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https://github.com/jimbrig/property_allocation_demo

Dynamic Risk Allocation Model - bringing simplicity to the complex realm of Property Insurance.
https://github.com/jimbrig/property_allocation_demo

actuarial-science allocation dashboard data-science insurance property-management r r-shiny workflow

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Dynamic Risk Allocation Model - bringing simplicity to the complex realm of Property Insurance.

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README 

        
---

output: github_document

---



```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```



# Property Allocation 



**propalloc** is an R Package housing the codebase for the R Shiny

Property Allocation Demo Application.



+ Date: `r Sys.Date()`

+ Demo: https://propallocation.jimbrig.com/



## Badges



```{r badge_prep, echo=FALSE}

# dep <- as.vector(read.dcf('DESCRIPTION')[, 'Depends'])

# rvers <- substr(dep, 7, nchar(dep) - 1)

version <- as.vector(read.dcf('DESCRIPTION')[, 'Version'])

version <- gsub('-', '.', version)

```



![pkgdown](https://github.com/jimbrig/propalloc/workflows/pkgdown/badge.svg)

[![lifecycle](https://img.shields.io/badge/Lifecycle-Maturing-darkgreen.svg)](https://www.tidyverse.org/lifecycle/#maturing)

[![package%20version](https://img.shields.io/badge/Package%20Version-1.1.0-orange.svg)](https://github.com/jimbrig/propalloc/blob/master/commits/master)

[![github](https://img.shields.io/badge/Github-jimbrig/propalloc-black.svg)](https://github.com/jimbrig/propalloc)



## 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:



```{r, eval=FALSE}

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



+ [Changelog](inst/reports/changelog.md)

+ [Contributor Code of Conduct](CODE_OF_CONDUCT.md) 

+ [License](LICENSE.md) 

+ View the [Contributing](inst/reports/contributing.md) document for on-boarding resource.  

+ View the [Roadmap](inst/reports/roadmap.md) for schedule and planned future actions. 



## 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](https://github.com/hadley/devtools).



### GitHub



Install from [GitHub](https://github.com) via:



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

[this webpage](https://github.com/settings/tokens).



```{r, eval=FALSE}

library(devtools)



# using username/password

devtools::install_github("jimbrig/propalloc",

                         "", 

                         "")



# 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]([email protected]) 

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.