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Statistical models of judgment 447
market – such that insurance products are transformed from commodity
items to customized, value-added, services. The authors argue that
expert systems can aid underwriters to segment client groupings.
In summary, a strong business case can be made for automating
an expert underwriter’s decision-making processes and utilizing the
resulting expert system at an early phase of back-office transaction
processing. In addition, advice-giving systems at front-office point-ofsale
can enhance the sale capabilities of front-office financial services
staff. Such advice-giving systems also enable the collection of detailed
customer profiles.
Compared to such exemplar systems, more generalized advice-giving
systems which are intended to stimulate strategic thinking or negotiation
seem less utilitarian.
Statistical models of judgment
One of the major databases used for early experimentation on multiattributed
inference has been that collected by Meehl. 38 The judgmental
problem used was that of differentiating psychotic from neurotic patients
on the basis of their MMPI questionnaire profiles.
Each patient, upon being admitted to hospital, had taken the MMPI.
Expert clinical psychologists believe (or at least used to believe) that
they can differentiate between psychotics and neurotics on the basis of a
profile of the 11 scores. Meehl noted that
because the differences between psychotic and neurotic profile are considered
in MMPI lore to be highly configural in character, an atomistic treatment by
combining scales linearly should be theoretically a very poor substitute for
the configural approach.
Initially, researchers tried to ‘capture’ or ‘model’ expert judges by a
simple linear regression equation. These judgmental representations are
constructed in the following way. The clinician is asked to make his
diagnostic or prognostic judgment from a previously quantified set of
cues for each of a large number of patients. These judgments are then
used as the dependent variable in a standard linear regression analysis.
The independent variables in this analysis are the values of the cues. The
results of such an analysis are a set of regression weights, one for each
cue, and these sets of regression weights are referred to as the judge’s