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Swarm Intelligence for Predictive Analytics in Insurance and Finance
Abstract
Swarm Intelligence (SI), inspired by the collective behavior of social organisms such as ants, bees, and birds, has emerged as a powerful tool in the realm of predictive analytics. This chapter delves into the applications of SI in insurance and finance, illustrating how algorithms such as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC) can optimize predictive models for risk assessment, fraud detection, customer segmentation, and portfolio management. Through case studies and empirical evaluations, this chapter highlights the strengths of SI-based approaches in enhancing decision-making, accuracy, and efficiency. Additionally, ethical considerations and computational challenges associated with implementing SI in predictive analytics are discussed.
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