<\/p>\n
A few years ago, a junior employee at a major Indian bank<\/a> spent hours navigating outdated policy manuals just to respond to a client query. Today, that same task takes less than 30 seconds to complete. All thanks to an artificial intelligence (AI) powered chatbot. What once demanded tedious manual effort, multiple approvals, and endless email threads is now handled by intelligent automation, offering instant and reliable answers.<\/p>\n<\/div>\n This offers a glimpse into a broader transformation quietly reshaping the banking, real estate, and financial services sectors. AI is no longer a distant promise. It\u2019s here, and it\u2019s redefining how legacy industries operate, deliver value, and make decisions.<\/p>\n<\/div>\n One powerful example is the State Bank of India\u2019s generative AI solution, askSBI. Designed to help employees tackle complex business scenarios, the chatbot serves as a centralised knowledge hub. It reduces dependence on manually curated documents, enhances internal communication, and streamlines access to critical information, ultimately improving operational efficiency and service quality across the board.<\/p>\n<\/div>\n But AI in traditional sectors is not just about cutting costs or increasing speed\u2014it\u2019s about enabling smarter decisions, improving customer experiences, and future-proofing operations. This was the central theme of a recentpanel on Mint’s series All About AI featuring industry veterans such as Arundhati Bhattacharya, President and CEO of Salesforce – South Asia; Kripadyuti Sarkar, CIO at Ambuja Neotia; and Ratan Kumar Kesh, Executive Director and COO of Bandhan Bank<\/a>. Together, they unpacked how AI is creating real, tangible change\u2014and the roadblocks that still need to be overcome.<\/p>\n<\/div>\n Watch the full episode below,<\/p>\n<\/div>\n In banking, AI tackles vast operational challenges swiftly and efficiently. Arundhati remarked, \u201cBanking has a lot of operational challenges. There are risk management issues. There are issues of finding fraud. But more than anything else, there is an issue of giving a uniform level of customer service that really and truly gives an experience to a customer which will enable the customer to want to come back again.\u201d<\/p>\n<\/div>\n The transformation is already measurable. One of the most immediate and visible applications is fraud detection. Traditional systems rely on static, rule-based models that can be slow to adapt. In contrast, AI-powered tools continuously learn and evolve. For instance, in 2019, SBI deployed an AI-driven fraud analytics platform capable of analysing transaction patterns in real-time. Similarly, ICICI Bank\u2019s AI chatbot, \u2018iPal,\u2019 utilises natural language processing not only to handle customer queries but also to proactively flag suspicious behaviour, thereby enhancing both customer service and fraud prevention. Besides these, multiple other banks, including HDFC Bank<\/a>, Axis Bank, Federal Bank<\/a>, and more, have implemented conversational AI solutions.<\/p>\n<\/div>\n But AI\u2019s role in banking goes far beyond risk mitigation. It\u2019s helping banks deliver hyper-personalised experiences.<\/p>\n<\/div>\n Ratan highlighted AI\u2019s indispensable role in today\u2019s financial services landscape, stating, \u201cIn the financial services industry, you cannot survive without AI. It provides a comprehensive view that allows effective management without needing a large number of experts on staff.\u201d<\/p>\n<\/div>\n The potential benefits of AI are substantial. According to anEY report<\/a>, generative AI is projected to boost productivity in Indian financial services by 34\u201338% by 2030, with banking operations alone expected to see a 46% increase. Ratan also pointed to concrete improvements, noting, \u201cCosts come down by 20 to 30%. Net Promoter Scores increase by 20 to 30%. Fraud detection, personalised customer offers, and credit decision-making \u2014 AI is fundamentally transforming the banking landscape.\u201d<\/p>\n<\/div>\n Further emphasising AI\u2019s growing prominence, Gartner predicts that by 2026,90%<\/a> of finance functions will have integrated at least one AI-enabled technology. This shift marks a move from experimentation to full operational adoption, making AI a core pillar of modern financial strategy and decision-making.<\/p>\n<\/div>\n Kripadyutipointed out the inherent human dependency of the real estate sector. “Real estate is a human-dense industry. It has always been trusted human intelligence over any sort of intelligence, be it AI or ML.” He emphasised the challenges posed by human variability and emotion in decision-making, which led to difficulties in analytics and customer insights.<\/p>\n<\/div>\n AI is helping real estate firms make data-backed decisions faster than ever before. From predicting market trends to qualifying leads and automating documentation, AI is streamlining everything.<\/p>\n<\/div>\n One standout example of AI in action is the rise of intelligent property platforms, such asHousing.com. These platforms now use AI algorithms to analyse buyer behaviour, preferences, and search intent, enabling them to recommend properties more accurately and significantly reduce the time required to find a suitable home.<\/p>\n<\/div>\n In the commercial real estate sector, the potential is even more transformative. By strategically embracing AI, companies can optimise everything from space utilisation and lease management to predictive maintenance and investment planning. According to JLL\u2019s recent report<\/a>, over 90% of C-suite leaders believe AI will fundamentally change the way the workforce operates within the next five years.<\/p>\n<\/div>\nBanking: Smarter Services, Stronger Risk Management<\/strong><\/h2>\n
Real Estate: Faster Transactions, Smarter Investments<\/strong><\/h2>\n