My presentation about Using Behavioral Finance Techniques at Yapı Kredi Bank at EFMA Customer Week, April'2013 at Paris

1. EFMA Customer Week
23-25 April’13,Paris
Ahmet Vefa Erdem
Yapı Kredi

2. Agenda
• About Yapı Kredi
• CRM Architecture of Yapı Kredi
• Behavioral Finance Application: Golden Offer
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3. About Yapı Kredi
 Established in 1944, first retail focused private bank of Turkey
#4 largest private bank with;
 928 branches
2,825 ATMs
17,000 employees
Large customer base ( 6,4 M )
#1:Largest credit card base with 8M cards
(%19 #of merchandisers, %13,6 #of card holders )
2,3M internet banking users
# 1 : Largest mobile banking users ( %15 market share )
# 1 : Factoring (%14,3 market share )
# 1 : Leasing ( %17,2 market share )
Subsidaries : Netherlands, Russia, Azerbaican
Strong stakeholders : Koç Holding and UniCredit
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4. Yapı Kredi is an IT Pioneer in Banking Sector
The first ISO
9001 Quality
Certifed Bank in
Turkish Banking
Sector
The first provider of
Credit Cards and
Consumer Loans
The first computer user
in Turkish Banking
Sector
1967
1984
The biggest IT
migration in Turkey
with YapıKredi and
Kocbank
The first bank which
provides special ATMs to
disabled customer
1988
1991
1995
2002
2006
2007
2010
2010
Mobile Banking Applications at top 5
The first implementer of
online inter – branch
application
The first Phone Banking
The first Mobile
restructured
Application and Credit
POS Application in
“World Credit
Card loyalty system
Turkey
Card” program
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mobile platforms

5. Agenda
• About Yapı Kredi
• CRM Architecture of Yapı Kredi
• Behavioral Finance Application: Golden Offer
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6. Continous Improvement of BI & CRM at YapıKredi
GO!
Campaign
Real Time
Decision
V a lu e / B e h a v io r S e g m e n tie r u n g
MultiChannel
Managem
ent
Project
2010
2011
B10
B9
B8
B7
B6
B5
B4
B3
B2
B1
V1
V2
V3
V4
V5
V6
V7
V8
V9
V10
Web
Reporting
DWH
Campaign
Managme
nt
Subsegme
ntation,
new data
mining
models
2005
2007
Customer
&
Portflolio
Managme
nt Tool
Reporting
Center for
Branches
Golden
Offer
( BO 4.0
web,
4,500
users)
(Mind
Book)
Data
Mining,
Customer
Segmenta
tion
DWH
1991
2001
2002
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2009
2012
2012

7. Multi-Channel CRM
Source System
Deposit
Credit Card
CIF
Loans
MIS
Subsidaries
YK Pension
YK Assurance
YK Factoring
YK Leasing
Info Center
Responses
Pricing Strategies & Commissions & Service Model
Securities
Yapı Kredi Datawarehouse
LTV
Contact
Man.DM
CRM DM
Querying
Software
Contact
Management
Akıl Defteri
Datamining
Software
Credit Card
DM
Campaign
Man. DM
Campaign Management
Software (Chordiant)
Marketing
Optimization
Marketing
Optimization
Software (SAS)
Real Time
Decision
Real Time Decision
Marketing
(Chordiant)
Service Model
Que System
Sales/Service Points
Branch
Teller / RM
Call
Center
Contact Management
( Akıl Defteri)
Internet
Banking
ATM
IVR
IVN
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Web
Pages
POS
Direct
Mail
Statement
E-mail
SMS

