Premium rating without losses

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      <subfield code="a">Fackler, Michael</subfield>
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      <subfield code="a">Premium rating without losses</subfield>
      <subfield code="c">Michael Fackler</subfield>
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      <subfield code="a">In insurance and even more in reinsurance it occurs that about a risk you only know that it has suffered no losses in the past, e.g. seven years. Some of these risks are furthermore such particular or novel that there are no similar risks to infer the loss frequency from. In this paper we propose a loss frequency estimator that copes with such situations, by just relying on the information coming from the risk itself: the amended sample mean. It is derived from a number of practice-oriented first principles and turns out to have desirable statistical properties. Some variants are possible, enabling insurers to align the method to their preferred business strategy, by trading off between low initial premiums for new business and moderate premium increases after a loss for renewal business. We further give examples where it is possible to assess the average loss from some market or portfolio information, such that overall one has an estimator of the risk premium.

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      <subfield code="a">Pérdidas</subfield>
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      <subfield code="a">Cálculo actuarial</subfield>
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      <subfield code="w">MAP20220007085</subfield>
      <subfield code="g">06/06/2022 Número 1 - junio 2022 , p. 275-316</subfield>
      <subfield code="t">European Actuarial Journal</subfield>
      <subfield code="d">Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</subfield>
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