The Implementing of SPIA in Big Data Analytics on The Effectiveness of Fraud Prevention
DOI:
https://doi.org/10.59188/eduvest.v4i12.1793Keywords:
SPIA, Big Data Analytics, Fraud Prevention, Qualitative Study, Case Study, Predictive IntelligenceAbstract
This study explores the impact of implementing the SPIA (Systematic Predictive Intelligence Analysis) framework in big data analytics on the effectiveness of fraud prevention. Utilizing a qualitative case study approach, this research delves into how SPIA can enhance the detection and prevention of fraudulent activities by analyzing vast amounts of data in real-time. Data were collected through interviews with industry experts and professionals who have implemented SPIA in their fraud prevention strategies. The findings reveal that SPIA significantly improves the accuracy and speed of identifying potential fraud cases, leading to more proactive and efficient fraud management. Additionally, the study highlights the challenges and opportunities associated with integrating SPIA within existing big data systems. These insights contribute to the broader understanding of the role of advanced analytics in combating fraud and offer practical recommendations for organizations seeking to strengthen their fraud prevention mechanisms.
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