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The banking and financial services are at the center of all commercial activity. When the data revolution hit various industries, the banking industry took advantage of the opportunities. In the last couple of decades, technology has played a vital role in the evolution of the banking and finance industries. The way that banks operate and the cutting-edge services they offer have made life easier for both banking professionals and customers. 

Lifetime Value Prediction

Customer lifetime value is an estimate of the benefits a company will have from its relationship with the customer. The significance of this measure is growing as it assists with making and maintaining helpful associations with selected customers, generating higher benefits and business development. Procuring and holding productive clients is a constant test for banks. As competition rises, banks need a 360◦ view on every client to effectively center their assets. As large quantities of data, such as thoughts of customer’s securing and weakening, utilization of banking  applications and services, their volume and profits, and customer attributes (geography, demography, market information, etc.) must be taken into account, this is where data science comes in.

Enhanced Customer Satisfaction

Real-time analysis on banks’ huge quantities of customer data empowers them to convey exceptionally customized services that leverage knowledge derived from conduct, budget history, social networking, and information feedback. Banks can then use this data to create meaningful reports to plan new services and products. Data science teams can study customer behavior to find precisely when and where clients need the most guidance and support them with better administrations of managing money, social-segment patterns, area, etc.

Managing Customer Data

Nowadays, banks collect, analyze, and store data, but with the use of machine learning, this process has become more efficient. Thanks to the growing use of digital banking, there is a larger production of customer data storage. The only way to successfully complete this is with the use of machine learning. With access to information regarding customer behaviors, interactions, and preferences, companies can produce better results from customer interactions.

Resources

Case Study
Providing better, relevant, and real-time merchant offers to credit card customers
Case Study
Explore the use case of a leading bank transforming business and enable customer experiences with Digitial initiatives
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Data Governance a Path to better credit Analytics

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