Claim Reserving Estimation by Using the Chain Ladder Method

F F Adam

Article Details

Claim Reserving Estimation by Using the Chain Ladder Method

Authors:

F F Adam

Publisher:

KnE Social Sciences

Journal:

KnE Social Sciences Vol.3 Issue 11, pp.1192-1204

Document Type:

Article

Publication Date:

8/2018

Document Language:

English

Document ID (Org No.):

2001516308

pISSN:

2518-668X

Keywords:

Abstract:

 An insurance company promises its policyholders to pay out benefits if certain events occur, for example, events such as a car accident and health conditions. When this is happens, the insurance company has a liability to pay the claim by claim reserving. The calculation of claim reserving must be done carefully in such a way that it should not cause loss to the company. One of the simplest methods to calculate claim reserving is the chain ladder method (CL). The method uses an algorithm that can be used to estimate claim reserving in the future. The CL method estimates the claim reserving to be paid by using run-off triangle data. The rows on a run-off triangle data represent claim occurrence periods and the columns represent development periods, the periods when claim were settled. The real data used is a claim amount observed in the past that is located in the upper-left triangle, and the lower triangle has to be estimated. This research will use the data from one of the insurance companies in Indonesia taken from OJK.

Article Details

Claim Reserving Estimation by Using the Chain Ladder Method

Authors: F F Adam

Publisher: KnE Social Sciences

Journal: KnE Social Sciences Vol.3 Issue 11, pp.1192-1204

Document Type: Article

Publication Date: 8/2018

Document Language: English

Document ID (Org No.): 2001516308

pISSN: 2518-668X

claim

CL method

run-off triangle

claim reserving

Issues

Authors:

F F Adam

Publisher:

KnE Social Sciences

Journal:

KnE Social Sciences Vol.3 Issue 11, pp.1192-1204

Document Type:

Article

Publication Date:

8/2018

Document Language:

English

Document ID (Org No.):

2001516308

pISSN:

2518-668X