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Abstract Details
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Activity Number:
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14
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Type:
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Topic Contributed
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Date/Time:
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Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section for Statistical Programmers and Analysts
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| Abstract - #306099 |
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Title:
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Statistical Modeling for Large Financial Data Sets
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Author(s):
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Antonello Loddo*+
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Companies:
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Capital One
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Address:
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3200 Shandwick Pl., Fairfax, VA, 22031, United States
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Keywords:
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cunsumer financial ;
statistical modeling ;
large data
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Abstract:
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Statistical modeling for the consumer financial industry presents some unique characteristics. Large sample sizes and focus on predictive modeling of complex behaviors make for a typical directed data mining problem. However, models used for credit decisions might require treatment conditional predictions. This, coupled with interpretability requirements, render some supervised learning approaches unfeasible. In addition, economic knowledge, econometric methodology, business insights and additional information not included in the data can be used to improve model performance. This study focuses on these aspects of modeling consumer financial data, and how statisticians can leverage them in order to build better models.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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