Property Allocation

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lifecycle package%20version

propalloc is an R Package housing the codebase for the R Shiny Property Allocation Demo Application.

propalloc ***

Builds and Deployment

Purpose

The goal of this project is to create a model in R Shiny that allocates an insured’s prospective year property insurance costs in an equitable, easily understood manner that saves the client time, provides the option to use an “actuarial” methodology, while still allowing for maximum flexibility and edits.

Demo

To demo the app, you have a couple of options:

  • If you want to run the application locally, simply install the package and run the code below:
library(propalloc)
propalloc::run_app()

Note that the run_app function will automatically install package dependencies for you.

Scope of Services

Upon completion, this model will be used as a demo to sell future work, similar to the R Shiny casualty cost allocation model. Once sold, this model will provide a template for billable projects.

Specifically, the property allocation model will allocate the premium, taxes, fees, surcharges and any related costs (collectively, the “property insurance costs”) to the desired level. This level can include up to six hierarchies (e.g. Country, Business Unit, Division, Region, Location, and Intra-location Department).

The tool will enable the client to incorporate the following criteria into its allocation process:

  • Total Insured Value (TIV)
  • Market AOP Rates (provided by Marsh or Client)
  • Market CAT Rates
  • Wind Tier
  • Earthquake Exposure
  • Flood Exposure
  • Terrorism Rates
  • Claim Frequency
  • Claim Severity
  • Risk Engineering Credits/Surcharges
  • Other Manual Adjustments
  • Relativity Adjustments
  • Combustible vs. Non-Combustible
  • Sprinkler Type/Status
  • Business Unit (BU)

In addition, the model will allow a client to select various thresholds and caps on premium/rate changes.

The tool will also provide multiple summaries, facilitating the comparison of the resulting allocation in up to three different scenarios. For example, the client can compare the resulting to allocation based upon: proposed market rates without adjustment, rates used in the prior year allocation, proposed increases for budget guidance applied to the rates used in the prior year.

The tool will also give the user the ability to:

  • Edit the TIV, properties, or other aspects of the exposures in the statement of values (SOV) between the scenarios outlined above (this is of importance as information often changes throughout the allocation process)
  • Force the final allocation for a specific or a set of specific locations to be a fixed number
  • Change the different loss severity buckets considered in the model
  • Add extra fees after the allocation is complete, while still maintaining the allocation of the other property insurance costs

Lastly, the tool will provide a summary by any combination of the six hierarchies that will calculate the dollar change in premium attributable to any of the following:

  • change in TIV,
  • change in the initial implied rates,
  • claims charges,
  • manual “all other risk” adjustment, and/or
  • cap placed on the increase in rate and the resulting off-balance associated with a cap.

Resources

View all package documentation by installing and running:

propalloc::open_docs()

Documents

Installation

propalloc is setup as an R Package making it simple to house all the various dependencies that the final application relies on.

Make sure you have the latest and stable version of devtools.

GitHub

Install from GitHub via:

For information on setting up your GitHub PAT (Personal Access Token) visit this webpage.

library(devtools)

# using username/password
devtools::install_github("jimbrig/propalloc",
                         "<username>", 
                         "<password>")

# using GitHub PAT
# library(usethis)
# usethis::browse_github_pat()

devtools::install_github("jimbrig/propalloc",
                         auth_token = github_pat(quiet))

If you have any trouble, contact Jimmy Briggs to make sure you have read access to the repository and for further troubleshooting.

Technical

This project is set up as an R Package. To view important details regarding the setup visit the Technical API Vignette.

It also utilized GIT LFS. To install run git lfs install in git bash.