BETTER RISK ASSESSMENT WITH BEHAVIORAL ANALYSIS

Valkyrie engaged with an international financial institution client to assist in reducing their default rate for personal loans. Through ingesting their data sources and experimenting on the data with the hypotheses we generated, Valkyrie scientists were able to build a custom risk prediction engine that successfully cut the client’s default rate in half.

The Challenge

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.

The Solution

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.

The Outcome

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. Our team was able to show this company the ways in which behavioral data works as a better indicator of financial reliability than traditional risk measurements.

Avg. Default Rate

50 %

Reduction

Research & Development

10

Weeks

Projected Savings

$ 10 mil

Annually

Office

515 Congress Ave. Austin, TX 78701 Suite #1425

Email

inquiries@valkyrie.ai

Phone

(512) 947 – 6472

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