Yogyakarta, July 15, 2025 — The “Time Series Model for Risk Management and Insurance” workshop entered its second day with a focus on advanced approaches in time series data analysis, particularly to address challenges in financial resilience and nonlinear models. The event was held in Meeting Room 1 of the UGM Department of Mathematics.
The first session began with a presentation by Dr. Mohd Mahayaudin Mansor from Universiti Teknologi MARA (UiTM), Malaysia, on the topic “Autoregressive Models and the Case for Nonlinearity.” In his presentation, Dr. Mahayaudin explained the limitations of conventional autoregressive models in capturing the complex dynamics of financial and insurance data. He also highlighted the importance of considering the possibility of nonlinear relationships in data, which often occur in economic and climate phenomena.
After a short break, the second session was continued by Danang Teguh Qoyyimi, M.Sc., Ph.D., a lecturer in the Actuarial Science Study Program at UGM. In his presentation titled “Patterns Over Time: The Critical Role of Time Series Analysis in Achieving Financial Resilience,” Dr. Danang explained how actuarial science can be applied in various public sectors, including disaster financing, management of social security employment funds, and the role of actuaries in the Hajj financial system. Time series analysis can strengthen the role of actuarial science not only in insurance modeling but also in enhancing resilience across various public sectors.
After the lunch break, the third session was again led by Dr. Mahayaudin with the topic “TAR Models: Why Linear Models Aren’t Always Enough.” This session was a continuation of the previous discussion, focusing on Threshold Autoregressive (TAR) models, which allow for structural shifts in data based on certain thresholds. Dr. Mahayaudin demonstrated how these models are more accurate in capturing changes in data behavior that cannot be explained by ordinary linear models.
The conclusion of this session also marked the end of the second day’s activities, which collectively provided technical and in-depth insights into the application of time series models in risk management and insurance, as well as their application in enhancing public sector resilience.
Keywords: Time Series Modeling, Risk Management, Actuarial Science
Author: Fathan Rasyid Rahmadhan
Photo: Shafira Fauzia Untsa