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Banks, credit unions, and other lenders are constantly challenged to lend responsibly, improve customer experience, increase profitability, and advance their competitive positions. Achieving these goals without taking on more credit risk, spending heavily on marketing, or taking on big and challenging technology projects is often difficult.
Leading institutions are using advanced predictive analytics to transform their marketing, origination, account management, and collections and recovery processes. But not all businesses are equally prepared to develop and deploy their own analytics, and the leading data science talent necessary to build effective models can be hard to find and expensive to retain. Even organizations deep in data science talent often have operational bottlenecks that make it difficult to deploy analytics to generate timely business value.