8. Data Warehouse Architecture
Business Intelligence
Business
Objects
Operational
Systems
Internet
Banking
Core
Banking
ATM
Replication (GoldenGate)
Single Pyramid
Profitability
World rapor
Merchant
Reporting
CreditCard
Cartography
CreditCard
Branch
Reporting
Operations
Dashboard
(Opmis)
ODS
(operational data store)
And Other
Sources
- Treasury
CreditCard - Mobile Banking
- Call Center
- Branch IVRs
- External data
Oracle
Exadata
ETL
Enterprise
DataWarehouse
Profitability
DMart
CRM
DMart
Fraud
DMart
D.Mining
DMart
Credit Scoring
(SAS)
Marketing
Optimisation
(SAS)
Presentation
DataMarts
BILIVE
CAMPLIVE
Fraud
Management
Basel 2
(SAS)
Sybase IQ
ETL
Reporting
Center
Data Mining
(SAS)
Budgeting &
Planning
Data Warehouse
CreditCrd
DMart
Analytics
SQLServer
OLAP
Customer
Data Quality
(SAS)
Oracle Exadata
CRM
Campaign
Management
(Chordiant)
Potential
Customer
Management
Customer
Contact
Management
(Mind Book)
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Wealth
Management
(Navigation)
Portfolio
Management
Opportunity
Management
Cust.Visit
Management

9. Facts and Figures about Data Warehouse
Database
• Sybase IQ 15.2
Data Size of DW?
• 70 TB
# of table in DW?
• ~ 17,000 tables
Data Warehouse
# of source database?
# of database types
integrating with?
# of ETL jobs ?
# of daily running ETL jobs?
• 15+
• 6 ( Oracle, Exadata, SQL Server, MySQL,
Mainframe, SAS )
• ~15,000
• ~10,000
• Others monthly, weekly
# of query in a month?
ETL
• ~1,6M
Processing data size in a
day?
• ~3,5 TB
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10. CRM Strategy of Yapı Kredi
From simple product offerings
to customer oriented solutions
By tracking the life-cycle of the customer
Understanding customers’ behaviours and needs
Creating tailor-made customer-centric solutions
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11. Agenda
• About Yapı Kredi
• CRM Architecture of Yapı Kredi
• Behavioral Finance Application: Golden Offer
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12. About «Golden Offer - GO!»
•
•
•
Golder Offer «GO!» is a Yapı Kredi Private Banking application which is unique
analytical approach for Turkish banking sector with using «Behavioral Finance
Methods»
Yapı Kredi and Koç University cooperated to define algoritms of the project
Project was reinforced by Tubitak* because of its innovative approach
* The Scientific and Technological Research Council of Turkey
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13. What is Behavioral Finance?
•
•
The fields are primarily concerned
with the bounds of rationality of
economic agents.
•
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Behavioral finance studies the effects
of social, cognitive and emotional
factors on the economic decisions of
individuals and institutions and the
consequences for market prices,
returns and the resource allocation.
Behavioral models typically integrate
insights from psychology with neoclassical economic theory; in so doing,
these behavioral models cover a range
of concepts, methods, and fields

14. Why Behavioral Finance?
The newest analysis method since the crisis
of technology stocks in 2000
Implementation of the psychology about
financial behavior
While the classical finance theory assumes
people give logical and rational decisions, this
method accepts people are not always make
rational decisions.
We could help to our customers by
discovering their financial decision factors and
using these behavioral characteristics to
suggest best solutions according to their
preferences.
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15. Why GO! ?
 GO!
is a board game for two
players that originated in China
more than 2,500 years
 GO!
is a game using tactical,
strategy and observation
 GO!
Motivating, innovative
 GO!
requires for strong tactical play
and ability to read ahead.
 GO!
Golden Offer!
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16. «Golden Offer (GO!) » Project Objective
The project targets to differentiate in customer experience
of private banking with;
•
Offering appropriate products according to investment needs
and preferences of the customer with combining behavioral
finance and predictive models under the optimisation
techniques
•
Providing new investment opportunities
•
Giving information consulting in areas of personal interests
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17. «Golden Offer (GO!) » Project Objective
Yapı Kredi would like to achieve multiple objectives:
•
After the improvement of Turkish economy, time deposit
interest rates has begun to decrease, customers started to
look for ways to increase their returns. Moving customers
toward products that will provide higher expected returns
while keeping portfolio risk at acceptable levels is one of the
objectives
•
Introducing new products to the customer’s portfolio, thereby
increasing the depth of the relationship with Yapı Kredi, which
should improve customer retention and share of customer’s
investments with Yapı Kredi is also an objective
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18. Solution Steps
1. Customer and RM Survey to learn;
 Customer financial behaviour
 Customer loss aversion
 Customer obsessions
2. Generate Customer Scorecard by considering;
 Customer and RM Survey results
 Customer’s historical data
 Mining scores about customer : churn, share of wallet,
cross-sell, CLTV
3. Make Optimization to create Golden Offer by using
 Customer scorecard results
 Customer portfolio
 Products info
 Parameters
4. Make simulation & what-if analysis to customer ;
 To show different offer benefits by using different product
combinations
5. Give Golden Offer to customer
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19. Basic flow of Golden Offer process(partial)
1
Give
report to
customer
Customer
behavior
survey
RM
behavior
survey
Give
report to
RM
2
3
5
Optimisation
Customer
scorecard
Customer
Historical
Data
Predictive models:
Churn, CLTV, Xsell opportunities
Golden
offer
4
Parameters
Customer
Portfolio
Products
info
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Simulation
What-if
Analysis
GO!
Offer to
customer

