Enhancing security and risk management with predictive analytics: A proactive approach
Enhancing security and risk management with predictive analytics: A proactive approach
Ibrahim Adedeji Adeniran,Christianah Pelumi Efunniyi,Olajide Soji Osundare,Angela Omozele Abhulimen
TLDR
Organizations' need to integrate predictive analytics into their risk management frameworks to enhance resilience and ensure long-term success in a rapidly evolving risk landscape is emphasized.
Abstract
and interconnected world. This paper explores the transformative potential of predictive analytics in enhancing security and risk management by shifting from reactive to proactive strategies. Examining the theoretical foundations and application areas of predictive analytics, the paper highlights how organizations can anticipate and mitigate risks across various domains, including cybersecurity, fraud detection, and supply chain management. The benefits of predictive analytics, such as early threat detection and optimized resource allocation, are discussed alongside data quality, privacy, and model interpretability challenges. Additionally, emerging trends, such as artificial intelligence, real-time data analytics, and blockchain technology, are key drivers shaping the future of predictive analytics in risk management. The paper concludes by emphasizing organizations' need to integrate predictive analytics into their risk management frameworks to enhance resilience and ensure long-term success in a rapidly evolving risk landscape.

