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Insurance Analytics

Plotly graphs are used in the dashboards, reports, and software products of insurance companies worldwide.

Plotly serves the insurance industry with its collaborative analytics platform and open-source charting tools:

  1. Plotly's open-source graphing library, Plotly.js, powers the charting capabilities of many insurance and reinsurance analytics platforms.
  2. Plotly's collaborative analytics platform serves teams building internal dashboards and reports in Python, MATLAB, R, and Excel.

Car insurance sales with Plotly dashboards and Python (Goji)

Car insurance provider Goji uses Plotly Enterprise and the Plotly Python client for all their internal dashboards on sales performance. By switching to internal tools built on Plotly Enterprise, they were able to save over a hundred thousand dollars in BI infrastructure because they no longer needed to pay for traditional data warehouse functionality. Read more in the full customer story linked below.

Plotly is a breath of fresh air in a BI space has become bloated, noisy, frustrating, and inflexible. It embraces increasingly dominant open source data analysis tools such as IPython, and is embeddable wherever HTML is served.
- Goji, world's leading provider of automobile insurance

Monte Carlo simulations and reinsurers

Plotly is used for stochastic simulations and Monte Carlo methods in MATLAB, R, and Python. Graphs from these analyses are embedded in web dashboards and reports for easy sharing.
Plotly provides a robust platform for visualizing data and the various outputs from simulation-based analyses. Among its many strengths is the ability to modify graphics iteratively and to easily share work with collaborators, making the process of describing and interpreting my analyses that much easier.
- Dr. Chris Fonnesbeck
Author of PyMC, Python's library for Markov chain Monte Carlo algorithms

Financial research in R, Python, and MATLAB

Plotly allows financial analysts to use the languages that they know - R, Python and the MATLAB Finance Toolbox - but draws publication-quality graphs using D3.js.

Comparing sales performance by geography

Plotly choropleth and bubble maps are ideal for comparing regional sales performance. Plotly maps are drawn in D3.js, but can be made in Excel or a language familiar to financial analysts such as R, Python, or MATLAB.

A Plotly sales engineer will answer any questions, walk you through a demo, and support a trial deployment.