README.md

simulationmachine

This package implements the claims history simulation algorithm detailed in An Individual Claims History Simulation Machine by Andrea Gabrielli and Mario V. Wüthrich. The goal is to provide an easy-to-use interface for generating claims data that can be used for loss reserving research.

Installation

You can install the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("kasaai/simulationmachine")

Example

First, we can specify the parameters of a simulation using simulation_machine():

library(simulationmachine)

charm <- simulation_machine(
  num_claims = 50000, 
  lob_distribution = c(0.25, 0.25, 0.30, 0.20), 
  inflation = c(0.01, 0.01, 0.01, 0.01), 
  sd_claim = 0.85, 
  sd_recovery = 0.85
)

charm
#> A simulation charm for `simulation_machine`
#> 
#> Each record is:
#>  - A snapshot of a claim's incremental paid loss and claim status
#>    at a development year.
#> 
#> Specs:
#>  - Expected number of claims: 50,000
#>  - LOB distribution: 0.25, 0.25, 0.3, 0.2
#>  - Inflation: 0.01, 0.01, 0.01, 0.01
#>  - SD of claim sizes: 0.85,
#>  - SD of recovery sizes: 0.85

Once we have the charm object, we can use conjure() to perform the simulation.

library(dplyr)
records <- conjure(charm, seed = 100)
glimpse(records)
#> Observations: 603,324
#> Variables: 11
#> $ claim_id          <chr> "1", "1", "1", "1", "1", "1", "1", "1", "1", "…
#> $ accident_year     <int> 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1994…
#> $ development_year  <int> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 0, 1, 2,…
#> $ accident_quarter  <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4…
#> $ report_delay      <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ lob               <chr> "3", "3", "3", "3", "3", "3", "3", "3", "3", "…
#> $ cc                <chr> "42", "42", "42", "42", "42", "42", "42", "42"…
#> $ age               <int> 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65…
#> $ injured_part      <chr> "51", "51", "51", "51", "51", "51", "51", "51"…
#> $ paid_loss         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4913, 0, 0…
#> $ claim_status_open <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…

Let’s see how many claims we drew:

records %>% 
  distinct(claim_id) %>% 
  count()
#> # A tibble: 1 x 1
#>       n
#>   <int>
#> 1 50277

If you prefer to have each row of the dataset to correspond to a claim, you can simply pivot the data with tidyr:

records_wide <- records %>% 
  tidyr::pivot_wider(
    names_from = development_year, 
    values_from = c(paid_loss, claim_status_open),
    values_fill = list(paid_loss = 0)
  )

glimpse(records_wide)
#> Observations: 50,277
#> Variables: 32
#> $ claim_id             <chr> "1", "2", "3", "4", "5", "6", "7", "8", "9"…
#> $ accident_year        <int> 1994, 1994, 1994, 1994, 1994, 1994, 1994, 1…
#> $ accident_quarter     <dbl> 1, 4, 4, 2, 1, 1, 1, 3, 4, 4, 2, 2, 4, 3, 1…
#> $ report_delay         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0…
#> $ lob                  <chr> "3", "3", "3", "4", "2", "1", "3", "1", "3"…
#> $ cc                   <chr> "42", "39", "26", "8", "50", "22", "43", "1…
#> $ age                  <int> 65, 52, 23, 54, 24, 53, 39, 40, 27, 43, 55,…
#> $ injured_part         <chr> "51", "53", "70", "36", "36", "53", "51", "…
#> $ paid_loss_0          <dbl> 0, 4913, 0, 458, 1158, 376, 0, 285, 0, 0, 0…
#> $ paid_loss_1          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 3389, 0, 0, 0, 0…
#> $ paid_loss_2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_3          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_4          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_5          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_6          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_7          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_8          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_9          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_10         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ paid_loss_11         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_0  <int> 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0…
#> $ claim_status_open_1  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0…
#> $ claim_status_open_2  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_3  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_4  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_5  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_6  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_7  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_8  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_9  <int> 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_10 <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
#> $ claim_status_open_11 <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…

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