Post on 25-Mar-2018
Copyright © 2002, SAS Institute Inc. All rights reserved.
Payment Behavior Analysis and Prediction Project at a Telco Company
Özge Neslihan ÇaycıSAS Turkey
Copyright © 2002, SAS Institute Inc. All rights reserved.
Agenda! Project Background
! About the company! Previous Marketing Department CRM project
! Finance Department Payment Behavior Analysis Project! Business Needs! Business Answers! Business Benefits! Project Architecture and Modelling techniques
! Questions
Copyright © 2002, SAS Institute Inc. All rights reserved.
About the company! The leading Mobile Operator in Turkey! About 10 million subscribers
Copyright © 2002, SAS Institute Inc. All rights reserved.
Marketing Department CRM initiated project
Copyright © 2002, SAS Institute Inc. All rights reserved.
Business needs (Marketing)! Customer Understanding
Discover who the customers are to gain a global market knowledge
! Segmentation and ProfilingSeparate the customers into homogeneous groups according
to the call behavior and service usage
! Churn PredictionPredict which customers will churn and determine the causes
Copyright © 2002, SAS Institute Inc. All rights reserved.
Business Answers (Marketing)! Customer Understanding
! Identification of major pains (fraud, suspension) ! Initiated a new project on the payment behavior
! Segmentation and Profiling study! Know their customers call behavior better! Started a new tariff which has received the most response ever
! Churn Prediction! Churners are not the most valuable customers! Able to run models for different targets
Copyright © 2002, SAS Institute Inc. All rights reserved.
Agenda! Project Background
! About the company! Previous Marketing Department CRM project
! Finance Department Payment Behavior Analysis Project! Business Needs! Business Answers! Business Benefits! Project Architecture and Modelling techniques
! Questions
Copyright © 2002, SAS Institute Inc. All rights reserved.
Score the customers for their payment risk
Apply different collection actions
Increase the rate of payment
Business Needs
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Project ScopeCustomer UnderstandingReaction to the current collection actions, realization of different payment behaviors
Project Scope
Segmentation and ProfilingSeparate the customers into homogeneous groups according to their payment behaviors for applying proper collection action sets
Non-payment PredictionPredict which customers will pay late and which customers will become suspended due to nonpayment
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Collection Process! Payment on due is very important for
• the cash flow planning• for the reduced risk!
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Customer Understanding! The percentage of the number of payments and
the amount of payments done are slightly different in terms of the time it takes to pay.• Higher invoices tend to be paid later...
! The payment of the customers are studied in terms of• Their reactions to the collection process• The way of payment they prefer• The past payment behavior
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Segmentation and Profiling! After the study of the variables for segmentation three
variables were selected: • past payment behavior• past payment amount• age of the contract
! Finance department grouped the segments into two groups as good and late payers and planned different collection actions for these groups
! The 7 segments are studied and grouped into 3 for the new collection actions as• Strict, Moderate, Tolerant
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Late Payment Prediction! Target Variables
• Paying after the due date• Being Suspended due to non-payment
! Model variables• past payment behavior• past invoice amount
Can easily predict the late payers checking the previous payment behavior
Copyright © 2002, SAS Institute Inc. All rights reserved.
Business BenefitsWith the differentiation of the collection actions an improvement of 10% has been achieved first month with the success of the collections.
The improvement has also significantly affected the success of the collections in the coming months which is sentenced as a great profit for the company.
The predictive models for non-payment and suspension are going to be used by the marketing department for the campaigns that will be generated.
Copyright © 2002, SAS Institute Inc. All rights reserved.
Project Challenges! Limited time for the project delivery
The operational system for the differentiation of the collection actions was in place and the finance department was waiting for the model results
! Human capitalAcquire analytical competence inside the finance department
! MethodologyGain knowledge on data warehousing and data mining
! EnvironmentEconomic crisis caused sudden changes in the payment behavior and the company objectives
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Project Organization! SAS Data Mining Methodology! Project Details
! SAS team (200 man days) Project Manager Özge Çaycı (SAS Turkey)Business Specialist Guillaume Leorat (SAS France)Warehouse Architect Timothee Robert (SAS France)
! Customer team (5 people involved, 200 man days)! Duration (5 months)
Copyright © 2002, SAS Institute Inc. All rights reserved.
EnterpriseDataWarehouse
DataWarehouse server
Project Architecture
DM
SelectControl
Agregate
Decision oriented server
ProductionDatabase
Reporting
Data Mining
ANALYTICS / VALUE ADDITIONS
External Data
MergeTransformTranspose
Payment Analysis
Reports on customerand analysis
Data sources
CustomerDatabase
Data CheckingData sources qualityimprovement
STORAGEEMTL
Copyright © 2002, SAS Institute Inc. All rights reserved.
Data Mining Modelling Techniques! SAS Enterprise Miner
!Segmentation and Profiling!Variable Selection!Clustering
!Predictive Modelling!Decision Trees!Regression!Assessment
Copyright © 2002, SAS Institute Inc. All rights reserved.
Conclusion! Implementing seperate segmentation models for Finance
and Marketing resulted with more accurate and useful customer groups
! The marketing call behavior segments and the finance payment behavior segments are merged for a company segmentation that will be used by the customer care and sales departments
! The marketing and the sales departments merged with a reorganization after the marketing segmentation project and divided into three departments as a marketing team serving each one of the three main customer groups
! Marketing Department is working on new data mining projects for identifying cross selling opportunities
Copyright © 2002, SAS Institute Inc. All rights reserved.
Upcoming Initiatives! Finance department is in need of a modelling
system that will serve their cash flow forecasting need and SAS ETS is being evaluated
! Fraud department is also evaluating Enterprise Miner for the tuning and the assessment of their Fraud Management System parameters
Management has put a lot of belief and hope into the data mining teams in the company...
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Questions ???