Insurance Policy Administration AI Expert

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Quick Summary

Key Responsibilities

Design, develop, and implement AI-driven solutions to streamline end-to-end policy administration processes, including policy issuance, mid-term endorsements, and renewals.

Requirements Summary

Design, develop, and implement AI-driven solutions to streamline end-to-end policy administration processes, including policy issuance, mid-term endorsements, and renewals.

Technical Tools

OtherExpert

Requirements

~1 min read

Bachelor’s or Master’s degree in Insurance, Actuarial Science, Computer Science, Data Science, or a related field.
2–7 years of experience in insurance operations, policy administration, or AI/ML implementation in the insurance domain.
Strong understanding of policy lifecycle processes: issuance, endorsements, cancellations, and renewals.
Deep knowledge of insurance coverage structures, policy language, and risk interpretation.
Experience with AI/ML techniques such as Natural Language Processing (NLP), classification models, and rule-based systems.
Familiarity with regulatory and compliance frameworks (e.g., IRDAI guidelines, GDPR, or other regional insurance regulations).
Hands-on experience with data analysis tools (Python, SQL) and AI frameworks (TensorFlow, PyTorch, or similar).
Ability to translate business requirements into technical solutions and vice versa.
Strong problem-solving skills and attention to detail, especially in handling exceptions and edge cases in policy processing.

Experience working with Policy Administration Systems (e.g., Guidewire, Duck Creek, or similar platforms).
Exposure to intelligent document processing (IDP) and OCR technologies.
Understanding of underwriting principles and claims impact on policy structures.
Experience in implementing AI governance or model risk management frameworks.

Responsibilities

~1 min read

→ Design, develop, and implement AI-driven solutions to streamline end-to-end policy administration processes, including policy issuance, mid-term endorsements, and renewals.
→ Analyze and interpret complex insurance policy coverage, translating business rules into scalable AI/ML models and decision frameworks.
→ Collaborate with underwriting, operations, and compliance teams to automate policy workflows while maintaining high accuracy and auditability.
→ Build intelligent systems for document processing, policy validation, and exception handling using NLP, rule engines, and predictive models.
→ Enhance renewal strategies through data-driven insights, customer behavior analysis, and risk profiling.
→ Ensure AI systems align with regulatory requirements across jurisdictions, incorporating compliance checks into automated workflows.
→ Monitor model performance, accuracy, and bias, continuously improving systems based on feedback and evolving regulatory standards.
→ Support integration of AI solutions with policy administration systems (PAS), core insurance platforms, and third-party data providers.
→ Provide domain expertise in interpreting policy wording, exclusions, and coverage limits to ensure correct system outputs.