Policy Recommendation Agent
Suggest insurance policies based on profile, finances, risk
Description
Challenge:
Customers and advisors often struggle to identify the right insurance policies that align with needs, risk profiles, and financial capacity. Manual selection can lead to unsuitable recommendations, compliance risks, and lower conversion rates. Without automation, advisors spend excessive time analyzing options and explaining product fit.
How It Works:
The Policy Recommendation Agent evaluates a user’s profile—including age, income, dependents, lifestyle, and coverage preferences—against available life, health, and critical illness products. It applies risk and affordability filters, regulatory suitability rules, and personalized goal mapping. The agent outputs a ranked list of suitable policies with transparent rationale, supporting advisors or self-service onboarding journeys.
Benefits:
65–80% higher accuracy in matching policies to customer profiles
25–40% improvement in lead-to-policy conversion rates
Reduces policy mismatch complaints to under 5%
Automates up to 70% of first-level advisory conversations in self-service channels
Personalized recommendations with transparent reasoning for informed decisions
Ensures regulatory compliance and suitability for every recommendation
Features
This agent provides intelligent, compliant, and personalized policy recommendations by analyzing user profiles, financials, and risk indicators, helping advisors and customers select the best-fit insurance products.
Features & Capabilities:
Data Intake: Collect customer age, income, dependents, goals, and lifestyle inputs
Policy Matching: Evaluate available plans across life, health, and critical illness segments
Risk & Affordability Filtering: Apply health, occupation, and lifestyle risk scores; enforce income-cover ratios and premium caps
Exclusion & Compliance Checks: Exclude incompatible plans or coverages based on regulatory or customer-specific criteria
Goal Fitment Logic: Match plans to financial objectives like child education, wealth accumulation, or protection needs
Rider Recommendation: Suggest optional riders such as critical illness or waiver of premium based on lifestyle/occupation
Duplicate Coverage Check: Avoid recommending policies the customer already holds
Output & Explanation: Generate ranked list of recommended policies with clear rationale for advisors or users
Operating Blueprint
Knowledge Sources:
Product Master Database (coverage terms, premium range, riders)
Customer Profiling Models (age, income, family size, liabilities)
Risk Assessment Models (health, occupation, lifestyle scores)
Regulatory Suitability Guidelines
Business Rules:
Affordability Check: Premium ≤ 10–15% of declared income
Cover-to-Income Ratio: Minimum 7x–10x income for life insurance
Health Condition Mismatch: Recommend medically underwritten policies for high-risk applicants
Exclusion Sensitivity: Include only compliant products for flagged coverages
Goal Fitment: Match plans to specific objectives (education, protection, investment)
Duplicate Coverage Check Prevent overlap with existing policies
Rider Suggestion Logic: Suggest CI, premium waiver, or other riders based on risk profile
Tool Workflow:
Collect Inputs: Gather customer details (age, income, goals, lifestyle)
Fetch Policies: Retrieve product catalog with eligibility and benefits
Score & Filter: Apply risk, affordability, exclusions, and goal-based filters
Generate Recommendations Produce top policy matches with explanations
Advisor/User Interface Display options for comparison and selection
Audit & Logging Record recommendation logic and rationale for compliance
Badges
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