What is Knowledge Management in Insurance
AI Customer Service Software: Knowledge Management in Insurance Explained
Knowledge Management in insurance is defined as capturing, organizing, and disseminating knowledge–both explicit (e.g., policy documents and procedures) and tacit (e.g., underwriting best practices and claims handling insights).
In the competitive landscape of Property & Casualty (P&C) insurance, effective knowledge management (KM) is crucial for operational efficiency, regulatory compliance, and member satisfaction. As insurers undertake AI transformation, strong KM practices become essential to deliver trusted answers, ignite adoption, and generate business value.
AI Customer Service Software: Types of Knowledge in P&C Insurance
Here are examples of the types of knowledge in the context of P&C insurance:
Data
Information that supports reporting, benchmarking, and automation.
- What is my annual premium and when is it due?
- How many more years are left in my life insurance policy?
- What are the loss ratios by product line and region?
- What is the average time to close a standard auto claim?
- How many quotes are converted to bound policies each quarter?
Insights
Aggregated knowledge derived from data analysis and cross-functional expertise, often used for decision support.
- Which customer segments show the highest retention or cross-sell rates?
- How do weather trends correlate with claims spikes across different geographies?
- What patterns emerge from denied claims that could improve policy design?
- What channels do small business owners prefer for quoting and servicing?
Policies
Rules and frameworks that define how business is conducted to ensure compliance and consistency.
- State-by-state regulatory compliance checklists
- Claims escalation policies and adjuster authority levels
- Knowledge governance and content lifecycle policies (e.g., review frequency, versioning)
Procedures
Documented workflows and step-by-step actions.
- How to conduct first notice of loss (FNOL) intake
- Steps for broker onboarding and credentialing
- How to apply catastrophe coding during claim triage
Expertise
Tacit knowledge based on experience, often undocumented and difficult to transfer without intentional KM practices.
- How do senior adjusters assess liability in complex multi-party accidents?
- What questions help uncover under-disclosed risks during commercial underwriting?
- How do experienced agents build trust with skeptical first-time buyers
AI Customer Service Software: Knowledge Management in Insurance: Challenges
Despite its importance, KM in P&C insurance sector faces several challenges:
- Siloed information: Disparate systems and departments often lead to fragmented knowledge repositories, resulting in obsolete information and conflicting answers.
- Legacy systems: 37% of frontline insurance agents don’t have a knowledge base to get answers and an additional 27% struggle with basic keyword search to get them, according to a BenchmarkPortal Agent Experience survey. No wonder 84% of frontline agents hate their desktop tools, per Gartner!
- Workforce turnover: The retirement of experienced professionals, triggered by corporate layoffs and baby boomer retirements, is creating a crisis of knowledge exodus in all industries, insurance included.
AI Customer Service Software: How AI Can Help KM for Insurance Carriers
KPMG reports that 57% of insurance organizations view AI as the most important technology for achieving their ambitions over the next three years. (KPMG) A modern knowledge management system, paired with AI can:
- Automate knowledge: AI can help automate the long-standing challenge of knowledge discovery, creation, curation, publication, and optimization. However, it needs to draw from trusted content to ensure correct, consistent, and compliant answers.
- Enhance information retrieval: AI-powered search capabilities can quickly surface relevant information from large data sets.
- Provide predictive analytics: Machine learning algorithms can identify patterns and predict outcomes, aiding in risk assessment and fraud detection.
- Personalize knowledge: AI can tailor information dissemination based on user roles and needs, improving efficiency.
AI Customer Service Software: Knowledge Management in P&C Insurance: Best Practices for Success
To optimize KM, P&C insurers should consider the following best practices:
- Develop a unified KM-AI strategy: Synchronize and integrate your KM and AI strategy to ensure success.
- Invest in modern KM Tools: Evaluate if the tool leverages and orchestrates AI with trusted content to deliver reliable answers to users.
- Foster a knowledge-sharing culture: Encourage employees to share insights and document best practices.
- Train workers on tools and not tasks: Provide ongoing education to ensure employees are adept at using KM systems effectively.
AI Customer Service Software: Knowledge Management in P&C Insurance: Success Stories
A mid-sized UK insurance provider is outgrowing the competition by reimagining member experience on our knowledge-powered customer engagement platform, while keeping a firm lid on cost of service.
