What is 'Loss Reserve'
Loss reserve is an estimate of an insurer’s liability from future claims. Loss reserves are typically comprised of liquid assets, and they allow the insurer to cover claims made against policies that it underwrites. Estimating liabilities can be a complex undertaking. Insurers must take into account the duration of the insurance contract, the type of insurance offered and the odds of a claim being resolved quickly. Insurers have to adjust their loss reserve calculations as circumstances change.
When an insurer underwrites a new policy, it records a premium receivable (which is an asset) and a claim obligation (which is a liability). The liability is considered part of the unpaid losses account, which represents the loss reserve.
BREAKING DOWN 'Loss Reserve'
Accounting for loss reserves involves complex calculations because losses can come at any time, including years down the road. For example, a final settlement of litigation with a claimant may require a multi-year court battle.
Insurers prefer to use present value when calculating claims, since it allows them to consider interest. However, regulators require claims be recorded at the actual value of the loss – its nominal value. The undiscounted loss reserve will be greater than the discounted loss reserve. This regulatory requirement results in higher reported liabilities.
Regulators determine an insurer’s taxable income by taking the sum of annual premiums and subtracting any increases in loss reserves. This calculation is called loss reserve deduction. Income, which is the insurer’s underwriting income, includes the loss reserve deduction, plus investment income.
Insurance companies may use loss reserve for income smoothing. The claims process can be complex; determining whether an insurer is using loss reserves to smooth income requires examining changes to the insurer’s loss reserve errors, relative to past investment income.
Loss Reserves and Loans
Lending institutions also use loss reserves to manage their books.
For example, consider Bank ABC that made $10,000,000 of loans to various companies and individuals. Though Bank ABC works very hard to qualify the people to whom it grants loans, some will inevitably default or fall behind, and some loans will have to be renegotiated.
Bank ABC understand these realities and, thus, estimates that 2 percent of its loans, or $200,000, will probably never be paid back. This $200,000 estimate is Bank ABC's loan loss reserve, and it records this reserve as a negative number on the asset portion of its balance sheet.If Bank ABC decides to write all or a portion of a loan off, it will remove the loan from its asset balance and also remove the amount of the write-off from the loan loss reserve. The amount deducted from the loan loss reserve may be tax-deductible for Bank ABC.
Chain Ladder Method (CLM)
DEFINITION of 'Chain Ladder Method (CLM)'
A method for calculating the claims reserve requirement in an insurance company’s financial statement. The chain ladder method (CLM) is used by insurers to forecast the amount of reserves that must be established in order to cover future claims. This actuarial method is one of the most popular reserves methods.
BREAKING DOWN 'Chain Ladder Method (CLM)'
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 that are forecasted, along with the amount of claims that are actually paid, determine how much profit the insurer will publish in its financial documents.
The chain ladder method calculates incurred but not reported (IBNR) loss estimates using run-off triangles of paid losses and incurred losses, representing the sum of paid losses and case reserves. The 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 heart, 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 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.
Creating estimations can be difficult because random fluctuations in claims data and a small data set can result in forecasting errors. To smooth over these problems, insurers combine both company claims data with data from the industry in general.