Quiterian advanced analytics solution for banking

1. www.quiterian.com | 2011, April

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