Decompose claim amounts into capped and excess parts

Calculate the historical excess amount above a selected threshold.

calculate_excess_loss() is deliberately deterministic. It does not perform bootstrap simulation, smoothing or allocation. The function simply decomposes each observed claim into a capped part and an excess part: excess_claim_amount = pmax(claim_amount - threshold, 0).

Use the output as input for allocate_excess_loss() when the historical excess burden needs to be pooled, credibility-weighted or bootstrapped.

Usage

calculate_excess_loss(data, claim_amount, threshold)

Arguments

data

A data.frame with claim-level observations.

claim_amount

Character string. Claim amount column.

threshold

Positive numeric scalar. Claims above this value are treated as excess claims.

Value

A data.frame with the original data and the columns claim_amount, capped_claim_amount, excess_claim_amount and is_excess_claim.

Author

Martin Haringa

Examples

claims <- data.frame(claim_amount = c(1000, 120000, 30000))
calculate_excess_loss(claims, claim_amount = "claim_amount", threshold = 100000)
#>   claim_amount capped_claim_amount excess_claim_amount is_excess_claim
#> 1         1000               1e+03                   0           FALSE
#> 2       120000               1e+05               20000            TRUE
#> 3        30000               3e+04                   0           FALSE