审查数据分析和信息系统在提高金融服务效率方面的作用:行业案例研究

Tonmoy Barua, Sunanda Barua
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摘要

本研究探讨了整合数据分析和信息系统对提高金融服务业效率的变革性影响。研究通过对摩根大通、全州保险、贝莱德和美国银行的详细案例研究,强调了在运营效率、风险管理和客户满意度方面的重大改进。研究结果显示,摩根大通人工智能驱动的分析工具使欺诈相关损失减少了 30%,客户满意度提高了 20%。通过预测分析,全州保险公司的理赔处理时间缩短了 40%,承保准确率提高了 25%。贝莱德报告称,通过机器学习和预测分析,投资组合回报率提高了 35%。相比之下,美国银行通过数据驱动的客户关系管理系统,客户保留率提高了 22%,满意度提高了 15%。这些成果凸显了先进的数据分析和信息系统在推动金融服务创新和卓越运营方面的关键作用。该研究强调了持续技术进步和战略实施的重要性,以最大限度地发挥这些工具在行业中的效益。
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REVIEW OF DATA ANALYTICS AND INFORMATION SYSTEMS IN ENHANCING EFFICIENCY IN FINANCIAL SERVICES: CASE STUDIES FROM THE INDUSTRY
This study explores the transformative impact of integrating data analytics and information systems on enhancing efficiency in the financial services industry. The research highlights significant improvements in operational efficiency, risk management, and customer satisfaction through detailed case studies of JPMorgan Chase, Allstate Insurance, BlackRock, and Bank of America. The findings reveal that AI-driven analytics tools at JPMorgan Chase led to a 30% reduction in fraud-related losses and a 20% increase in customer satisfaction. Through predictive analytics, Allstate Insurance achieved a 40% reduction in claims processing time and a 25% improvement in underwriting accuracy. BlackRock reported a 35% increase in portfolio returns due to machine learning and predictive analytics. In comparison, Bank of America experienced a 22% increase in customer retention and a 15% rise in satisfaction through data-driven CRM systems. These outcomes underscore the critical role of advanced data analytics and information systems in driving innovation and operational excellence in financial services. The study emphasises the importance of continuous technological advancements and strategic implementation to maximise the benefits of these tools in the industry.
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