White Papers

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Grow Profits and Reduce Loan Rejection Rates with Machine Learning

Read this white paper to learn how lenders can:

  • Use Machine Learning to refine their data models
  • Grow profits
  • Reduce loan rejection rates
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 Accelerate Mobile Onboarding with Machine Learning

Accelerating Mobile Account Opening with Machine Learning

Read this white paper to learn how organizations can:

  • Validate the identities of mobile users, typically by analyzing photos of driver's licenses or other IDs.
  • Complete this authentication in real time in order to reduce application abandonment rates that can reach as high as 80%.
  • Deliver a great experience for mobile users, who have high expectations for fast, frictionless service.
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Leveraging Data Analytics to Deliver a Frictionless Customer Journey

Read this white paper to learn:

  • Why reducing friction is critical for banks, credit unions, FinTechs, and other organizations in the financial services market.
  • The critical role that data analytics can play in reducing friction, especially for mobile account opening.
  • How Accelitas' patented solution for mobile account opening reduces frictions and helps organizations grow profits and reduce risks.
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Growing Revenue by Focusing on Profitability, Not First Payment Default

Many lenders base their lending decisions on predictions of First Payment Default (FPD), rather than on likely account profitability. But our analysis of multiple lenders shows that, when it comes to predicting actual profitability, FPD is no more reliable than a coin toss. Using Accelerated Insight, lenders can build decision models that focus on real business outcomes while also reducing FPD.

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Unlocking the Potential of Mobile Banking with Predictive Insights

The next frontier in digital finance is mobile account opening. By 2020, one in four financial accounts will be opened on a mobile device. Enabling consumers to open accounts on smartphones and tablets is especially critical for those institutions interested in serving tech-savvy Millennials or unbanked and underbanked households who use smartphones as their sole means of Internet access.

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