The public release of ChatGPT in late 2022 sparked discussions on the durability and influence of generative AI. One year later, the conversation has changed from doubt to deliberate strategy in the banking industry. Although generative AI will not completely transform the fundamental operations of banking, it is positioned to transform the implementation of those tasks profoundly.

According to IDC's most recent estimate, Indian banks are expected to spend more than $1 billion on public cloud efforts by 2025, demonstrating the cloud's relevance in fostering technological transformation. At the policy level, the Union Budget 2022-23 includes increased capital expenditures to fund infrastructure projects. Some critical technologies being worked on include accelerating cloud adoption, heavily using AI, and improving data management efficiency.

According to an Accenture analysis, every function at every bank is expected to gain from generative AI. This study and their ongoing collaboration with premier banks worldwide have uncovered hundreds of intriguing use cases that span the banking value chain. From the back and middle offices to the tellers, advisers, relationship managers, and contact centre representatives in the front office, the ability of generative AI to automate mundane manual activities and improve humans' capacities will make a significant difference. 

Similarly, SBI proudly stated in its annual report (June 23) that it has used breakthrough technologies such as AI, machine learning (ML), and business analytics to extend its product offerings and boost customer satisfaction. The next iteration of SBI's YONO app will stress customer-centric design, hyper-personalized experiences, and novel product offerings by leveraging AI/ML. 

Likewise, ILA, the Interactive Live Assistant for SBI Cards, can provide the most relevant information about products and services. Anyone can learn about Card features, benefits, services, and much more by chatting with ILA. Their Generative Conversational AI system has also helped them generate over 130,000 leads to date, improving top-line revenue by thousands of dollars.

Global Examples of AI in Banking

• Capital One (Virginia)—The bank unveiled Eno, an AI-powered virtual assistant that consumers can use via mobile app, SMS, email, and PC. Eno manages credit card payments, account balances, credit checks, and transaction verification. This impressive banking AI also allows users to text inquiries and receive fraud alerts.
• Ally Financial(Michigan) - AI-powered chatbots on the bank's mobile platform serve customers with questions, transfers, payments, and payment summaries. The chatbot may handle banking demands via voice or text. 
• HSBC (Hong Kong)—HSBC Hong Kong released PayMe to revolutionize mobile payments. The bank's biggest challenge was rethinking and updating payment procedures utilizing old technology. The bank securely disseminated anonymized production data to data science teams in real time using Azure Databricks and Delta Lake. PayMe also helped the bank centralize its analytics process.

Conclusion

AI applications will significantly transform India's banking and financial services industry. They offer opportunities to enhance customer happiness, increase operational efficiency, manage risks, and foster innovation.

A crucial element of integrating AI into the banking industry is enhancing employee education and public awareness of the novel technology. With Indian Banks' apparent efforts and excitement, we can expect to see a dynamic ecosystem driven by AI change how services are delivered and structured.

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