Key Responsibilities and Required Skills for Insurance Analyst

🎯 Role Definition

As an Insurance Analyst, you will apply analytical rigor, insurance domain knowledge, and data tools to evaluate policies, claims, pricing and risk. You will synthesize quantitative and qualitative information to support underwriting decisions, pricing strategy, claims reserving, loss mitigation and regulatory reporting. The role requires strong technical skills (Excel, SQL, BI tools), insurance product knowledge (personal, commercial, specialty), and the ability to translate complex analysis into clear recommendations for underwriters, actuaries, product owners and business leaders.

📈 Career Progression

Typical Career Path

Entry Point From:

Claims Processor / Claims Examiner with intermediate claims exposure.
Junior Data Analyst or Business Analyst supporting insurance teams.
Underwriting Assistant or Policy Administration Specialist.

Advancement To:

Senior Insurance Analyst / Lead Insurance Analyst.
Underwriting Manager or Pricing Manager.
Risk Manager, Product Manager, or Actuarial Analyst.

Lateral Moves:

Product Analyst for insurance propositions.
Compliance or Regulatory Reporting Analyst.
Business Intelligence / Data Analytics roles in insurance operations.

Core Responsibilities

Primary Functions

Analyze large sets of policy, claims and premium data to identify frequency and severity trends, loss drivers, and emerging risks; produce actionable insights that influence underwriting strategy and pricing decisions.
Develop, validate and maintain pricing models and rate indications (GLMs, generalized linear models, or rule-based pricing) in collaboration with actuarial and underwriting teams to improve profitability and market competitiveness.
Prepare detailed monthly and quarterly management reports, including loss ratios, combined ratios, reserve adequacy, premium growth, and underwriting profitability by product, segment and distribution channel.
Conduct reserving support by producing loss reserve analyses, validating claim reserves, and reconciling actuarial reserve outputs with finance and claims data to ensure accurate financial reporting.
Perform claims analytics to identify unusual claim patterns, potential fraud indicators, high-cost claim segments and escalation triggers; recommend operational changes to claims workflow and fraud controls.
Execute portfolio-level risk assessments and stress tests to quantify exposure concentrations, catastrophe scenarios and reinsurance attachment points, and advise on reinsurance program design and placement.
Design, implement and maintain KPI dashboards and scorecards in Power BI, Tableau or equivalent to provide real-time visibility into underwriting performance, claims trends and operational metrics.
Conduct pricing and profitability segmentation by product line, geography, broker/agent, and customer cohort to identify growth opportunities and optimize retention strategies.
Lead underwriting guideline reviews by answering data-driven questions about past performance, recommended rating changes, and underwriting criteria improvements to reduce leakage and improve selection.
Perform premium audits and revenue reconciliations for complex commercial accounts; work with policy administration systems to correct billing and rating discrepancies.
Collaborate with actuaries and finance to align pricing assumptions, reinsurance recoverable estimates, ceded premium accounting and GAAP/IFRS reserving implications.
Prepare regulatory and external reporting packages, ensuring accuracy and timely submission for rate filings, statutory reporting and solvency requirements.
Validate and cleanse third-party vendor datasets (exposure, claims, geo, credit) and map source systems into the analytics environment; document transformations and assumptions to maintain data integrity.
Conduct ad-hoc deep-dive analyses (e.g., new product launch, competitor benchmarking, loss triangle analysis) and present findings to senior leadership with clear recommendations and implementation plans.
Build and maintain underwriting and claims-related forecasting models (short-term and long-term), incorporating seasonality, economic indicators, and portfolio movement to support budgeting and capital planning.
Establish and maintain model governance documentation, including methodology write-ups, data source inventories, validation results and sensitivity testing outputs for internal audit and regulatory scrutiny.
Support pricing submission and rate filing preparation by compiling loss exhibits, actuarial justification, comparative rate analyses and responses to regulator inquiries.
Partner with IT and data engineering to define data requirements, improve data pipelines, and automate repetitive reporting tasks to accelerate time-to-insight.
Drive process improvement initiatives in underwriting and claims operations by testing hypotheses with controlled experiments, quantifying ROI and scaling successful changes across regions.
Mentor and coach junior analysts, review their deliverables for accuracy and clarity, and help establish best practices for reproducible analysis, documentation and presentation.
Evaluate new product opportunities and coverage endorsements by performing profitability projections, competitor analysis and regulatory feasibility assessments.
Coordinate with compliance and legal teams to ensure that underwriting and pricing practices adhere to state and federal insurance regulations and anti-discrimination guidelines.
Prepare executive-level presentations that translate technical analysis into business impact, including recommended actions, estimated benefits, timelines and required resources.
Monitor key market indicators, competitor actions and regulatory changes to adjust underwriting strategies and pricing tactics proactively.
Support audit, SOX controls and internal review processes related to analytics, data access and model controls, including remediation tracking and evidence preparation.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.
Document business rules, rating logic and data lineage to improve transparency and handoffs between underwriting, actuarial and IT.
Assist in vendor selection and performance monitoring for analytics, data services and fraud detection platforms.
Participate in cross-functional project teams for system implementations (policy admin, claims management, billing) to ensure analytic requirements are met.

