Combining Expert Knowledge and Databases for Risk Management

12 Pages Posted: 18 Jan 2003

See all articles by Hennie Daniels

Hennie Daniels

Erasmus Research Institute of Management (ERIM); Tilburg University, CentER for Economic Research

H.G. van Dissel

Erasmus Research Institute of Management (ERIM); Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management

Date Written: October 2003 1,

Abstract

Correctness, transparency and effectiveness are the principalattributes of knowledge derived from databases. In current data miningresearch there is a focus on efficiency improvement of algorithms forknowledge discovery. However important limitations of data mining canonly be dissolved by the integration of knowledge of experts in thefield, encoded in some accessible way, with knowledge derived formpatterns in the database. In this paper we will in particular discussmethods for combining expert knowledge and knowledge derived fromtransaction databases.The framework proposed is applicable to widevariety of risk management problems. We will illustrate the method ina case study on fraud discovery in an insurance company.

Keywords: knowledge discovery, risk management, knowledge based systems, datamining

JEL Classification: M, M11, R4, D83

Suggested Citation

Daniels, Hennie and van Dissel, H.G., Combining Expert Knowledge and Databases for Risk Management (October 2003 1,). Available at SSRN: https://ssrn.com/abstract=371062

Hennie Daniels (Contact Author)

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Tilburg University, CentER for Economic Research ( email )

P.O. Box 90153
Tilburg, 5000 LE
Netherlands
+31 13 466 2026 (Phone)

H.G. Van Dissel

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management

RSM Erasmus University
PO Box 1738
3000 DR Rotterdam
Netherlands