How Agentic AI is transforming
financial services in India

Listen to our latest podcast on the economic shift of Agentic AI in financial services and it's role is transforming the financial services sector.

Key takeaways:

Agentic AI moves decisions from support to real-time orchestration.
Distributed intelligence drives fast, precise decisions in India’s complex, high‑volume financial system.
AI agents enable hyper‑personalized financial services by continuously reading customer signals and delivering real‑time, tailored insights.
Autonomous end-to-end workflow management reduces costs and improves turnaround time across onboarding, lending, claims and collections.
Greater autonomy in Agentic AI also necessitates accountability framework, explainability and continuous monitoring.

Agentic AI can autonomously manage end-to-end workflows such as onboarding, credit assessment, claims and collections. This reduces costs, improves turnaround time and supports hyper-personalized decisions. When combined with responsible use of data, it also strengthens financial inclusion by enabling institutions to serve customers who previously depended only on traditional credit scores.

Pratik Shah

Partner and National Leader – Financial Services, EY India

For your convenience, a full text transcript of this podcast is available on the link below:

Pallavi

Welcome to EY.AI Unplugged Season 2: AI Agents of Impact, a special series by EY India Insights. In this episode, ‘The economic shift of Agentic AI in financial services’, we examine how autonomous, decision-making AI systems are redefining the financial services ecosystem, from risk and compliance to customer engagement and capital allocation.

Our guest today is Pratik Shah, Partner and National Leader – Financial Services at EY India. Pratik works closely with banks, insurers and financial institutions on large-scale transformation programs, helping them navigate regulatory change, digital disruption and the adoption of advanced AI at an enterprise scale.

Pratik, a very warm welcome to you and thank you for joining us today.

Pratik Shah

Thank you, Pallavi.

Pallavi

Pratik, to begin with, how is Agentic AI reshaping the financial services ecosystem from autonomous risk assessment to intelligent portfolio management?

Pratik Shah

Agentic AI represents a fundamental evolution from traditional automation or predictive analytics. We are moving from AI that supports decisions to AI that can orchestrate decisions with well-defined guardrails. For example, in risk assessment, agentic systems can continuously monitor transactions, movements in the market, customer behaviors and regulatory signals and then act in real time by triggering controls, escalating issues, or rebalancing exposure.

What is important is that these agents now operate across systems, platforms, risk engines and compliance tools, enabling a more integrated and responsive financial ecosystem. The result is faster decision cycles, improved resilience and better alignment of risk, return and regulation. We are entering a very interesting regime where an end-to-end process uses Agentic AI rather than operating on a standalone basis.

Pallavi

Thank you, Pratik. In what ways does the rise of self-directed decision-making AI systems mark a fundamental shift in the structure and operation of India's financial economy?

Pratik Shah

This shift is structural, not incremental. India's financial economy has traditionally relied on centralized decision-making and human-intensive processes and controls. Agentic AI introduces a distributed intelligence model where decision authority is embedded very close to real events as they happen. Given India's scale, millions of customers, high transaction velocity and the diverse risk profile, an Agentic AI model becomes particularly powerful.

AI agents operate continuously across geographies, languages and customer segments, enabling financial institutions to respond with speed and precision, which was difficult earlier. At a macro level, as financial institutions scale, this becomes a very differentiated tool for them. Growth is no longer constrained by operational headcount or linear expansion. Instead, intelligence becomes scalable, allowing institutions to serve more customers, manage risk more dynamically and operate efficiently within guardrails and regulatory frameworks. It is a structural shift in how financial services institutions will operate.

Pallavi

Thank you, Pratik. Adding to the previous question, how can India's financial institutions leverage Agentic AI to unlock new sources of value, efficiency and inclusion in a fast-evolving marketplace?

Pratik Shah

There are three value levers. There is efficiency, personalization and an inclusion standpoint. Agentic AI can autonomously manage end-to-end workflows, from the time a customer is onboarded to credit assessment, claim processing, collections and other processes. There is a significant amount of cost that can be managed and turnaround time can be improved, purely from an efficiency standpoint. From a value creation standpoint, agents can be extremely hyper-personalized, whether offering financial products, doing credit underwriting, or providing investment advice on a real-time basis, given the risk profile and risk signal of a customer.

Again, this is a clear value driver. Then, perhaps most importantly, Agentic AI can drive financial inclusion because by analyzing alternate data sources responsibly and at scale, AI agents can help institutions serve the underbanked population, which was traditionally relying on credit scores. There is a lot of data that can be used and AI can use it to a much better advantage.

The key is that none of these are static. They can adapt as they understand customer behavior and profile, in addition to the evolving market. Clearly, those are the ways in which financial institutions will benefit in the future.

Pallavi

Thank you, Pratik. From a regulatory perspective, what role will governance and regulatory innovation play in ensuring that the autonomy of AI systems coexists with transparency, ethics and trust?

Pratik Shah

Governance is table-stakes; it is the defining factor for the success of Agentic AI or AI for that purpose. As AI gets autonomy, financial institutes must treat digital actors within the organization in the same way as any other employee, which means clear accountability framework, explainability by design and a very strong continuous monitoring process. So, controls will play a big role. Regulatory innovation, including principle-based guidelines, sandbox environments and outcome-focused supervision, will also become critical. India's regulatory ecosystem has already demonstrated an ability to balance innovation with stability and that will be tested as AI systems scale, trust will evolve over a period.

There has to be a deep-rooted understanding of what decisions the AI agents are making and how they make them, given the regulatory, ethical and business objectives in mind. That gets embedded as part of the governance process for financial services as they scale up more responsibly.

Pallavi

Thank you, Pratik. Lastly, as we move towards the AI-powered economy, what new leadership data and control models will financial firms need to adopt to responsibly harness Agentic AI?

Pratik Shah

As we move forward, leadership models will continue to evolve. Financial leaders must shift from overseeing processes to governing outcomes, which requires a very strong understanding of AI capabilities, its limitations and risk implications, right from the top of the house, at the board level to the executive level and then populated down to the organization. Data models will mature with a focus on quality, interoperability and how to manage biases? Control models will become a lot more dynamic. Instead of static rules, institutions will need adaptive controls that learn alongside AI agents and are supported by real-time auditability and a human in the loop. I think those who get this balance right and adopt AI at scale clearly differentiate themselves in the market, as financial services evolve across India.

Pallavi

Thank you. That brings us to the end of this episode. Thank you so much for joining us and sharing all those valuable insights.

Pratik Shah

Thank you, Pallavi.

Pallavi

Thank you to all our listeners; you have been listening to EY.AI Unplugged Season 2: AI Agents of Impact, a special series by EY India Insights. To explore more perspectives on how Agentic AI is reshaping industries and economies, visit ey.com/in.

Stay tuned as we continue to spotlight leaders driving AI with impact. Until next time, this is Pallavi signing off.

Presenters

Pratik Shah

Partner and National Leader – Financial Services, EY India

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Season 02 Episode 03

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9m 4s

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How Agentic AI is transforming
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Key takeaways:

Pallavi

Pratik Shah

Pallavi

Pratik Shah

Pallavi

Pratik Shah

Pallavi

Pratik Shah

Pallavi

Pratik Shah

Pallavi

Pratik Shah

Pallavi

Pratik Shah

Pallavi

Presenters

Pratik Shah

In this series

Presenters

Insights

Highlights

Services

Spotlight

Industries

Case studies

Careers

Spotlight

About us

Top news

How Agentic AI is transforming financial services in India

Key takeaways:

Presenters

Pratik Shah

In this series

Presenters

How Agentic AI is transforming
financial services in India