Case Study: National Electrical Components Distributor reduces bad debt by $15M with dotData

Component Supplier Lowers Bad Debt $15M With Machine Learning Credit Risk Assessment

a national electrical components distributor faced significant challenges in managing credit risk and bad debt across its portfolio of over 10,000 B2B customers. The sheer volume of clients made manual, gut-instinct assessments by regional managers impractical and unscalable, leading to millions in unpaid invoices. The company lacked a data science practice and needed to find an advanced method to predict potential credit defaults, a problem exacerbated by the economic uncertainty of the pandemic.

The distributor implemented dotData's AI platform, leveraging its proprietary automated feature engineering (AutoFE) and automated machine learning (AutoML) technology to build a predictive model. The solution analyzed billions of data points to identify over 400 risk-indicating patterns, automating 80% of the credit management workload. As a result, dotData helped the client reduce its annual bad debt by $15 million, which equated to a 1% increase in annual revenue.