Mr. Laxman Doddipatla

Making Liquidity Management Smarter with AI in Modern Banking

Abstract:

In today’s fast-moving world of banking especially in the payments sector, it is critical for banks to always have enough funds on their settlement account. This is known as liquidity management. As banks handle a growing number of real-time payments, international money transfers, and stricter rules from regulators, the old ways of managing liquidity just aren’t fast or flexible enough anymore. They often rely on static processes that can’t keep up with the speed or complexity of today’s financial environment.

This is where Artificial Intelligence (AI) steps in as a powerful solution. AI technologies, especially machine learning and predictive analytics, can help banks improve how they manage their money throughout the day. By analyzing past transaction data, real-time payment flows, and even market trends, AI can forecast how much cash a bank will need and when they’ll need it. Instead of reacting to problems after they happen, banks can use AI to plan ahead.

For example, AI can automatically move funds between accounts at the right time, flag unusual activity that might signal risk, and make sure the bank uses its available funds in the most efficient way. This means less reliance on expensive borrowing and a lower chance of payment failures.

Using AI for liquidity processing makes the entire system smarter and more responsive. It helps banks operate more efficiently, reduces financial risks, and ensures they meet important regulatory requirements like the Liquidity Coverage Ratio (LCR). Overall, AI doesn’t just make the job easier—it helps banks adapt to the demands of a fast-changing global financial system, paving the way for more intelligent, agile, and secure operations.