DKW Analytics provides quick turn around in developing predictive models. We focus on models that are both accurate and understandable. Our models are designed for easy incorporation into a production environment for scoring new data. We are highly familiar with a variety of tools including SAS, Python, and R; and we make use of a variety of modeling techniques from both the statistics and machine learning fields. We are experienced in a wide range of applications including the ones listed below.

Customer Relationship Management (CRM) Analytics

  • Customer Churn
  • Customer Lifetime Value
  • Customer Response
  • Next Best Action
  • Customer Segmentation
  • Transaction (Recency/Frequency/Amount)
  • Retail store placement

Banking / Financial Services

  • Credit Risk
  • Loss Given Default
  • Prepayment Analytics
  • Stress Testing
  • Financial Manager / Relationship Manager Churn


  • Rating and Underwriting
  • Territory Factors
  • Usage Based Insurance (Telematics)

General Analytics

  • Time Series
  • Fractal Analysis / Chaos Modeling of Time Series
  • Text Mining / Natural Language Processing (NLP)
  • Artificial Intelligence / Machine Learning
  • Fraud Analytics
  • Cluster Analysis including “Fuzzy” Clustering