Indian Leaders Embrace AI in Corporate Treasury, 50% Rank Automation as Top Investment Priority

Indian treasury teams ranked automation as their top investment priority as per EY India Corporate Treasury Survey 2025. Based on responses from 85 treasury leaders, the survey shows that Indian treasuries are moving beyond their traditional role in cash and risk management, and now investing in AI-enabled transformation, talent upskilling, and shared services to prepare for the treasury of 2030. 

Top use cases of AI in treasury

Overall, 82% of organizations are either planning or actively progressing toward AI adoption. Use cases such as forex risk, trade finance, and anomaly detection are gaining traction. This shift indicates that Indian treasuries are moving from AI experimentation to execution, aiming to reduce operational bottlenecks, improve accuracy, and free up resources for strategic decision-making. 

Cash forecasting, where 26% of respondents are already piloting AI-led models, is becoming a high-impact application. Early-stage use cases in foreign exchange risk (9%), trade finance (8%), and working capital optimization (6%) reflect a growing ambition to integrate AI across core treasury processes, potentially unlocking efficiency, reducing errors, and supporting faster, data-driven decisions.

DBS Bank using AI in hedging

DBS Bank is using AI as a part of their hedging strategy. “We leverage DBS GPT, a customised generative AI tool deployed on top of our internal product and market research knowledge base. This has driven significant productivity improvements by providing teams with faster access to information, richer synthesis of research, and more informed decision-making. Additionally, AI-powered data analytics helps us analyse client transaction patterns, trade flows, and currency exposures to proactively recommend optimal hedging strategies. We also leverage AI-led automation to prepare indicative term sheets for hedging instruments—reducing manual effort, ensuring consistency, and improving turnaround times,” says Ramesh Mallya, Chief Technology Officer, DBS Bank India, speaking with FE CIO.

Reflecting on the findings, Hemal Shah, Partner and Leader, Treasury and Commodity Advisory – Risk Consulting, EY India, says, “Economic volatility, regulatory shifts, and rapid digitization are forcing treasury teams to do more with less – automate without losing control, manage risk while enabling growth, and deliver predictive, real-time insights for strategic decision making. Insights from our report show a major shift toward digitally intelligent treasuries. The majority are planning or deploying AI solutions across cash forecasting, trade finance, and risk management, and redesigning operating models. Future-ready treasuries will go beyond liquidity and compliance management to anticipate risks, shape capital allocation, and safeguard organizational resilience.” 

Key gaps identified

The survey also underscores critical areas that could hinder progress if left unaddressed:

• Over 70% of treasury teams still rely on disparate spreadsheets and disaggregated historical data, reinforcing that automation journeys are still in early stages

• Nearly two-thirds cite weak reporting and dashboarding, pointing to a gap in real-time visibility.

On the data front, DBS Bank is using ML for better insights across the customer lifecycle, "At DBS Bank India, our Global Financial Markets (GFM) team is embedding AI into the treasury function to strengthen insights, improve efficiency, and create data-driven opportunities. We use machine learning models that combine internal and external data to generate sharper business insights across the customer life cycle. This enables us to better understand client needs and proactively anticipate opportunities,” says Mallya.

The 2030 vision for treasury

Looking ahead, the report outlines that the treasury of 2030 will be digitally native, operating on real-time data and intelligent systems, staffed by cross-functional specialists fluent in finance, technology, and transformation. Organizations that invest in platforms, processes, and people will be able to anticipate risks, accelerate decision-making, and capture strategic opportunities faster than their peers.

DBS Bank plans to use the Agentic AI opportunity in the treasury department, “Looking ahead, we are evaluating Agentic AI to drive workflow automation in the treasury. This will allow us to move beyond insights and research support to fully automating repetitive tasks and streamlining processes, freeing up our teams to focus on higher-value, strategic activities. Through these initiatives, AI is helping us make our treasury more digitally native, agile, and future-ready—solving immediate challenges while also creating space for long-term innovation,” Mallya concludes.