
	Journal of Artificial Intelligence
	Year: 2019 \| Volume: 12 \| Issue: 1 \| Page No.: 18-23 DOI: 10.3923/jai.2019.18.23

Risk Assessment with Decision Tree in Professional Liability Insurance: In Accounting

Murat Sari

, Eyyup Gulbandilar

and Nilufer Dalkilic

Abstract: Background and Objective: Evaluation of new tools to assess the risk of professional liability insurance is needed in daily life shaped by many parameters. The pragmatic aim of this study is to deal with the assessment of insurance risks in the professional liability insurance through decision tree algorithm and the entropy. Thus the present study is to provide effective decision-making based on risk factors of insurance in various branches of professional liability. Materials and Methods: To achieve this study, an algorithm was produced by taking into consideration a quite big number of variables. This algorithm was based on a decision tree and entropy. To produce this algorithm, 258 policies (exam group) were tested on the 54 policies (testing group). Results: The computed results were seen to be in very good agreement with the policies. Over 87% of the results are in agreement with the policies. Our tool is designed to be used by professional liability insurance companies at minimum risk and to be used at optimum prices of clients. Conclusion: This study is the first and important attempt to assess the level of risk for a wide range of insurance companies and to find the optimal price for many clients.

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How to cite this article:

Murat Sari, Eyyup Gulbandilar and Nilufer Dalkilic, 2019. Risk Assessment with Decision Tree in Professional Liability Insurance: In Accounting. Journal of Artificial Intelligence, 12: 18-23.

DOI: 10.3923/jai.2019.18.23

URL: https://scialert.net/abstract/?doi=jai.2019.18.23

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