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Implementing predictive analytics allows financial firms to find previously hidden patterns in data that can amplify business results, reduce churn, increase marketing effectiveness, and more.
FREMONT, CA: With the advent of connected technologies, more and more data is delivered every day. Businesses are struggling to derive a more innovative approach for analyzing and using these data volume. Proving it as active method business developers and managers in the financial sector are adopting data analytics to tackle the future challenges caused by data. According to one latest report, worldwide revenues for big data and business analytics will go up to more than $203 billion in 2020. Financial institutions are realizing and reaping the benefits. Its applications are as follows.
Along with the arrival of digitization, fraudulent practices in financial institutions have become more common, which raises the need to adopt more intelligent systems to deal with cybercriminals. The role of analytics here is to recognize frauds, while predictive analytics are implemented to analyze the likelihood of fraudulent activities further and detect them at the earliest possible. This is done through data integration and processing of unstructured data, which helps identify patterns and repetitive behaviors. The ability of predictive analysis to understand and analyze underlying fraud risks takes center stage of the success of financial institutions
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Majority of financial institutions claim that their top priority is to understand better, predict customers, and give them the quality of services they need. With predictive analytics, banks and financial firms can make an in-depth analysis of the customer base and predict customers behaviors. It examines customers’ performance and spending and then targets the best product offerings to the most appropriate customer group. Firms can thus build solid relationships based on loyalty and continuous customer engagement resulting in better customer experience.
The financial services institutions are among the most advanced users of predictive analytics, with which they are enabled to make more data-oriented decisions to improve fraud detection, customer retention, which translates to overall productivity.