VALKYRIE

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CASE 00X

We developed a risk prediction engine that more appropriately determined credit risk by basing it on customer behavior. Our models used a variety of data sources to better identify and understand the key behavioral indicators that drive loan repayment.

INTELLIGENT APPLICATION OF ALTERNATIVE DATA

BETTER RISK ASSESSMENT WITH BEHAVIORAL ANALYSIS

MITIGATING RISK WITH LIMITED DATA

Our client, an international bank, sought to reduce the default rate for small loans in emerging markets. Modeling risk in this environment presented a significant challenge for the bank, as most customers had a limited digital footprint.  As a result, less reliable demographic information was used to assess creditworthiness.

INSIGHT PLUS QUOTE

"I’m a paragraph. Double click here or click Edit Text to add some text of your own or to change the font. This is the place for you to tell your site visitors a little bit about you and your services."

- Name & Title Attribution

Scientific Summary

  • Feature Engineering

  • Graph Theory

  • Data Architecture & Domain Structure

  • ETL Design (Extract, Transform, Load)

Strategic Summary

  • Feature Engineering

  • Graph Theory

  • Data Architecture & Domain Structure

  • ETL Design (Extract, Transform, Load)

Integrating our model into the underwriting process cut the bank’s default rate in half, and is projected to create savings of tens of millions of dollars annually.