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Risk Evaluation in the Insurance Company Using REFII Model (CROSBI ID 58332)

Prilog u knjizi | ostalo

Klepac, Goran Risk Evaluation in the Insurance Company Using REFII Model // Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods / Satchidananda Dehuri (Fakir Mohan University, India), Manas Ranjan Patra (Berhampur University, India), Bijan Bihari Misra (Silicon Institute of Technology, India) and Alok Kumar Jagadev (Siksha O Anusandhan University, India) (ur.).: IGI Global, 2013. str. 84-104

Podaci o odgovornosti

Klepac, Goran

engleski

Risk Evaluation in the Insurance Company Using REFII Model

A business case describes a problem present in all insurance companies: portfolio risk evaluation. Such analysis deals with determining the risk level as well as main risk factors. In the specific case, an insurance company is faced with market share growth and profit decline. Discovered knowledge about the level of risk and main risk factors was not used to increase premium for the riskiest portfolio segments due to a specific market situation, which could lead to loss of clients in the long run. Instead, additional analysis was conducted using data mining methods resulting in a solution, which stopped further profit decline and lowered the risk level for the riskiest portfolio segments. The central role for the unexpected revealed knowledge in the chapter acts as the REFII model. The REFII model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series.

Risk Evaluation, REFII Model

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Podaci o prilogu

84-104.

objavljeno

Podaci o knjizi

Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods

Satchidananda Dehuri (Fakir Mohan University, India), Manas Ranjan Patra (Berhampur University, India), Bijan Bihari Misra (Silicon Institute of Technology, India) and Alok Kumar Jagadev (Siksha O Anusandhan University, India)

IGI Global

2013.

0-553-57777-8

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