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Factor analysis for discrete risk factors

Source: R/univariate.R
factor_analysis.Rd

Performs a factor analysis for discrete risk factors in an insurance portfolio. The following summary statistics are calculated:

  • frequency = number of claims / exposure

  • average severity = severity / number of claims

  • risk premium = severity / exposure

  • loss ratio = severity / premium

  • average premium = premium / exposure

univariate() is deprecated as of version 0.8.0. Please use factor_analysis() instead with standard evaluation (SE), i.e. column names as character strings.

Usage

factor_analysis(
  data = NULL,
  risk_factors = NULL,
  claim_amount = NULL,
  claim_count = NULL,
  exposure = NULL,
  premium = NULL,
  group_by = NULL,
  df = NULL,
  x = NULL,
  severity = NULL,
  nclaims = NULL,
  by = NULL
)

univariate(
  df,
  x,
  severity = NULL,
  nclaims = NULL,
  exposure = NULL,
  premium = NULL,
  by = NULL
)

Arguments

data

A data.frame with the insurance portfolio.

risk_factors

Character vector: column(s) in data with the risk factor(s).

claim_amount

Character, column in data with claim amounts (default = NULL).

claim_count

Character, column in data with number of claims (default = NULL).

exposure

Character, column in data with exposures (default = NULL).

premium

Character, column in data with premiums (default = NULL).

group_by

Character vector of column(s) in data to group by in addition to risk_factors.

df, x, severity, nclaims, by

Deprecated argument names. Use data, risk_factors, claim_amount, claim_count, and group_by instead.

Value

An object of class "factor_analysis" and "univariate" with summary statistics.

Details

The function computes summary statistics for discrete risk factors.

  • Frequency: number of claims / exposure

  • Average severity: severity / number of claims

  • Risk premium: severity / exposure

  • Loss ratio: severity / premium

  • Average premium: premium / exposure

If one or more input arguments are not specified, the related statistics are omitted from the results.

Migration from univariate()

The function univariate() is deprecated as of version 0.8.0 and replaced by factor_analysis(). In addition to the name change, the interface has also changed:

  • univariate() used non-standard evaluation (NSE), so column names could be passed unquoted (e.g. x = area).

  • factor_analysis() uses standard evaluation (SE), so column names must be passed as character strings (e.g. x = "area").

This makes the function easier to use in programmatic workflows.

univariate() is still available for backward compatibility but will emit a deprecation warning and will be removed in a future release.

Author

Martin Haringa

Examples

## --- New usage (SE) ---
factor_analysis(MTPL2,
                risk_factors = "area",
                claim_amount = "amount",
                claim_count = "nclaims",
                exposure = "exposure",
                premium = "premium")
#>   area  amount nclaims   exposure premium  frequency average_severity
#> 1    2 4063270      98  818.53973   51896 0.11972540         41461.94
#> 2    3 7945311     113  764.99178   49337 0.14771401         70312.49
#> 3    1 6896187     146 1065.74795   65753 0.13699299         47234.16
#> 4    0    6922       1   13.30685     902 0.07514927          6922.00
#>   risk_premium loss_ratio average_premium
#> 1    4964.0474  78.296400        63.40071
#> 2   10386.1390 161.041632        64.49350
#> 3    6470.7486 104.880188        61.69658
#> 4     520.1832   7.674058        67.78464

## --- Deprecated usage (NSE) ---
univariate(MTPL2,
           x = area,
           severity = amount,
           nclaims = nclaims,
           exposure = exposure,
           premium = premium)
#>   area  amount nclaims   exposure premium  frequency average_severity
#> 1    2 4063270      98  818.53973   51896 0.11972540         41461.94
#> 2    3 7945311     113  764.99178   49337 0.14771401         70312.49
#> 3    1 6896187     146 1065.74795   65753 0.13699299         47234.16
#> 4    0    6922       1   13.30685     902 0.07514927          6922.00
#>   risk_premium loss_ratio average_premium
#> 1    4964.0474  78.296400        63.40071
#> 2   10386.1390 161.041632        64.49350
#> 3    6470.7486 104.880188        61.69658
#> 4     520.1832   7.674058        67.78464