What is Knowledge Management in Financial Services

Knowledge Management in Financial Services Defined
In an industry where regulatory complexity, customer expectations, and competition are intensifying, effective knowledge management (KM) becomes a critical enabler of differentiation for customer service excellence and operational performance.
Types of Knowledge in Financial Services
Financial institutions rely on various types of knowledge to operate successfully:
Data
- What is the 5-year return of mutual fund X?
- What is the current rate for a $50K home equity loan?
- What transactions have I made in the past 90 days?
- What is the current value of my portfolio?
Policies
- What are the lending guidelines for small business loans?
- Do you have a grace period for monthly loan repayment?
- What is your policy on borrowing money from my 401K account?
Insights
- What customer segments have been defaulting the most on mortgages?
- What customer segments are likely to take up offers on high-touch asset management and which ones are likely to be happy with just automated asset management?
- What mutual funds will benefit from an environment of tariffs?
Procedures
- What are the required steps to onboard a new business client from start to finish?
- How should I handle a payment dispute for a credit card transaction?
- What steps should I follow when a transaction triggers our fraud detection protocols?
Expertise
- What investment options can you recommend based on my risk tolerance and financial goals?
- How should we interpret the latest regulatory update from the SEC in the context of our advisory operations?
- What should I do to mitigate portfolio risk in volatile market conditions?
- What additional service should I offer to increase customer stickiness?
Knowledge Management in Financial Services: Challenges
- Knowledge siloes: Data and content siloes create chaos both in the frontline and the backoffice, making it difficult to maintain them while delivering trusted answers that are correct, consistent, and compliant and helping make sound decisions. In fact, 44% of consumers are frustrated that banks give them different answers for the same question, depending on whom you talk to and which channel you contact the bank through, according to a major consumer survey, conducted by Dimensional Research.
- Regulatory Pressures: Financial institutions are constantly navigating a sea of evolving regulations. The pace of regulatory change—often reactive to market shifts, security breaches, or political developments—makes it challenging to keep knowledge accurate and current across departments. According to the Financial Times, US banks alone paid over $200 billion in compliance-related fines over the past 20 years.
- Customer Expectations: As routine customer queries are handled by self-service, contact center agents and retail bankers face more complex questions. In fact, 53% of contact center agents in the financial services industry confirmed it in BenchmarkPortal’s agent survey. Customers expect frontline staff to provide them value-added advice whether it comes to credit cards to get or loans to secure or even long-lived advice on how to improve their finances. This calls for proactive AI knowledge pushed in the flow of conversations and backoffice work, not just siloed data and documents.
How AI Can Help
Spending on AI in the financial services sector is projected to grow at 29% annually, rising to $97 billion in 2027. Increased spending can be directly attributed to the power of AI to transform nearly every aspect of financial services operations from anti-money laundering to digital and call center customer service. Here are some of the ways that AI-powered KM platforms, like eGain’s, are being used to transform financial services operations:
- Automated Knowledge Capture & Curation: Use AI to continuously capture knowledge and insights from email threads, call transcripts from the best agents, and internal chats with trusted subject matter experts.
- Compliance Enforcement at Scale: AI-powered knowledge management allows financial services organizations to embed policy and regulatory checks directly into day-to-day workflows. This ensures frontline staff deliver trusted responses every time, while also alerting knowledge managers to outdated, conflicting, or non-compliant content before it reaches the front lines.
- AI-Powered Decision Support: Agentic AI systems can guide frontline teams through customer conversations by offering real-time reasoning and recommendations. The result is compliant, high-quality conversations, stronger outcomes, and measurable gains in customer satisfaction, revenue, and operational performance.


Knowledge Management in Financial Services: Best Practices for Success
Here are best practices for deploying successful KM in financial services:
- Consolidate trusted knowledge into a unified hub: Break down departmental silos by centralizing policies, procedures, FAQs, and institutional expertise into a structured, AI-powered knowledge hub. The hub can also federate trusted content that resides in external sources.
- Ensure regulatory compliance with your KM system: Use AI-powered knowledge solutions to enforce version control, maintain audit trails, and implement approval workflows. This minimizes risk and ensures that every piece of knowledge adheres to current regulations and internal policies.
- Partner with proven vendors: KM is more than just technology. Being successful requires domain expertise on the part of vendors which many companies (e.g., startups) lack.
- Foster Knowledge-Sharing Culture: Encourage knowledge sharing among employees through incentives, gamification, and evangelism.
- Ensure adoption: Train frontline employees to use the KM tool rather than hunt for answers.
- Measure value and communicate—It is important to measure KPIs such as call deflection, first contact resolution, speed to competence and compliance—and communicate to key stakeholders to sustain momentum. In parallel, use AI to analyze customer and employee feedback to uncover emerging needs, flag knowledge gaps, and drive ongoing content refinement.
Knowledge Management in Financial Services: Success Stories
- Multinational Financial Services Leader: By implementing the eGain AI knowledge hub, which provided conversational AI guidance to their frontline staff, the client achieved a 36% boost in First Contact Resolution and cut agent training time by 40%, while improving CX.
- Top-10 Global Bank: With proactive knowledge delivery and personalized AI guidance, this client increased advisor productivity by 15%, empowering them to deliver faster, more informed service across every interaction.
Knowledge Management in Financial Services: Conclusion
eGain’s risk-free pilots for the eGain AI Knowledge Hub and the eGain AI Agent provide a low-risk way for financial services organizations to start their transformation journey.