ibnr
Compute IBNR claims for bornhuetterFerguson
object
Description
computes incurred-but-not-reported (IBNR) claims for reported or paid claims for a
ibnrClaims = ibnr(bf)bornhuetterFerguson object.
additionally specifies the type of claims data. Specify this argument after the
input argument in the previous syntax.ibnrClaims = ibnr(___,referenceClaimsType)
Examples
Compute IBNR for either reported or paid claims for a bornhuetterFerguson object containing simulated insurance claims data.
load InsuranceClaimsData.mat;
head(data) OriginYear DevelopmentYear ReportedClaims PaidClaims
__________ _______________ ______________ __________
2010 12 3995.7 1893.9
2010 24 4635 3371.2
2010 36 4866.8 4079.1
2010 48 4964.1 4487
2010 60 5013.7 4711.4
2010 72 5038.8 4805.6
2010 84 5059 4853.7
2010 96 5074.1 4877.9
Use developmentTriangle to convert the data to a development triangle, which is the standard form for representing claims data. Create two developmentTriangle objects, one for reported claims and one for paid claims.
dT_reported = developmentTriangle(data,'Origin','OriginYear','Development','DevelopmentYear','Claims','ReportedClaims')
dT_reported =
developmentTriangle with properties:
Origin: {10×1 cell}
Development: {10×1 cell}
Claims: [10×10 double]
LatestDiagonal: [10×1 double]
Description: ""
TailFactor: 1
CumulativeDevelopmentFactors: [1.3069 1.1107 1.0516 1.0261 1.0152 1.0098 1.0060 1.0030 1.0010 1]
SelectedLinkRatio: [1.1767 1.0563 1.0249 1.0107 1.0054 1.0038 1.0030 1.0020 1.0010]
dT_paid = developmentTriangle(data,'Origin','OriginYear','Development','DevelopmentYear','Claims','PaidClaims')
dT_paid =
developmentTriangle with properties:
Origin: {10×1 cell}
Development: {10×1 cell}
Claims: [10×10 double]
LatestDiagonal: [10×1 double]
Description: ""
TailFactor: 1
CumulativeDevelopmentFactors: [2.4388 1.4070 1.1799 1.0810 1.0378 1.0178 1.0080 1.0030 1.0010 1]
SelectedLinkRatio: [1.7333 1.1925 1.0914 1.0417 1.0196 1.0097 1.0050 1.0020 1.0010]
Create an expectedClaims object where the first input argument is the reported development triangle and the second input argument is the paid development triangle.
earnedPremium = [17000; 18000; 10000; 19000; 16000; 10000; 11000; 10000; 14000; 10000]; ec = expectedClaims(dT_reported, dT_paid,earnedPremium)
ec =
expectedClaims with properties:
ReportedTriangle: [1×1 developmentTriangle]
PaidTriangle: [1×1 developmentTriangle]
EarnedPremium: [10×1 double]
InitialClaims: [10×1 double]
CaseOutstanding: [10×1 double]
EstimatedClaimsRatios: [10×1 double]
SelectedClaimsRatios: [10×1 double]
Create a bornhuetterFerguson object with reported claims, paid claims, and expected claims to calculate ultimate claims, cases outstanding, IBNR claims, and unpaid claims estimates.
bf = bornhuetterFerguson(dT_reported, dT_paid, ec.ultimateClaims)
bf =
bornhuetterFerguson with properties:
ReportedTriangle: [1×1 developmentTriangle]
PaidTriangle: [1×1 developmentTriangle]
ExpectedClaims: [10×1 double]
PercentUnreported: [10×1 double]
PercentUnpaid: [10×1 double]
CaseOutstanding: [10×1 double]
Use ibnr to compute IBNR reported claims for a bornhuetterFerguson object.
ibnrClaims = ibnr(bf,"reported")ibnrClaims = 10×1
103 ×
0
0.0052
0.0167
0.0347
0.0572
0.0889
0.1496
0.3006
0.6118
1.5509
Input Arguments
Bornhuetter-Ferguson object, specified as a previously created bornhuetterFerguson object.
Data Types: object
Type of claims data, specified as a character vector or a string.
Data Types: char | string
Output Arguments
IBNR claims, returned as an array.
More About
Incurred-but-not-reported (IBNR) claims are the claims amount owed by an insurer to all valid claimants who have had a covered loss but have not yet reported it.
Since the insurer knows neither how many of these losses have occurred nor the severity of each loss, IBNR is necessarily an estimate.
Version History
Introduced in R2020b
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