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Quiterian Ksf on advanced analytics for banking april 2011 eng
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
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