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GenAI Opportunity in the Financial Services Sector

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TL;DR:

Generative AI is rapidly transforming the financial services sector by enabling conversational and multimodal banking, smarter sales and credit decisions, and large-scale automation. As highlighted by Pratik Shah of EY India, GenAI agents already handle millions of customer interactions, power AI copilots for relationship managers, accelerate underwriting through sentiment analysis and financial spreading, and automate workflows across sales, collections, and operations. These use cases deliver measurable gains in customer experience, decision quality, and operational efficiency, positioning GenAI as a core capability for banks, NBFCs, and fintechs scaling digital-first financial services.

Podcast summary featuring Pratik Shah, Partner and National Leader – Financial Services, EY India

Generative AI has moved from experimentation to execution in financial services. In this episode, Pratik Shah shares how banks, NBFCs, and fintechs are using GenAI to reshape customer engagement, decision-making, and operational scale. The shift centers on conversational experiences, faster credit workflows, and large-scale automation that directly impacts productivity.

The Rise of Conversational and Multimodal Banking

Financial services interactions are evolving toward conversational and multimodal experiences. Customers increasingly expect to speak, type, or interact contextually with their bank through digital channels.

GenAI-powered agents can:

→ Engage customers in natural conversations inside banking apps

→ Offer investment guidance based on user inputs

→ Execute transactions in real time after customer confirmation

This model transforms the banking app into an intelligent advisor rather than a static interface. The result is higher engagement and a more intuitive customer experience.

GenAI at Scale: Automation of Customer Interactions

One of the strongest signals of GenAI’s maturity comes from scale. A US-based fintech used AI to handle 2.3 million customer interactions in a single month, reducing dependency on around 700 human agents.

This demonstrates how GenAI:

→ Handles high-volume, repeatable interactions reliably

→ Maintains service quality while improving response speed

→ Creates measurable efficiency gains across operations

At this scale, AI-driven service models move from cost optimization to structural transformation.

Sales Enablement Through AI Copilots

In sales functions, GenAI acts as a real-time copilot for relationship managers. These systems support assisted sales journeys by:

→ Explaining product features contextually

→ Capturing customer intent and interactions automatically

→ Supporting consistent, compliant communication

Sales teams gain higher productivity, while customers receive clearer and more personalized conversations.

Smarter Credit and Underwriting Decisions

Credit assessment represents another high-impact GenAI use case. By applying sentiment analysis and automated financial spreading, GenAI can generate credit assessment memos faster and with greater consistency.

This approach:

→ Shortens underwriting turnaround time

→ Improves information synthesis from structured and unstructured data

→ Allows underwriters to focus on decision quality rather than manual preparation

GenAI strengthens decision support rather than replacing human judgment.

Agent-Less Collections and Service Operations

Sales and collections emerge as strong conversational AI use cases. Over time, GenAI-powered systems handle a growing share of outbound and inbound interactions, driving productivity across call center operations.

As conversational maturity increases, financial institutions move closer to largely autonomous service workflows, especially for routine and policy-driven interactions.

Enterprise-Wide Productivity Through Workflow Automation

Beyond customer-facing use cases, GenAI automates internal workflows and manual processes. This includes:

→ Document generation

→ Process orchestration

→ Exception handling support

Automation at this level delivers compounding efficiency gains across departments.

What This Means for Financial Institutions

Financial services organizations are actively deploying multiple GenAI use cases in parallel. The focus areas remain consistent:

→ Better customer experience

→ Higher operational efficiency

→ Faster decision cycles

According to the discussion, adoption velocity continues to increase, signaling a rapid transition from pilots to production-grade systems.

Key Takeaways from the Podcast

→ Conversational and multimodal banking represents the next interface shift

→ GenAI already operates at multi-million interaction scale

→ Sales, credit, and collections lead early adoption

→ Productivity gains come from both customer-facing AI and internal automation

→ Financial services GenAI adoption continues to accelerate rapidly

Citation

This blog summary is based on insights from the podcast “GenAI opportunity in the Financial Services Sector” featuring Pratik Shah, Partner and National Leader – Financial Services, EY India. The discussion explores how Generative AI is driving transformation in financial services through conversational banking, smarter decision-making, and large-scale automation, reshaping customer experience and operational efficiency at scale. Original podcast available at: GenAI opportunity in the Financial Services Sector

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