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Add excess loading to a pricing portfolio

Source: R/excess_loss.R
add_excess_loading.Rd

Add an allocated excess loading to a portfolio data set.

add_excess_loading() is the final workflow step. It does not estimate or allocate excess loss. It takes an object produced by allocate_excess_loss() and adds row-level loading columns to data.

The default workflow is premium based: loaded_premium = base_premium + allocated_excess_loss. allocated_excess_loss represents the allocated excess burden in absolute monetary terms. allocated_loading represents the excess loading per unit of weight.

Use output = "rate" when base_premium should be interpreted as a premium amount that first needs to be converted to a rate with base_rate = base_premium / weight.

Usage

add_excess_loading(
  data,
  allocation,
  base_premium = "base_premium",
  allocated_excess_loss = NULL,
  allocated_loading = NULL,
  weight = NULL,
  output = c("premium", "rate")
)

Arguments

data

A data.frame.

allocation

An object returned by allocate_excess_loss().

base_premium

Character string. Base premium amount before excess loading.

allocated_excess_loss

Optional character string. Column in allocation$data with the allocated excess burden in absolute monetary terms. If NULL, allocated_excess_loss is used.

allocated_loading

Optional character string. Column in allocation$data with the excess loading per unit of weight. If NULL, allocated_loading is used.

weight

Optional character string. Weight column used to convert between premium amounts and rates when output = "rate".

output

Character. Use "premium" to return premium amounts or "rate" to return rates per unit of weight.

Value

A data.frame. With output = "premium", the result contains base_premium, allocated_excess_loss, allocated_loading, excess_loading and loaded_premium. With output = "rate", it contains base_rate, allocated_loading and loaded_rate.

Author

Martin Haringa

Examples

claims <- data.frame(
  sector = rep(c("Industry", "Retail"), each = 4),
  claim_amount = c(1000, 120000, 30000, 8000, 2000, 150000, 40000, 6000),
  earned_exposure = rep(1, 8)
)
decomposed <- calculate_excess_loss(claims, "claim_amount", threshold = 100000)
allocation <- allocate_excess_loss(
  decomposed,
  excess_amount = "excess_claim_amount",
  weight = "earned_exposure"
)
add_excess_loading(decomposed, allocation)
#> Error: Column not found in `data`: base_premium