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Dedy Dwi Prastyo
Department Of Statistics, Institut Teknologi Sepuluh Nopember
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Journal : Bulletin of Applied Mathematics and Mathematics Education

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Predicting financial distress in Indonesian life insurance companies with classification methods and synthetic features generation Purwanto, Dwi; Prastyo, Dedy Dwi
Bulletin of Applied Mathematics and Mathematics Education Vol. 5 No. 1 (2025)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bamme.v5i1.13114

Abstract

Financial problems in life insurance companies can become serious if not addressed immediately. Companies experiencing financial distress, for instance, are unable to meet their obligations to pay their liabilities. A company can be categorized as experiencing financial distress when it has an RBC ratio of less than 120%—based on regulation by the Indonesian Finance Service Authority—or ROA < 0 (suffering loss). Therefore, financial distress prediction is carried out to assess the company's current financial condition so that it can be handled early. In this study, we aimed to predict financial distress of Indonesian life insurance companies. We utilized the Support Vector Machine (SVM) classification method, Generalized Extreme Value Regression (GEVR), and Extreme Gradient Boosting (XGB) and by incorporating synthetic feature generation in variable selection. The results of financial distress prediction obtained the best model that can predict the financial condition of life insurance companies in Indonesia at each size, where for sizes 0 and 1, the XGB model with variable selection produces accuracy values of 98.00% and 94.10%, respectively, and AUC values of 100% and 87.40%. Then, at size 2, we can use Stepwise Generalized Extreme Value Regression with accuracy and AUC results of 90.20% and 82.60%, respectively. Each addition of size to the time window classification results tends to reduce the model's performance in predicting the financial condition of life insurance companies in Indonesia.
Co-Authors A. Tuti Rumiati Abdul Karim Abdul Karim Adatul Mukarohmah Affandy*, Nur Azizah Ahsan, Muhammad Akhmad Faturohman Bambang Widjanorko Otok Bambang Widjanorko Otok Budi Manfaat budi manfaat, budi Danny Hermawan Adiwibowo Data Iranata dwi purwanto Era Ardhya Pramesti Erma Oktania Permatasari Faturohman, Akhmad Fithriasari, Kartika Forestryani, Veniola Fredi Suryadi Fredi Suryadi Hendri Prabowo Heri Kuswanto Hidayatul Khusna Husna Miratin Nuroini Ismaini Zain Luh Putu Shintya Handayani Maharsi, Rengganis Woro Maulana, Mahendra Andiek Muhammad Hisyam Lee Muhammad Sjahid Akbar Nadjadji Anwar Novi Ajeng Salehah Prandipa, Rayza Pusaka, Semerdanta Rhifda Zukhrufi Rizki Nanda Savera Roosyidah, Nila Ayu Nur S Suhartono Salafiyah Isnawati Santi Eksiandayani Santi Puteri Rahayu Saputra, Wisnowan Hendy Setiawan Setiawan Setiawan Setiawan Shofi Andari Suhartono Suhartono Suhartono Suhartono Suhartono Suhartono Supriyatna, Putu Krishnanda Veniola Forestryani Vita Ratnasari Wardoyo, Wasis Wibawati Wibawati Widhianingsih, Tintrim Dwi Ary Yusop, Zulkifli