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AI Tools for Insurance Data Analysts
AI tools that help insurance data analysts build loss triangles, track market trends, research economic indicators, and generate shareable charts and reports for underwriters and actuaries.
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Combined Ratio (%)
Macro economic indicator analysis
Pull GDP, inflation, interest rate, and unemployment data to model how economic cycles affect loss frequency, severity, and investment income. Build data-backed arguments for pricing changes using World Bank and FRED economic series.
Pull US CPI inflation, 10-year Treasury yields, and unemployment rates for the last 15 years. I need to model the relationship between inflation and workers comp claim severity.
Retrieved 3 series from FRED: CPI (2010–2024), 10Y Treasury (2010–2024), and unemployment. Strong correlation (r=0.71) between CPI spikes and lag-2 workers comp severity increases visible in 2021–2023.
ToolRouter get_indicator
CPI Inflation (%)
10Y Treasury (%)
Unemployment (%)
Carrier performance benchmarking
Extract and compare loss ratios, expense ratios, combined ratios, and catastrophe loads from public carrier filings. Benchmark your company's performance against peers and identify where pricing or reserving diverges from market norms.
Pull the last 4 quarters of combined ratio and cat loss data from 10-Qs for Travelers, Hartford, and Chubb.
Extracted from SEC filings: Travelers avg combined ratio 97.2%, Chubb 88.4%, Hartford 103.1%. Cat losses as % of NEP: Travelers 3.1%, Chubb 2.2%, Hartford 4.8%. Hartford's elevated cat ratio is driven by convective storm activity.
ToolRouter search_filings
CarrierQ1 2025Q2 2025
Travelers96.1%98.4%
Chubb87.2%89.1%
Hartford101.4%104.8%
Source: SEC EDGAR 10-Q filings · cat losses Travelers 3.1% / Chubb 2.2% / Hartford 4.8% of NEP
Insurance market trend research
Research hard market trends, reinsurance capacity changes, catastrophe model updates, and regulatory changes affecting your lines of business. Feed your pricing and reserving models with current market intelligence.
Research the current state of the US homeowners insurance market. What is driving rate increases, carrier exits, and availability issues in coastal states?
Compiled a 12-source report. Key drivers: reinsurance cost increases of 30–50% at Jan renewals, increased convective storm frequency, assignment of benefits litigation in Florida, and climate model updates increasing modeled expected losses by 15-25%.
ToolRouter research
Reinsurance cost increase
30–50% at Jan 2025 renewals — primary driver of premium increases
Convective storm frequency
Non-hurricane severe weather claims up 28% YoY nationally
AOB/litigation reform
Florida AOB reform 2022–2023 reducing but not eliminating litigation inflation
Climate model updates
RMS/AIR modeled expected losses increased 15–25% in 2023 revisions
Carrier capacity
14 carriers exited FL; 6 exited CA since 2022 — availability crisis
Chart and visualization generation
Turn raw loss data, pricing models, and actuarial outputs into professional charts for management presentations, board reports, and underwriter briefings. Generate bar charts, trend lines, and scatter plots without needing a BI tool.
Create a grouped bar chart comparing our personal auto, homeowners, and commercial auto loss ratios for 2021, 2022, 2023, and 2024 YTD.
Generated grouped bar chart for 4 years across 3 lines. Personal auto shows a consistent improvement trend from 108% (2021) to 87% (2024 YTD). Commercial auto remains elevated at 95%.
ToolRouter create_chart
Personal Auto
Homeowners
Commercial Auto
Natural catastrophe exposure research
Research earthquake, hurricane, wildfire, and flood risk for specific geographic exposures. Integrate with economic loss data to stress-test reserves against realistic catastrophe scenarios.
Research insured loss estimates from the top 10 costliest US natural catastrophe events in the last decade. I need this for a catastrophe model calibration exercise.
Compiled data on 10 events. Hurricane Ian (2022): $60.7B insured losses. California Camp Fire (2018): $12.5B. Winter Storm Uri (2021): $18.5B. Full table with event details, modeled vs actual loss comparisons, and industry cat model performance.
ToolRouter research
EventYearType
Hurricane Ian2022Hurricane
Winter Storm Uri2021Winter storm
CA Camp Fire2018Wildfire
Hurricane Harvey2017Hurricane/Flood
Hurricane Irma2017Hurricane
10 events compiled · total $214B insured losses across decade
Academic and regulatory research
Find peer-reviewed research on actuarial methods, loss reserving techniques, and regulatory requirements. Source credible references for pricing papers, ORSA submissions, and reserve opinions.
