Enterprise Knowledge Automation Using LLMs for BFSI Clients

Overview

In the rapidly evolving BFSI (Banking, Financial Services, and Insurance) sector, the ability to harness enterprise knowledge at scale has become a strategic imperative. With the explosion of unstructured data—emails, reports, policy documents, customer interactions, and regulatory updates—financial institutions are struggling to extract actionable insights in real time.

DeltaDot AI partnered with a leading BFSI conglomerate to deploy a cutting-edge Enterprise Knowledge Automation solution powered by Large Language Models (LLMs). The goal was to transform fragmented institutional knowledge into a unified, intelligent layer that could support decision-making, compliance, customer service, and innovation.

Client Background and Challenges

The client is a diversified BFSI group operating across retail banking, insurance, asset management, and fintech. With over 50,000 employees and operations in 12 countries, the organization manages petabytes of data across legacy systems, cloud platforms, and third-party services.

Key characteristics of the client’s environment:

Data Silos: Knowledge trapped in departmental systems—CRM, ERP, DMS, and email archives.
Regulatory Complexity: Constantly evolving compliance requirements across jurisdictions.
Customer Expectations: Rising demand for personalized, real-time service across digital channels.
Operational Bottlenecks: Manual document processing, slow onboarding, and fragmented workflows.

Solution Highlights

DeltaDot AI proposed a modular Enterprise Knowledge Automation Platform powered by domain-tuned LLMs. The solution was designed to:

Ingest and index unstructured documents from multiple sources.
Enable semantic search and contextual Q&A using LLMs.
Automate document summarization and classification.
Integrate with existing workflows via APIs and secure connectors.
Ensure compliance with BFSI-grade security standards.

Business Impact

The Platform delivered measurable impact across multiple dimensions:

1. Operational Efficiency: 40% reduction in time spent searching for documents. 60% faster compliance update dissemination.

2. Improved Decision-Making: Real-time access to summarized insights. Contextual Q&A reduced dependency on senior staff.

3. Enhanced Compliance: Automated alerts for regulatory changes. Traceable knowledge trails for audits.

Conclusion

DeltaDot AI’s Enterprise Knowledge Automation solution transformed the client’s approach to information management. By deploying LLMs in a secure, explainable, and scalable manner, the BFSI organization achieved:

60% reduction in time spent searching for information.
40% improvement in customer query resolution accuracy.

This case study demonstrates how LLMs can be operationalized beyond experimentation—delivering tangible business value in regulated, data-intensive environments like BFSI.

Case Study