Question
    • We’re looking to find customers’ usage patterns of banking methods 
    over the course of a three month study period. Using 100,000 case 
    examples. We’re wanting to find out which banking method is being 
    used and which ones aren’t. Using that information we want to make 
    the customers’ banking experience easier and more convenient.
                    Background
      • 100,000 active customers were study.
      • The dataset has six attributes. Which one, ID, being a special attribute used to identify the 
       customers.
   Attribute Name      Model Role         Measurement Level             Description             Examples
   ID                  ID                 Nominal                       Customer ID
   CNT_TBM             Input              Interval                      Traditional bank    In-bank services; 
                                                                        method transaction  deposit and 
                                                                        count               withdraws. Building 
                                                                                            a relationship
   CNT_ATM             Input              Interval                      ATM transaction     ATMs
                                                                        count
   CNT_POS             Input              Interval                      Point-of-sale       MoneyGram, 
                                                                        transaction count   Western Union
   CNT_CSC             Input              Interval                      Customer service    Tellers, personal 
                                                                        transaction count   bankers, financial 
                                                                                            advisors
   CNT_TOT             Input              Interval                      Total transaction 
                                                                        count
          Data Mining Approach
    SAS Segmentation Approach
                     • Using RapidMiner and SAS, we 
                      ran different filters to attempt to 
                      find any patterns or 
                      commonalities within the 
                      dataset.
         RapidMiner Segmentation
    Model             Results
                      • Cluster 0; traditional method the  most 
                       similarities.
                      • Clust 1-4 follower in order from greatest 
                       to least.
                      • Most banking methods used
                      1. Traditional
                      2. ATM
                      3. Point-of-sale
                      4. Customer service