Concrete Examples of Enterprise GenAI in BFSI

From compliance to client experience, Enterprise AI is actively reshaping how financial institutions operate, serve, and scale. But what does real-world AI deployment actually look like in the BFSI world?

Let’s break it down.👇

Use Case Spotlight: Supercharging Client Advisor Onboarding

New financial advisors typically take months before they’re ready to add value. But in a market that’s losing experienced advisors faster than it’s gaining new ones, speed is survival.

Here’s how Enterprise GenAI flips the script—turning long onboarding cycles into short, strategic sprints.

Challenge: Training new hires quickly without sacrificing compliance or knowledge depth. Specific areas of improvement the highlight include: 

• Client meeting preparation
• Financial proposal creation
• Day-to-day operations, administration, and compliance management
• Investment research

Solution: Squirro’s GenAI platform, powered by your institution’s proprietary data.

Result: New advisors up to speed in weeks—not months

Real Example: Meet Mark, a New Client Advisor

Mark is tasked with advising a client on rolling over a 401(k)—a multi-step and complex process even for seasoned professionals. With Squirro Enterprise GenAI platform, here’s how Mark succeeds: (See the full interactive demo here)

• Search for information: Mark can use the search bar to access all of the bank's internal documents.
• Retrieve relevant documents: The semantic search accurately retrieves the most relevant documents quickly.
• Go directly to relevant paragraphs: Clicking on a document directs Mark to the most relevant section, saving time during the client meeting.
• Generate summaries: Mark can quickly extract the key points from automatically generated summaries of documents rather than having to read them from cover to cover.
• Ask follow-up questions: Mark can ask follow-up questions to the documents, in the same way that he would interact with a senior mentor.
• Ensure compliance: AI guardrails ensure that outputs are compliant with company and regulatory requirements.
• Create an email summary: Finally, Mark can create an email summarizing the main takeaways of the client meeting to share with the client and his superiors.

This isn’t theory—it’s enterprise AI in action. And it’s happening now.

🔐 Secure, Private, and Accurate AI-Driven Enterprise Intelligence at Scale with Squirro

While many enterprise GenAI providers claim to have met these demands, the scarcity of production-scale enterprise GenAI deployments suggests otherwise. 

At Squirro, we have over a decade serving financial service providers, central banks, and other organizations in highly regulated sectors – initially with enterprise search solutions and now leading the charge in enterprise GenAI. 

Privacy: For GenAI in BFSI, privacy isn't optional, it's foundational. This means rigorous protection of Personally Identifiable Information (PII) and strict enforcement of Access Control Lists (ACLs). A robust privacy layer is essential to prevent PII exposure during AI processing. ACLs are equally crucial, ensuring only authorized personnel can access specific data, maintaining confidentiality and meeting stringent regulatory demands.

Security: Security is another pillar. BFSI GenAI must adhere to the highest standards, including ISO 27001, and employ robust encryption to safeguard sensitive data. Secure deployment options are key, such as on-premises setups or single-tenant Virtual Private Clouds (VPCs), to ensure data residency and control. Crucially, the flexibility to choose and change Large Language Models (LLMs) allows organizations to adapt to evolving security threats and data residency regulations.

Accuracy: Accuracy is non-negotiable when dealing with financial decisions. Semantic knowledge graphs are the answer. By integrating deep domain knowledge and complex process flows, they enrich data completeness, drastically reduce AI “hallucinations,” and enable deterministic data retrieval, eliminating ambiguity. Knowledge graphs also offer full data lineage, providing transparency into how insights are generated and bolstering the trustworthiness of AI applications.

Flexibility: GenAI isn't deployed in a vacuum. BFSI needs solutions that integrate seamlessly with existing infrastructure. LLM-agnostic enterprise AI platforms are vital. They connect effortlessly to existing data sources and workflows, allowing for LLM flexibility and model mixing tailored to specific needs. This approach maintains control over security, cost, and performance and builds future-proof solutions that can evolve.

Scalability: Scaling GenAI in BFSI must be seamless without sacrificing privacy, security, accuracy, or cost-efficiency. Many organizations struggle with scalability when building AI in-house. While many enterprise-ready SaaS AI platforms promise fast deployment and security, few vendors have proven their ability to deliver permission-enabled and production-scale GenAI in this demanding sector. We have. 

Ready to See What’s Possible for You?

Download our in-depth guide: Transforming Banking & Financial Services With Enterprise GenAI Inside, you’ll find actionable use cases—from advisor enablement to compliance automation—and practical strategies for scaling GenAI safely and successfully in your organization.

🔗 Download the Guide here: https://squirro.com/generative-ai-in-financial-services

👀 Want to see the platform in action? Book a demo with us today

Recognized by Gartner as a visionary company, Squirro stands at the forefront as an enterprise-ready generative AI solution for search, insights, and automation. Our clientele includes prestigious organizations such as:  the European Central Bank, the Bank of England, Henkel, Mubadala.

Thank you for being part of our journey. Stay tuned for more updates as we continue to bridge the AI reality gap!