Case Study

MACHINE LEARNING APPLICATIONS HELP TOP-20 EUROPEAN BANK MEET EVOLVING CONSUMER NEEDS

MACHINE LEARNING APPLICATIONS HELP TOP-20 EUROPEAN BANK MEET EVOLVING CONSUMER NEEDS

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CUSTOMER SUCCESS STORY MACHINE LEARNING APPLICATIONS HELP TOP-20 EUROPEAN BANK MEET EVOL VING CONSUMER NEEDS Challenge The bank’s challenge was harnessing large quantities of data from disparate sources into one place, illustrating the power of using alternative data. This would enhance the decision process to fit the evolving needs of customers. With consumer preferences shifting away from credit card spend and more towards direct debits and indirect financing, fewer and fewer customers have a significant amount of credit bureau information associated with them. For example, younger buyers seeking financing for buying smartphones. Less credit history available presented a challenge in making traditional lending decisions. Additionally, the bank needed a solution to connect data science t

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