• Enterprise Applications

Big Data is creating tremendous opportunities for financial services institutions to leverage untapped data sources, integrate unstructured data, and gain insights through better visualization. NDM has proven methodologies, technologies, and industry insights that you can use to manage the entire Big Data lifecycle.

  • Predict Buyer Behavior: Leveraging vast amounts of structured and unstructured data, banks can recommend products based on individual customer attributes, driving increased revenue per customer and predicting at-risk customers taking action before they leave to a competitor.
  • Improve Customer Service: Firms can reach out to external data sources (such as social media data and off-platform behavior), match the social media identity to user account, and perform sentiment analysis to improve customer satisfaction score.
  • Identify and Reduce Risk: With analytics, underwriting that takes days on legacy systems can be done in minutes, resulting in daily risk model updates that reduce underwriting risk. Factors including applicant social and profession history can be added to reduce default risk.


Until now, most financial services firms have been trying to answer key questions about the customers, risk profile, and financial products by looking in the rear-view mirror with a fractional subset of the information available across the enterprise.

Because of this, business leaders are limited, both in the questions they can answer and in the answers they can get.


NDM advises financial firms – their IT experts and their business executives– on how best to manage and make commercial use of big data. The IT departments want to know about the practicalities of gathering, cleansing, analyzing, storing and retrieving, and ultimately monetizing the data.

The first step is NDM’s Big Data Advisory Service. We match new technology developments to the business opportunities. We review Big Data trends and directions, sparking ideas by presenting case examples of how other organizations are leveraging Big Data and through the service, guide the participants through a prioritization process where each business opportunity is judged based upon its relative business value.


  • Predict buyer behavior to increase revenue
  • Reduce financial and operational risk with external data
  • Improve service and increase customer satisfaction