International Conference on Insurance Mathematics and Statistics - (ICIMSTAT-26)
9th - 10th October, 2026 | Ishwarganj, Bangladesh
Multi-format (In-person/Virtual)
Explore conference registration categories designed for every mode of participation.
9th September, 2026
14th September, 2026
24th September, 2026
9th - 10th October, 2026
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.
SDG 1 — No Poverty
SDG 3 — Good Health and Well-being
SDG 4 — Quality Education
SDG 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
This track focuses on advanced statistical techniques used in the assessment and management of insurance risks. Participants will explore methodologies that enhance predictive accuracy and decision-making in risk evaluation.
This session will delve into mathematical models that underpin actuarial science, emphasizing their applications in pricing, reserving, and risk management. Researchers are encouraged to present innovative approaches that improve model robustness and applicability.
This track examines the role of data analytics in optimizing insurance operations and enhancing customer experience. Discussions will center on the integration of big data and machine learning techniques in insurance practices.
Participants will explore the application of stochastic processes in modeling various insurance-related phenomena. This session aims to highlight theoretical advancements and practical implementations in the field.
This track investigates econometric models specifically designed for insurance pricing strategies. Contributions should focus on empirical studies that demonstrate the effectiveness of these models in real-world scenarios.
This session addresses quantitative approaches to risk management within the financial services sector, with a focus on insurance companies. Participants will share insights on regulatory challenges and innovative risk mitigation strategies.
This track will cover statistical inference techniques applicable to insurance datasets, emphasizing the importance of accurate data interpretation. Researchers are invited to present novel methods that enhance inference reliability.
This session focuses on the burgeoning field of machine learning and its applications within the insurance industry. Participants will discuss case studies and methodologies that leverage machine learning for improved underwriting and claims processing.
This track explores the intersection of behavioral economics and insurance, analyzing how psychological factors influence decision-making processes. Contributions should highlight empirical findings that inform better insurance practices.
This session will focus on the theoretical foundations of risk theory and its practical applications in insurance. Participants are encouraged to present research that bridges theoretical insights with real-world implications.
This track addresses emerging trends and methodologies in insurance statistics, focusing on innovations that shape the future of the industry. Discussions will include new statistical tools and their impact on insurance analytics.