DATA SCIENCE

Our Data Science Team specializes in scientific methods, processes, and data platforms to extract insights from structured or unstructured data. We focus on understanding and analysis of “actual phenomena” associated with data.  Our team employs techniques drawn upon the broad areas of mathematics, statistics, information science, and computer science, especially from the areas of machine learning, classification, cluster analysis, data mining, databases, and visualization.

WE CAN HELP YOU …

  • Conduct Current State Evaluation.  Complete an in-depth assessment of current modeling initiatives and end-to-end data decisioning processes.
  • Make Recommendations. Provide recommendations that can effectively enhance data capturing processes; identify steps to improve data modeling and mitigate risk, and suggested practices to optimize speed of data driven decision making.
  • Prioritize. Determine the appropriate allocation of scarce data science resources to achieve key business goals and objectives.
  • Execute. Provide highly skilled data science resources to assist with the implementation of recommendations. Options include a team of onshore or a blend of onshore and offshore data scientists.

CASE SUMMARY 1

DecisivEdge Principals led the development of a credit underwriting model for a Fortune 500 financial services company. The new credit strategy  modeled solution resulted in the automation of a personal loan credit underwriting process. Our auto-decisioning solution significantly reduced manual credit review costs and increased both the speed and capacity to process time sensitive credit applications.

CASE SUMMARY 2 

DecisivEdge Principals developed a suite of marketing acquisition models for a Fortune 500 financial services company that enabled targeted messaging to a selected customer segments. The models significantly improved target marketing campaign performance.

CASE SUMMARY 3

DecisivEdge Principals led the development of an attrition model for a Fortune 500 global ‎document solutions and services company. The model enabled the business to identify high risk accounts. Along with the attrition model, a communication strategy was developed to trigger “red-alert” messages to the sales force for  target prospects  and cross selling to existing customers.

CASE SUMMARY 4

DecisivEdge Principals designed a customer segmentation model for a Fortune 500  healthcare insurance company. The model supported the design of a new product for the direct to consumer sales channel. This product was successfully launched both on and off the healthcare exchanges.