plans. Through data analysis, AI empowers banks to offer automated investment portfolios, thus improving the overall customer experience with a focus on personalisation and customer-centric services.

Fraud detection and prevention

Fraud in banking, like money laundering and shady transactions, is unfortunately common. In such scenarios, AI and ML act as superheroes, scanning through all transactions superfast to catch anything fishy. These smart algorithms can detect unusual patterns and alert humans to take a closer look, making online banking much safer for everyone. JP Morgan, one of the world’s biggest banks, has been using AI for over two years to check payments. It’s like having a digital guardian that not only reduces fraud but also speeds things up by cutting down on mistakes. Result: A better experience for customers, with a 15-20% drop in account validation rejection rates.

At ICICI Bank, they’ve software robots, which learn from different systems, recognise patterns, and smoothly handle tasks across various applications. This not only reduces errors but also ensures a more reliable and efficient banking experience.

Back-office automation

In the banking and financial sector, automation has not only cut down on operational costs but also lowered the chances of human error. AI-powered automation takes care of routine and repetitive jobs like data entry and document verification. This means employees can now concentrate on more important tasks like building relationships with customers and making strategic decisions, thus adding more value to the overall operations.

Credit scoring and risk assessment

Traditional ways of checking if someone is eligible for a loan can take a long time and might not give the full picture of their financial situation. AI algorithms, however, can look at a wider range of information, even details from social media and online activities. Using ML, banks can create more precise and faster credit scores. This helps them make smarter decisions about who should get a loan, increasing the chances for deserving borrowers to get approved and lowering the risk for the bank. “The AI application in risk management has significantly enhanced Anti-Money Laundering (AML) efforts. Financial institutions utilise AI to scrutinise transaction patterns for suspicious activities. An example is AI identifying irregular large transfers from high-risk jurisdictions like tax havens. The integration of AI in risk management is transforming how businesses predict, analyse, and mitigate various uncertainties. With the application of AI for risk management, companies are not just improving efficiency but also enhancing the accuracy of their risk assessment strategies,” said Chatterjee.

Trends and predictions

ML and AI are used for forecasting revenue, figuring out stock prices, and keeping an eye on risks. For investors, AI even suggests the best time to invest in stocks and warns about potential risks. It’s like having a smart personal assistant, who makes things clear and safe in the financial world.

The future of finance is changing with the seamless integration of AI into financial services, like digital wallets and interfaces. Imagine humanoid robots like Pepper at HSBC’s Miami branch, enhancing customer experience. HDFC Bank’s Interactive Robotic Assistant (IRA) 2.0, another interactive humanoid, is also part of this revolution. The future of banking is evolving through this powerful technology, ensuring you stay at the forefront of financial management.