AIG 2014 Annual Report Download - page 199

ITEM 7 / CRITICAL ACCOUNTING ESTIMATES
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of the accident year would be added to determine the total ultimate loss estimate for the accident year. Subtracting the
reported paid losses and loss adjustment expenses would result in the indicated loss reserve. In the example above, the
expected loss ratio of 70 percent would be multiplied by 90 percent. The result of 63 percent would be applied to the earned
premium of $10 million resulting in an estimated unreported loss of $6.3 million. Actual reported losses would be added to
arrive at the total ultimate losses. If the reported losses were $1 million, the ultimate loss estimate under the “Bornhuetter
Ferguson” method would be $7.3 million versus the $7 million amount under the expected loss ratio method described above.
Thus, the “Bornhuetter Ferguson” method gives partial credibility to the actual loss experience to date for the class of
business. Loss development methods generally give full credibility to the reported loss experience to date. In the example
above, loss development methods would typically indicate an ultimate loss estimate of $10 million, as the reported losses of
$1 million would be estimated to reflect only 10 percent of the ultimate losses.
A key advantage of loss development methods is that they respond quickly to any actual changes in loss costs for the class of
business. Therefore, if loss experience is unexpectedly deteriorating or improving, the loss development method gives full
credibility to the changing experience. Expected loss ratio methods would be slower to respond to the change, as they would
continue to give more weight to the expected loss ratio, until enough evidence emerged to modify the expected loss ratio to
reflect the changing loss experience. On the other hand, loss development methods have the disadvantage of overreacting to
changes in reported losses if the loss experience is not credible. For example, the presence or absence of large losses at the
early stages of loss development could cause the loss development method to overreact to the favorable or unfavorable
experience by assuming it will continue at later stages of development. In these instances, expected loss ratio methods such
as “Bornhuetter Ferguson” have the advantage of recognizing large losses without extrapolating unusual large loss activity
onto the unreported portion of the losses for the accident year.
Frequency/severity methods generally rely on the determination of an ultimate number of claims and an average
severity for each claim for each accident year. Multiplying the estimated ultimate number of claims for each accident year
by the expected average severity of each claim produces the estimated ultimate loss for the accident year. Frequency/severity
methods generally require a sufficient volume of claims in order for the average severity to be predictable. Average severity for
subsequent accident years is generally determined by applying an estimated annual loss cost trend to the estimated average
claim severity from prior accident years. In certain cases, a structural approach may also be used to predict the ultimate loss
cost. Frequency/severity methods have the advantage that ultimate claim counts can generally be estimated more quickly and
accurately than can ultimate losses. Thus, if the average claim severity can be accurately estimated, these methods can more
quickly respond to changes in loss experience than other methods. However, for average severity to be predictable, the class
of business must consist of homogeneous types of claims for which loss severity trends from one year to the next are
reasonably consistent. Generally these methods work best for high frequency, low severity classes of business such as
personal auto.
Structural drivers analytics seek to explain the underlying drivers of frequency/severity. A structural drivers analysis of
frequency/severity is particularly useful for understanding the key drivers of uncertainty in the ultimate loss cost. For example,
for the excess workers’ compensation class of business, we have attempted to corroborate our judgment by considering the
impact on severity of the future propensity for deterioration of an injured worker’s medical condition, the impact of price
inflation on the various categories of medical expense and cost of living adjustments on indemnity benefits, the impact of
injured worker mortality and claim specific settlement and loss mitigation strategies, etc., using the following:
• Claim by claim reviews to determine the stability and likelihood of settling an injured worker’s indemnity and medical
benefits – the claim file review was facilitated by third party specialists experienced in workers’ compensation claims;
• Analysis of the potential for future deterioration in medical condition unlikely to be picked up by a claim file review and
associated with potentially costly medical procedures (i.e., increases in both utilization and intensity of medical care) over
the course of the injured worker’s lifetime;
• Analysis of the cost of medical price inflation for each category of medical spend (services and devices) and for cost of
living adjustments in line with statutory requirements;
• Portfolio specific mortality level and mortality improvement assumptions based on a mortality study conducted for AIG’s
primary and excess workers’ compensation portfolios and AIG’s opinion of future longevity trends for the open reported
cases;
• Ground-up consideration of the reinsurance recoveries expected for the class of business for reported claims with
extrapolation for unreported claims; and