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Head-to-head · Insurance Analytics Software

Swiss Re P&C Analytics vs hyperexponential hx

  • Updated Sep 2026
  • Both researched from official sources
  • 2 checks side by side
Higher score Swiss Re P&C Analytics #6 in Insurance Analytics Software 8.9/10 Pricing on request ✓ 1 of 1 features Contact Swiss Re
hyperexponential hx #8 in Insurance Analytics Software 8.6/10 Pricing on request ✓ 1 of 1 features Visit site

Swiss Re P&C Analytics leads on 0 checks, hyperexponential hx on 0, and 2 are even. Who comes out ahead on the 2 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreSwiss Re P&C Analytics · 8.9/10

Swiss Re P&C Analytics scores higher on our rubric for insurance analytics software: 8.9 against 8.6 out of 10; our editors rank them #6 and #8.

Swiss Re P&C Analytics is the better fit for insurers analyzing portfolio and property risk. hyperexponential hx is the better fit for commercial insurers modernizing pricing workflows.

  • Swiss Re P&C Analytics fits best

    Insurers analyzing portfolio and property risk

  • hyperexponential hx fits best

    Commercial insurers modernizing pricing workflows

Advertiser disclosure: iTechGuides is reader-supported. We may earn a commission when you click some links. It never changes our verdict. How we rank.

Side by side

Feature Swiss Re P&C Analytics 8.9/10 Visit ↗ hyperexponential hx 8.6/10 Visit ↗
At a glance
Editor score 8.9 8.6
Ranking #6 in Insurance Analytics Software #8 in Insurance Analytics Software
Best for Insurers analyzing portfolio and property risk Commercial insurers modernizing pricing workflows
Pricing model Paid Paid
Starting price Not published Not published
Free plan Not published —
Free trial — —
Deployment Cloud Cloud
Platforms Web Web
Support Docs Email
Built for Mid-market, Enterprise Mid-market, Enterprise
Features Swiss Re P&C Analytics 1/1 · hyperexponential hx 1/1
Catastrophe modeling ✓ ✓
Specs
Analytics areas Portfolio analysis and optimisation; property risk and exposure; motor underwriting and pricing; commercial insurance; liability pricing and accumulation risk; market growth strategies Submission triage; pricing and rating; risk assessment; renewals; portfolio monitoring and analysis; reinsurance management; actuarial modeling
Modeling methods Proprietary risk modelling; actuarial expertise; data analytics; forward-looking exposure-based modelling; predictive property risk model Python-based actuarial calculations; quota-share, excess-of-loss, and property catastrophe treaty models; loss-curve benchmarking; what-if and scenario analysis
Deployment Not published Cloud
Data connectors Client portfolio data; Swiss Re risk data and models; external data sources; catastrophe risk layers; building characteristics APIs; files; databases; S&P Global Geopolitical Risk; Companies House API; HazardHub; AddressCloud; Moody’s RMS; AIR Worldwide Touchstone; CyberCube; Slack; Microsoft Teams; email systems
Output formats Interactive dashboards; charts; maps; API-accessible model results Not published
Our review
Pros
  • Combines portfolio dashboards, maps and catastrophe risk layers
  • Covers property, motor, commercial and liability risk analysis
  • Provides API access to models and risk data
  • Build rating calculations in Python or with low-code configuration.
  • Govern pricing logic with versioning, release governance, and audit trails.
  • Connect underwriting and portfolio analysis with catastrophe-model integrations.
Cons
  • Pricing requires contacting Swiss Re
  • The offering spans applications, data, APIs and consulting
  • Designed for mid-market and enterprise insurers
  • Pricing is sales-led, with prospective customers directed to request a demo.
  • Deployment is cloud-based, which may not fit teams seeking another deployment model.
  • Its focus is commercial P&C, reinsurers, and managing general agents.
Our verdict

Swiss Re P&C Analytics brings analytics applications, APIs, data and risk expertise to property and casualty insurers. Its Impact+ platform provides access to applications and insurance-related datasets, while bespoke consulting can…

Read the review →

Commercial insurers, reinsurers, and managing general agents can use hyperexponential hx to manage underwriting and analytics workflows for property and casualty risks. Its scope runs from submission triage and risk assessment through…

Read the review →
  1. Swiss Re P&C AnalyticsInsurance Analytics Software 8.9Pricing on request
  2. hyperexponential hxInsurance Analytics Software 8.6Pricing on request

Strengths and trade-offs

  • Swiss Re P&C Analytics — where it wins

    • Combines portfolio dashboards, maps and catastrophe risk layers
    • Covers property, motor, commercial and liability risk analysis
    • Provides API access to models and risk data

    Where it doesn't

    • Pricing requires contacting Swiss Re
    • The offering spans applications, data, APIs and consulting
    • Designed for mid-market and enterprise insurers

  • hyperexponential hx — where it wins

    • Build rating calculations in Python or with low-code configuration.
    • Govern pricing logic with versioning, release governance, and audit trails.
    • Connect underwriting and portfolio analysis with catastrophe-model integrations.

    Where it doesn't

    • Pricing is sales-led, with prospective customers directed to request a demo.
    • Deployment is cloud-based, which may not fit teams seeking another deployment model.
    • Its focus is commercial P&C, reinsurers, and managing general agents.
  • Swiss Re P&C Analytics8.9/10 · Pricing on request

    Portfolio, property and casualty risk analytics with applications, APIs and consulting.

    Contact Swiss ReFull verdict →
  • hyperexponential hx8.6/10 · Pricing on request

    A governed pricing and portfolio platform for commercial insurers, reinsurers, and MGAs.

    Visit siteFull verdict →

More comparisons

All insurance analytics software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026

Last updated · How we research and update