Driving Success with Predictive Analytics & Machine Learning

Many finance leaders are seeking predictive analytics and machine learning (PAML) technologies to deliver better outcomes to customers and stakeholders. However, a recent Forrester study found that only 15% of organizations have adopted these technologies. There is a major discrepancy between adoption of PAML technologies and intent to adopt, because over 90% of organizations say PAML is important for building more personalized customer experiences and is needed to drive efficiency with back-end and customer-facing applications. A common obstacle to adoption is that organizations are typically split into two sides of the house: the experimental side and the operations side, often at a rapid clip. There are three core attributes to drive success with PAML technologies.

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