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www.quiterian.com |   2011, April
Introduction

   Meeting todays informational needs and anticipating the future 
   ones of the organization, shows not only a great strategic 
   vision, but the realization that Information is a valuable asset to 
   financial institutions in their mission to ensure and increase 
   their present value (especially true for Banks).




   Carlos Alvarez, Quiterian’s FS specialist




                          © Quiterian 2011. All rights reserved
Background
Current situation and main challenges

• Crisis has prompted many Banks and Savings Banks in Spain 
  to offer real estates and assets(apartments, houses, 
  garages) at interesting prices, discounts or favorable credit 
  terms.
• These assets, from mortgage defaults by their customers or 
  real estate companies, are a burden on entities that look at 
  how these risky assets affect their market value and ratings.
• At present, Banks and Savings Banks must meet the new 
  capitalization requirements issued by the Bank of Spain.
• The capital requirements of some Savings Banks and Banks 
  to meet the new solvency requirements have increased, 
  and these assets bring to entities greater difficulties to 
  reach them.

                       © Quiterian 2011. All rights reserved
The Role for Advanced Analytics
• To succeed in selling the properties on the market, Banks and 
  Savings Banks need to know which customers to target for running 
  promotional and marketing campaigns.
• Have a buyer profile of customer who have bought in the past, 
  helps companies to know which of their current 
  customers/prospects meet this profile, being able to perform 
  actions in order to do cloned sales.
• Knowing how are their potential buyers (and how not) allows 
  organizations to react quickly and better target their sales activities 
  with greater efficiency and effectiveness.
• Advanced Analytics and predictive analysis facilitate immediate 
  action and intervention in data processing and exploitation of key 
  information for Business Productivity and Business Development.



                           © Quiterian 2011. All rights reserved
Self‐service and Agile BI: DDWeb
 Financial Institutions: Banking Industry
 Maximum value and rigor for Data

 DDWeb lets Financial Institutions advance their knowledge of customers,
 quickly from the collection of data, easy navigation and detailed analysis. The
 validation of data for official reporting is easier and can generate valuable
 information.
                                   Banking Solutions
                                        Customer growth and retention
                                        Campaign management
                                        Cross/Up‐selling strategies
                                        Fraud prevention
                                        Data Quality improvement
                                        Advanced Web Analytics
                              © Quiterian 2011. All rights reserved
Self‐service and Agile BI: DDWeb
 Financial Institutions: Banking Industry
 Advanced Analytics and Predictive Analysis Benefits

  Customer knowledge: their 
  behavior, trends and profiles.

  Valuable information for business 
  development: customer churn 
  prediction, cross‐selling 
  opportunities, best products to                     RSelections and segmentation of 
  recommend.                                          customers and prospects instantly.

  Detect anomalies, early warning of 
                                                      React just in time with the most 
  risk of fraud.
                                                      effective decisions, anticipating events.
  360º Analytical view about 
  customer information, products                      Provides a long term forecast and 
  and services.                                       detects customer value loosing soon.

                                   © Quiterian 2011. All rights reserved
Selling real state assets
6 Steps to build a successful strategy using Quiterian DDWeb

1.   Identify from customer base the right segment (based on business rules) to include them as the 
     target of the campaign. We will do this using a Venn Diagram to select customers who meet 
     these criteria.
2.   Determine profiles or behavioral features of customers who have bought properties before 
     through the technique Profile.
3.   Puts advanced analysis techniques into practice with the aim of identifying the relevant variables 
     that best describe the buyers and which don’t – Profiling can help on this topic.
     It tells us how the customers forming this group are and how they are not, what is typical from 
     them, what makes them different, in which geographical areas it is more likely to find them,... 
4.   Easily and quickly, we apply the target segment by dragging it to the predictive technique of 
     Decision Tree, that will predict within few seconds which other customers will behave the same 
     way or will show “buyer pattern”. 
5.   Once the process of managing potencial buyers is over, iWorkflow makes it possible to automate 
     this flow in order to put the learnt experience into practice. Create a business rule that would 
     make the same calculation but systematically, with the regularity we decide to establish.  
6.   Finally Campaign Workflow lets us plan and start groups of equal or different actions on each one 
     of the different groups of potential customers. 



