When Hare Beats Tortoise: Knowing When to Train Your Predictive Models

Presented by

Sean Naismith, Head of Analytics Services, Enova Decisions

About this talk

Businesses are realizing the benefits of predictive analytics, especially when using the latest technologies in machine learning & AI. The prevailing methodology has been to train predictive models in order to determine which data is useful and which data is not prior to deployment. While training improves the predictive power of your predictive models, there are cases when training prior to deployment may not make sense for your business. This session discusses how to determine when to train your models and how to effectively turn the insights from your models into action that improves business outcomes. Key Takeaways: • How machine learning & AI can boost business performance • How to determine when to train your predictive analytics models • How to turn analytics to action through digital decisioning

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With Enova Decisions, businesses can leverage powerful analytics to make instant real-time decisions at scale, protecting against fraud, optimizing operations and increasing marketing profitability. Enova Decisions uses real-time predictive analytics, AI, big data, and its on-demand digital decisioning platform, Colossus, to help companies build decision flows that make data-driven operational decisions instantly and at scale for an improved business performance and customer experience. Chicago-based Enova Decisions is part of Enova International, Inc. (NYSE: ENVA), a leading technology- and data-analytics-driven online lending company that operates 10 brands in four countries. Enova now leverages its 14 years of proven technology and analytics expertise to help clients thrive with custom, real-time analytics services and instant data-driven decisions at scale. Visit www.enovadecisions.com to learn more.