Required Skills & Competencies

Hard Skills (Technical)

Advanced Excel (pivot tables, INDEX/MATCH, advanced formulas, Power Query) for data manipulation and analysis.
SQL (writing optimized queries, joins, window functions) for extracting and aggregating policy and claims data from relational databases.
Experience with BI and dashboard tools (Power BI, Tableau, Looker) to build operational and executive reporting.
Familiarity with statistical software and programming languages (R, Python, SAS) for modeling, segmentation and automation.
Understanding of insurance-specific systems and data models (policy administration systems such as Guidewire, Duck Creek; claims management systems).
Knowledge of actuarial concepts, loss reserving methods, premium rating, exposure measurement and reinsurance mechanics.
Experience building and validating pricing and forecasting models (GLM, time series, machine learning models for claim frequency/severity).
Data engineering fundamentals: ETL processes, data validation, data governance and basic knowledge of cloud data platforms (Snowflake, BigQuery, AWS Redshift).
Reporting and regulatory filing experience, including compiling exhibits for state filings and statutory reporting.
Familiarity with accounting and financial reporting implications in insurance (GAAP, IFRS, ceded vs. written premium reconciliation).
Proficiency with visualization best practices and translating analytic results into clear dashboards and presentations.
Experience with fraud detection tools and techniques (rule-based and predictive analytics).

Soft Skills

Strong analytical and critical thinking skills with the ability to translate complex data into actionable business recommendations.
Clear and concise communication skills — able to present technical findings to non-technical stakeholders and executives.
Stakeholder management and cross-functional collaboration experience; comfortable working with underwriting, claims, actuarial, finance and IT.
High attention to detail and a disciplined approach to documentation and auditability.
Problem-solving mindset with creativity to design experiments and test operational hypotheses.
Time management and prioritization skills; able to handle multiple analyses and competing requests in a fast-paced environment.
Adaptability and continuous learning orientation to stay current with insurance market trends and analytic techniques.
Ethical judgment and compliance awareness when handling sensitive customer and claims data.
Coaching and mentoring ability to grow junior talent and improve team analytic maturity.
Project management capability to drive analytics projects from scoping through delivery and measurement.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Finance, Economics, Mathematics, Statistics, Actuarial Science, Computer Science, Business Analytics or a related quantitative field.

Preferred Education:

Master’s degree in Actuarial Science, Data Science, Statistics, Finance, or MBA.
Professional designations such as CPCU, ASA/ACAS, CERA, or relevant industry certificates (Data Analytics, SQL, Power BI).

Relevant Fields of Study:

Actuarial Science
Statistics / Applied Mathematics
Finance / Economics
Data Science / Analytics
Business / Risk Management

Experience Requirements

Typical Experience Range:

2 to 5 years of progressive experience in insurance analytics, underwriting analytics, claims analysis, pricing, or actuarial support.

Preferred:

3 to 7 years of experience with demonstrated impact on pricing, reserving, claims outcomes or process improvements; experience in commercial lines, personal lines or specialty insurance depending on role focus.
Prior exposure to policy administration systems, regulatory filings, and model governance frameworks is highly desirable.
Proven track record of delivering dashboards, analytics products, or pricing recommendations that influenced business outcomes (improved retention, reduced loss ratio, optimized pricing).