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Benktander method

A reserve built by feeding the Bornhuetter-Ferguson ultimate back in as the new a priori. The result is a credibility estimator with a lower mean squared error than either of its two parents.

Definition

Benktander, 1976, then Hovinen, 1981, working independently: take the ultimate produced by Bornhuetter-Ferguson and reuse it as the a priori loss ratio in a second pass. Chain ladder trusts the triangle entirely, Bornhuetter-Ferguson trusts the a priori entirely for the undeveloped share, and Benktander goes one step further. Algebraically the result is a weighted average of chain ladder and Bornhuetter-Ferguson whose weight is the percent developed itself. The more mature the year, the closer the method sits to chain ladder, which is the behavior you want. The estimator has a lower mean squared error than the other two across most realistic settings, hence its use as a default when you are torn between them. It keeps the same blind spot, though: if the development pattern is wrong, all three methods are wrong together and in the same direction.

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Benktander method: Actuarial science glossary illustration, AlgoPolis
Example

Accident year 2023 of a construction book as of December 31, 2025, percent developed 40%. Chain ladder returns an ultimate of 18.0M EUR, Bornhuetter-Ferguson 14.4M EUR on a 12M EUR a priori. Benktander returns 0.40 x 18.0 + 0.60 x 14.4 = 15.8M EUR. The reserve therefore moves from 7.2M EUR under Bornhuetter-Ferguson to 8.6M EUR, and the 1.4M EUR difference is precisely the credibility given back to the triangle.

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