Best Practices for Predictive Analytics in B2B Financial Services

  • Authors:
  • Raul Domingos;Thierry Van de Merckt

  • Affiliations:
  • VADIS Consulting;VADIS Consulting

  • Venue:
  • Proceedings of the 2010 conference on Data Mining for Business Applications
  • Year:
  • 2010

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Abstract

Predictive analytics is a well known practice among corporations having business with private consumers (B2C) as a means to achieve competitive advantage. The first part of this article intends to show that corporations operating in a business to business (B2B) setting have similar conditions to use predictive analytics on their favor. Predictive analytics can be applied to solve a myriad of business problems. The solutions to solve some of these problems are well known while the resolution of other problems requires quite an amount of research and innovation. However, predictive analytics professionals tend to solve similar problems in very different ways, even those to which there are known best practices. The second part of this article uses predictive analytics applications identified in a B2B context to describe a set of best practices to solve well known problems (the “let's not re-invent the wheel” attitude) and innovative practices to solve challenging problems.