Downloadable - About University

Expert systems 443
described above represent complete replacements for underwriters, who
are seen as invaluable since they are still required to deal with the most
difficult of cases and to handle changes in risk assessment circumstances,
with which the systems themselves are unable to deal. For example,
updates are required to the rule bases when formerly peaceable countries
become war zones that a proposed insured plans to visit.
Of prime interest here, however, is the nature of the underwriting
domain which has made it amenable for the implementation of viable
expert systems.
Ifoneconsidersthenatureofthistaskmoreclosely,thenitisapparent
that it:
(1) Involves repetitive components;
(2) Is a clearly structured logical process;
(3) Is a high volume task;
(4) Involves the utilization of knowledge that is fairly static (otherwise
the system would require vast amounts of updating and reprogramming);
(5) Involves variation in human performance which could (beneficially)
be made more consistent.
Furthermore, and importantly, the underwriting domain complies with
the two criteria set out by Wright and Ayton for commercial viability,
namely, most of the rules for underwriting tend to be formalized
in manuals (in the case of life underwriting these are produced by
underwriters in collaboration with actuaries and chief medical officers),
and the domain is also verbally communicable in a step-by-step fashion
to novices. Indeed, before the expert system was developed, this
is how novices were trained. These factors ensure that the knowledge
elicitation and engineering aspects of devising the expert system are
achievable – aspects whose difficulty and pertinence to eventual system
success are often underestimated. Thus underwriting differs considerably
from the bulk of those marketing applications for which systems
have been built – few of which (if any) are based on rules or knowledge
which are stated explicitly in reference manuals, or which can
be coherently and reliably elicited from the supposed experts. In our
view, Rangaswamy et al.’s second and third checklist items for selecting
problems ‘suitable’ for expert systems have, in themselves, prompted
others to engage in overambitious projects. Indeed, one recent survey 31
found that expert systems in use in the UK were not designed to cross
functional and organizational boundaries but were instead utilized to
automate relatively simple problem domains.