Find recent academic papers on gradient boosting and neural network applications for P&C insurance pricing, published in peer-reviewed journals in the last 3 years.
Found 17 relevant papers. Key themes: GLM vs GBM comparison studies (8 papers), telematics-based pricing (4 papers), and deep learning for image-based claims (5 papers). Top-cited: Blier-Wong et al. (2022) on neural network credibility.
ToolRouter search_papers
Papers found
17 peer-reviewed papers (2022–2025)
GLM vs GBM
8 comparison studies — GBM consistently outperforms GLM on RMSE
Telematics pricing
4 papers — driving behavior features most predictive of frequency
Deep learning
5 papers on image-based claims (vehicle damage, property loss)
Top citation
Blier-Wong et al. (2022) — neural network credibility theory
Ready-to-use prompts
Pull economic indicators
Retrieve US CPI, PCE inflation, and 10-year Treasury yield data from FRED for the last 10 years. Format as annual averages for each metric.
Chart loss ratio trends
Create a line chart showing the US personal auto combined ratio from 2015 to 2024. Add a dashed line at 100% to mark the break-even threshold.
Research market hardening
Research the key drivers of commercial property rate hardening in 2023–2024. Include reinsurance capacity changes, catastrophe experience, and carrier actions.
Extract carrier financials
Search SEC EDGAR for Progressive Corporation's most recent 10-Q. Extract net earned premium, combined ratio, and catastrophe losses for the most recent quarter.
Find academic research
Find peer-reviewed papers on machine learning methods for insurance claims reserving published since 2021. Focus on chain-ladder alternatives.
Research cat losses
Summarize US insured catastrophe losses by event for the most recent full year. Include hurricane, tornado, wildfire, and winter storm subtotals.
Get GDP data
Retrieve GDP growth rates for the US, UK, Germany, and Japan for the last 10 years. I need this to model the relationship between economic growth and commercial lines premium growth.
Monitor news for pricing signals
Search for insurance market news from the last 30 days covering rate changes, carrier withdrawals, and reinsurance market updates.
Tools to power your best work
World Economy16000+ World Bank indicators & data
Earthquake MonitorLive & historical earthquake data
Generate ChartTurn data into chart images fast
SEC FilingsSEC EDGAR filings & financial data
Deep ResearchAI research reports with citations
Finance DataMarkets, rates, commodities & macro
NewsSearch and track news worldwide
165+ tools.
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Everything insurance data analysts need from AI, connected to the assistant you already use. No extra apps, no switching tabs.
Annual pricing review package
Compile the economic context, competitive benchmarks, and catastrophe loss data needed to support annual pricing reviews across commercial lines.
Catastrophe exposure review
Build a data package for a natural catastrophe exposure review: recent events, economic losses, and model performance.
Reserve adequacy benchmarking
Compare your reserve development patterns against industry peers using public filings and economic context.
Frequently Asked Questions
What economic data sources does the World Economy tool use?
World Economy pulls from World Bank open data and FRED (Federal Reserve Economic Data), covering over 16,000 indicators including GDP, inflation, unemployment, interest rates, and trade statistics across all countries.
Can SEC Filings pull data from insurance carrier annual reports?
Yes — SEC Filings searches the EDGAR database for any public company. US insurance carriers file 10-Ks, 10-Qs, and annual statutory supplements through EDGAR, making it possible to extract loss ratios, reserve details, and catastrophe data directly.
What chart types can the Generate Chart tool produce?
Generate Chart supports bar charts, grouped bars, stacked bars, line charts, area charts, scatter plots, and pie charts. Charts are produced as downloadable images suitable for presentations and reports.
How do I get historical catastrophe loss data?
Use Deep Research to compile catastrophe loss summaries from Munich Re, Swiss Re, Aon, and industry reports. These aggregate insured and economic losses by event and are widely cited in actuarial and pricing work.
Can these tools replace a BI platform like Tableau or Power BI?
These tools are best for research, benchmarking, and one-off analysis rather than interactive dashboards built on internal data. For portfolio dashboards using internal claim and premium data, a dedicated BI platform is still the right choice.
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