The Big 3: Big Data, Big Mining, Big Profit
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  Derly Almanza   Derly Almanza
Data Management and Business Analytics expert


Wednesday, April 30, 2014
08:30 AM - 09:15 AM

Level:  Business/Strategic

Financial institutions are facing the challenge of becoming more accurate in their customer retention strategy. Particularly in the case of Latin American markets banks are also being faced with new competitors such as retail stores, who are willing to take greater risks to expand its market share.

This presentation describes an approach to addressing this important Customer Master Data problem based on predicative analytics using techniques based on Big Data and data mining.

While this approach can more accurately identify customers more likely to "churn" (move to a competitor), companies find it difficult to quantify the benefits of such projects. In this session you will discover through a case study a methodology for quantifying the business case and be more effective in the internal sale of business analytics projects.

In this session you will learn:

  • How to identify the key points for securing the internal buy-in of Big Data Analytics projects.
  • Understand through a practical case study the power of advanced techniques for business analytics to support your Customer Retention strategy.
  • Discover how to quantify the business case for your Customer Retention programs and support them through predictive techniques.

Derly Almanza is currently Director of Business Intelligence at an important financial company in Colombia. Derly is a Certified Data Management Professional (CDMP), she is Statistician, and she is Master of Data Mining and Knowledge Discovery. Derly has broad experience in assessing companies in Latin America on the implementation of analytical solutions and information management projects, and supporting business strategies to achieve important economic benefits. She is currently leading the formation of a DAMA chapter in Colombia. Derly’s expertise includes business analytics, marketing research, data mining and business intelligence.

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