Consistency Checking of Risk Policy Rules Using Meta-Rules: Axiomatic Approach to Optimal Credit Policy Evaluation and Trade Offs for Credit Policy Expert Systems

17 Pages Posted: 6 Jun 2011 Last revised: 20 Jul 2014

See all articles by Dhruv Sharma

Dhruv Sharma

Independent

Joel Krenis

affiliation not provided to SSRN

Date Written: May 12, 2011

Abstract

This paper discusses a new approach to validating risk-related expert systems. The paper builds on existing knowledgebase verification and software testing literature to propose that risk related expert systems check for pareto optimal trade-offs in rule conditions along with the checks for ensuring contiguous numeric risk state space is covered by rules to ensure to gap in logic occurs. The construct of pareto optimal rules is novel and shown to be an effective and tractable approach used in production systems. In addition the pareto optimal property is form of common sense which financial credit related expert systems, which abound in industry, can benefit from as evidenced by the recent credit crisis. Ensuring that all rules are contiguous and pareto optimal within rule contexts adds to the expert system verification literature and is an approach that can increase early detection of defects along with ensuring sound credit decisioning for industrial expert systems. Thus the work has theoretical and practical value.

Keywords: risk management, expert systems, testing and validation, context based meta rules, pareto optimal risk trade-offs, credit risk underwriting

Suggested Citation

Sharma, Dhruv and Krenis, Joel, Consistency Checking of Risk Policy Rules Using Meta-Rules: Axiomatic Approach to Optimal Credit Policy Evaluation and Trade Offs for Credit Policy Expert Systems (May 12, 2011). Available at SSRN: https://ssrn.com/abstract=1839983 or http://dx.doi.org/10.2139/ssrn.1839983

Dhruv Sharma (Contact Author)

Independent ( email )

2023 N. Cleveland St.
Arlington, VA 22201
United States

HOME PAGE: http://theinterdisciplinarian.com/

Joel Krenis

affiliation not provided to SSRN ( email )

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
54
Abstract Views
632
rank
412,439
PlumX Metrics