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Below, you will find a collection of articles, press releases and technical papers representing the company, our passions, and our people. 

Reducing Customer Attrition with Predictive Analytics for Financial Institutions

As smaller banks market themselves to increase their market share against the big banks, they understandably focus on gaining new customers. However, they must also retain (and further engage) their existing customers. Otherwise, the new customers they gain can easily be offset…

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Stakana Launches “Member Retention Project” to Help Credit Unions Hold on to Members.

Seattle, Wash. (August 24, 2015) — Stakana Analytics has launched the Member Retention Project, an affordable solution designed to help credit unions of all sizes keep from losing existing members through the use of cutting-edge predictive analytics. The business intelligence…

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Managing and Monitoring Statistical Models

Managing and monitoring statistical models can present formidable challenges when you have multiple models used by a team of analysts over time. How can you efficiently ensure that you’re always getting the best results from your models? In this paper, we’ll first…

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Visualizing Your Data When There is Too Much of It to Visualize

In many of the SAS Institute publications about the new ODS statistical graphics, there is an introductory statement that defines an “effective” graph as one that reveals “patterns, differences and uncertainty that are not readily apparent in tabular output” (Kuhfeld, 2010; Rodriguez,…

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Managing and Monitoring Statistical Models

Managing and monitoring statistical models can present formidable challenges when you have multiple models used by a team of analysts over time. How can you efficiently ensure that you’re always getting the best results from your models? In this paper, we’ll first…

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An Introduction to the Analysis of Rare Events

Analyzing rare events like disease incidents, natural disasters, or component failures requires specialized statistical techniques since common methods like linear regression (PROC REG) are inappropriate. In this paper, we’ll first explain what it means to use a statistical model, then explain why…

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