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© 2014 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. Why Wells Fargo Has Its Head in the Cloud Using Scorecards and Decision Trees, and How That's Paying Off Nathan Pelzer Advanced Analytics Consultant Wells Fargo Real Estate Credit Management Lamar Shahbazian Senior Director FICO
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© 2014 Fair Isaac Corporation. Confidential. Real estate collections has faced competing priorities, a volatile housing market, and changes in customer payment patterns. 2 Something needed to change.
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© 2014 Fair Isaac Corporation. Confidential. And it did.. We even exceeded our expectations. 3
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© 2014 Fair Isaac Corporation. Confidential. What if it was like… © 2014 Fair Isaac Corporation. Confidential.4
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► Six portfolios Six collection strategies ► Different definitions of good and bad ► Combination of lines/loans/prime/subprime/first and junior liens ► Both owned and serviced accounts ► Different sets of credit bureau attributes ► Data from multiple legacy systems Model and Data Environment 5
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© 2014 Fair Isaac Corporation. Confidential. Delinquency Trends in Real Estate Collections Despite improving economy, longer term bad rates showed little change Bucket 1 Long-Term Delinquency by Quarter (Portfolios 1 and 2) Bucket 1 Population: Bad Rates by Portfolio 6
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© 2014 Fair Isaac Corporation. Confidential. What We Needed to Do Right Away Improve long-term delinquency rate While… Maintaining short-term roll rates Existing Model Performance Bucket 1 Population: Portfolios 1 and 2 7
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© 2014 Fair Isaac Corporation. Confidential. ► Simplify models and process ► Maintain or improve model performance ► Treat customers consistently across portfolios What We Needed in the Long Run 8
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© 2014 Fair Isaac Corporation. Confidential. ► Modify strategies to address concerns over longer-term delinquency ► Easier and quicker to implement ► Develop a new suite of scorecards to address all of the competing priorities ► Better long-term solution ► Requires more resources and time Our Two-Phase Approach © 2014 Fair Isaac Corporation. Confidential.9
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Why Use Decision Trees? ► Intuitive ► Visual ► Easy to explain ► Strong segmentation ► Profile end nodes for effective treatment Strategy Design 10
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© 2014 Fair Isaac Corporation. Confidential. ► Existing relationship (long-time users of Scorecard Professional powered by Xeno) ► SaaS environment enabled collaboration ► Evaluated current strategy and opportunities to improve ► Needed ability to use multiple objectives ► Wanted to assign treatments and evaluate them ► Needed ability to evaluate swap sets We Chose FICO ® Analytic Modeler Decision Trees Professional 11
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© 2014 Fair Isaac Corporation. Confidential. Phase I: Improve Long-Term Delinquency Rate 12
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© 2014 Fair Isaac Corporation. Confidential. ► Refine segmentation and look for nuances ► Figure out: How are predictors of short-term roll rate different from those of long-term delinquency? ► Develop more effective treatments ► Design improved strategy Game Plan: Segmentation and Treatment 13
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© 2014 Fair Isaac Corporation. Confidential. ► Accounts are currently ranked into tiers based on their likelihood of rolling delinquent within the next month ► These segments were examined using the a longer term delinquency outcome Using Decision Trees to Improve Collections Segmentation 14 Short-term bad rate Long-term Bad rate
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© 2014 Fair Isaac Corporation. Confidential. ► Explore each risk segment based on long term performance ► Note different sort order of variables when examining short term performance Exploring Opportunities to Segment by Long-Term Performance 15
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© 2014 Fair Isaac Corporation. Confidential. ► For segment 1, what’s most important is how long since the account was more seriously delinquent ► Accounts have a much different long-term bad rate, even thought the short term bad rate is similar Learning as We Segment 16
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© 2014 Fair Isaac Corporation. Confidential. ► For segment 2, first split on presence of serious delinquency in last 12 months ► For those that are “clean”, most important variable is months since any delinquency ► For those that were previously seriously delinquent, most important variable is months since serious delinquency Continued Learning 17
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© 2014 Fair Isaac Corporation. Confidential. 18 ► The original strategy ranked accounts into 6 risk tiers based on their short-term roll rate risk ► Using the existing strategy as a starting point, FICO ® Analytic Modeler Decision Trees Professional was able to identify segments of higher and lower risk accounts within the risk tiers ► Based on these results a test was initiated to determine if earlier intervention could benefit accounts that were higher long-term risks Strategy Improvement Potential earlier intervention Potential lighter action 18
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© 2014 Fair Isaac Corporation. Confidential. 19 Is There an Opportunity to Improve Account Segmentation? Definitely! Roll rate60+ rate 19
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© 2014 Fair Isaac Corporation. Confidential. Phase II: Address Competing Priorities 20
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© 2014 Fair Isaac Corporation. Confidential. Develop a model that… ► Consistently rank-orders across portfolios ► Standardizes processes and definitions ► Uses simpler variables ► Is compliant ► Better predicts multiple outcomes Game Plan: Scorecard Development 21© 2014 Fair Isaac Corporation. Confidential.
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Introducing Multiple Outcome Optimization ► Model A represents the opportunistically best score because it combines model coefficients to achieve: ► One of many equivalent optimal performance models on the primary objective ► Highest possible performance on a competing objective without loss on the primary objective FICO ® Analytic Modeler Scorecard Professional Primary objective response surface Z 11 22 A Competing objective response surface 22
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© 2014 Fair Isaac Corporation. Confidential. Working in the cloud can lead to efficiency gains Key Findings During Scorecard Project New tools can improve multiple outcomes, especially on key segments Easily evaluate across segments and portfolios 23
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© 2014 Fair Isaac Corporation. Confidential. Segmentation Analysis ► Several schemes evaluated ► Needed to work quickly but justify results ► Multiple projects—parallel work ► 5 analysts, 7 potential segmentation schemes, 2 days to complete ► Published results and evaluated against baseline and competing schemes Example 24
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© 2014 Fair Isaac Corporation. Confidential. Segmentation Analysis ► The ROC chart demonstrates several dimensions of our analysis ► Comparison of three segmentation schemes ► Evaluation on secondary performance ► Focus on one sub-population of accounts Example 25
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© 2014 Fair Isaac Corporation. Confidential. Multiple Objectives ► Focus on short-term and long-term performance ► Helped in segmentation decision ► Vital role in variable selection Example 26
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© 2014 Fair Isaac Corporation. Confidential. Multiple Objectives ► Ability to optimize via the dual objective function helped develop a model that met two of our top priorities Example Population 3 Short-Term PerformancePopulation 3 Long-Term Performance 27
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© 2014 Fair Isaac Corporation. Confidential. Conclusion ► Achieved goals of simpler models without giving up performance across portfolios and segments of interest ► Improved performance on key segments ► Improved long-term performance while maintaining short term performance ► Cloud-based tools lead to efficient workflows and standardization across the organization 28
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© 2014 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. Thank You! Nathan Pelzer nathanpelzer@wellsfargo.com 515-213-5668 Lamar Shahbazian Lshahbazian@fico.com 415-446-6321
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© 2014 Fair Isaac Corporation. Confidential. Learn More at FICO World Related Sessions ► Product Showcase: Analytic Modeling in the Cloud Products in Solution Center ► FICO ® Analytic Modeler Decision Trees Professional Experts at FICO World ► Lamar Shahbazian ► Jeff Dandridge Blogs ► www.fico.com/blog 30
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© 2014 Fair Isaac Corporation. Confidential. Please rate this session online! 31 Nathan Pelzer nathanpelzer@wellsfargo.com Lamar Shahbazian Lshahbazian@fico.com
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