Artificial Neural Network Model for Predicting Insurance Insolvency
الموضوعات :Ade Ibiwoye 1 , Olawale Ajibola 2 , Ashim Sogunro 3
1 - Department of Actuarial Science and Insurance, University of Lagos, Akoka, Yaba, Lagos
2 - Department of Systems Engineering, University of Lagos, Akoka, Yaba, Lagos
3 - Department of Actuarial Science and Insurance, University of Lagos, Akoka, Yaba, Lagos
الکلمات المفتاحية: insurance, Financial protection, Artificial Neural Network, insolvency, Ratio analysis, Training, prediction model, Early warning signal,
ملخص المقالة :
In addition to its primary role of providing financial protection for other industries the insurance industry also serves as a medium for fund mobilization. In spite of the harsh economic environment in Nigeria, the insurance industry has been crucial to the consummation of business plans and wealth creation. However, the continued downturn experienced by many countries, in the last decade, seems to have impacted negatively on the financial health of the industry, thereby rendering many insurance companies inherently distressed. Although there is a regulator to monitor the insurance companies in order to prevent insolvency and protect the right of consumers this oversight function has been made difficult because the regulators appeared to lack the necessary tools that would adequately equip them to perform their oversight functions. One such critical tool is a decision making model that provides early warning signal of distressed firms. This paper constructs an insolvency prediction model based on artificial neural network approach which could be used to evaluate the financial capability of insurance companies.