                                     © Quiterian 2011. All rights reserved
THANKS
                                    www.quiterian.com
  Advanced Analytics for
  Key Success Factors on

    Banking Industry




                                                            Carlos Álvarez
                                                              Account Manager
                                                             (+34) 662 64 71 41
                                                        calvarez@quiterian.com


www.quiterian.com |   2011, April

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Quiterian Ksf on advanced analytics for banking april 2011 eng

  • 2. Introduction Meeting todays informational needs and anticipating the future  ones of the organization, shows not only a great strategic  vision, but the realization that Information is a valuable asset to  financial institutions in their mission to ensure and increase  their present value (especially true for Banks). Carlos Alvarez, Quiterian’s FS specialist © Quiterian 2011. All rights reserved
  • 3. Background Current situation and main challenges • Crisis has prompted many Banks and Savings Banks in Spain  to offer real estates and assets(apartments, houses,  garages) at interesting prices, discounts or favorable credit  terms. • These assets, from mortgage defaults by their customers or  real estate companies, are a burden on entities that look at  how these risky assets affect their market value and ratings. • At present, Banks and Savings Banks must meet the new  capitalization requirements issued by the Bank of Spain. • The capital requirements of some Savings Banks and Banks  to meet the new solvency requirements have increased,  and these assets bring to entities greater difficulties to  reach them. © Quiterian 2011. All rights reserved
  • 4. The Role for Advanced Analytics • To succeed in selling the properties on the market, Banks and  Savings Banks need to know which customers to target for running  promotional and marketing campaigns. • Have a buyer profile of customer who have bought in the past,  helps companies to know which of their current  customers/prospects meet this profile, being able to perform  actions in order to do cloned sales. • Knowing how are their potential buyers (and how not) allows  organizations to react quickly and better target their sales activities  with greater efficiency and effectiveness. • Advanced Analytics and predictive analysis facilitate immediate  action and intervention in data processing and exploitation of key  information for Business Productivity and Business Development. © Quiterian 2011. All rights reserved
  • 5. Self‐service and Agile BI: DDWeb Financial Institutions: Banking Industry Maximum value and rigor for Data DDWeb lets Financial Institutions advance their knowledge of customers, quickly from the collection of data, easy navigation and detailed analysis. The validation of data for official reporting is easier and can generate valuable information. Banking Solutions Customer growth and retention Campaign management Cross/Up‐selling strategies Fraud prevention Data Quality improvement Advanced Web Analytics © Quiterian 2011. All rights reserved
  • 6. Self‐service and Agile BI: DDWeb Financial Institutions: Banking Industry Advanced Analytics and Predictive Analysis Benefits Customer knowledge: their  behavior, trends and profiles. Valuable information for business  development: customer churn  prediction, cross‐selling  opportunities, best products to  RSelections and segmentation of  recommend. customers and prospects instantly. Detect anomalies, early warning of  React just in time with the most  risk of fraud. effective decisions, anticipating events. 360º Analytical view about  customer information, products  Provides a long term forecast and  and services. detects customer value loosing soon. © Quiterian 2011. All rights reserved
  • 7. Selling real state assets 6 Steps to build a successful strategy using Quiterian DDWeb 1. Identify from customer base the right segment (based on business rules) to include them as the  target of the campaign. We will do this using a Venn Diagram to select customers who meet  these criteria. 2. Determine profiles or behavioral features of customers who have bought properties before  through the technique Profile. 3. Puts advanced analysis techniques into practice with the aim of identifying the relevant variables  that best describe the buyers and which don’t – Profiling can help on this topic. It tells us how the customers forming this group are and how they are not, what is typical from  them, what makes them different, in which geographical areas it is more likely to find them,...  4. Easily and quickly, we apply the target segment by dragging it to the predictive technique of  Decision Tree, that will predict within few seconds which other customers will behave the same  way or will show “buyer pattern”.  5. Once the process of managing potencial buyers is over, iWorkflow makes it possible to automate  this flow in order to put the learnt experience into practice. Create a business rule that would  make the same calculation but systematically, with the regularity we decide to establish.   6. Finally Campaign Workflow lets us plan and start groups of equal or different actions on each one  of the different groups of potential customers.  © Quiterian 2011. All rights reserved
  • 8. THANKS www.quiterian.com Advanced Analytics for Key Success Factors on Banking Industry Carlos Álvarez Account Manager (+34) 662 64 71 41 calvarez@quiterian.com www.quiterian.com |   2011, April