The claims projections in this method is done using the past experience of how the claims have developed. The principle of this method is that historical loss development patterns (called development factor) are indicative of future loss development patterns.
The chain ladder or development method (CLM) is a method used to calculate IBNR reserves as a part of claims reserves estimate by insurers for reporting on their financial statements.
This method assumes that the future pattern will follow past patterns. So, we will try to find the factor responsible for past incrementation. However, many times there are cases when we particularly do not consider a development year or an accident year due to adversities or change in processes. Simply, wherever the patter is hindered we do not consider that part.
Learn Chain Ladder Method (CLM)
The chain ladder method calculates incurred but not reportedIncurred But Not Reported or IBNR reserves are a part of claims reserves estimated by insurers for reporting on their financial statements. Claims reserves are estimates of claims that have occurred on or before the financial statement report date but which have yet to be paid. This a current lia… (IBNR) loss estimates, using run-off triangles of paid losses and incurred losses, representing the sum of paid losses and case reserves. Insurance companies are required to set aside a portion of the premiums they receive from their underwriting activities to pay for claims that may be filed in the future. The amount of claims forecasted, along with the amount of claims that are actually paid, determine how much profit the insurer will publish in its financial documents.
Reserve triangles are two-dimensional matrices that are generated by accumulating claim data over a period of time. The claim data is run through a stochastic process to create the run-off matrices after allowing for many degrees of freedom.
At its core, the chain ladder method operates under the assumption that patterns in claims activities in the past will continue to be seen in the future. In order for this assumption to hold, data from past loss experiences must be accurate.
Several factors can impact accuracy, including changes to the product offerings, regulatory and legal changes, periods of high severity. Severity refers to the amount you have received Insurance claim for. Average Severity would be the loss associated with an average Insurance claim. claims, and changes in the claims settlement process. If the assumptions built into the model differ from observed claims, insurers may have to make adjustments to the model.
The calculation takes place completely using the age to ultimate factors, the factors which were selected in earlier exercises and we simply multiply the reported/incurred to those factors. You’ll be able to understand from the below exercise.