20. 1.St Step : Customer’s Financial Behaviour Survey
Financial Behaviour Form includes 2 tabs;
1. Customer Financial Behaviour Form
2. RM Financial Behaviour Form
20
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21. 2.nd Step : Customer Scorecard
Inputs;
Customer scorecard report is generated by the system according
to;
• Survey result and RM Survey result
• Customer’s historical data
• Analytical scores like churn, CLTV and x-sell opportunities
about customer.
Consist of;
•
Measures of customers’ behaviors, attitudes and choices
concerning financial investments
Calculated based on;
•
•
Transactional and demographic data from company
databases, as well as a customer survey
The source databases contain customer demographic
information, portfolio holdings and transactions in the last
two years
Will be used for ;
•
To help formulate the Golden Offer for the individual Private
Banking Customer
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22. 2.nd Step : Customer Scorecard
Some of Scores from Customer
Scorecard
FX lover
Database
Survey
X
Deposit lover
X
Diversification
X
Transaction frequency
X
Liquidity lover / Cash lover
X
Risk attitude
X
X
Loss Aversion
X
Ambiguity aversion
X
To do after a loss / regret aversion etc.
X
Investment purposed
X
Financial products in other inst.
X
Etc……
•
•
The customer’s preferences for risk and return as well as for other characteristics of financial products are captured to
suggest a portfolio that suits the customer’s preferences better, increases the expected return for the tolerable risk
level while improving bank profitability
For example, if the customer displays a less risk averse attitude in the survey than indicated by the current portfolio,
the suggested portfolio can be allowed to be more risky, provided it satisfies the profitability goals for the customer
and Yapı Kredi
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23. 3.rd Step : Portfolio Optimization
Inputs to the optimization tool:
a) Product related inputs: Expected returns,
covariance matrix of the products.
b) Customer related inputs: Customer’s
current portfolio, Investment preferences and
attitudes based on the survey
c) Optimization requirements include
constraints on the optimization, such as
desired improvement in YKB profitability or
percent of portfolio that can be modified
Outputs of the optimization tool:
• The Golden Offer: product to be added and
the suggested weights of the products in the
new portfolio
• The expected value and the standard
deviation of the return for the current and
suggested portfolio
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24. 4.th Step : Simulation
Monte Carlo Simulation Method is used :
This methods are used in mathematical
finance to value and analyze (complex)
instruments, portfolios and investments by
simulating the various sources of uncertainty
affecting their value, and then determining
their average value over the range of
resultant outcomes
Objectives of the simulation tool:
• Customers see possible returns from a
portfolio
• Customers make comparisons between
various investment opportunities
• Customers better understand the
opportunities proposed by RMs
• RMs convince customers to switch to Yapı
Kredi products
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25. Some Feedbacks from Sales Channel
Advantages
Providing an investment alternative to the customer and create the possibility of
cross-selling
Confidence against the product presentation made by the system which is
developed by collaboration with university and reinforce of Tubitak
 Offering very appropriate customer based products
 Support knowing customer’s behavior better than themselves and customize
offers regarding to their preferences
Augmenting the customer’s portfolio to bring about a win-win situation for
customer and the bank and thus solidify the relationship
Giving advantage to customer to experience different scenarios via simulations
Creating innovative and prestigious image by using this distinctive technique
Challenges
Performance of the Golden Offer Optimisation process
Convincing customers to answer behavioral analysis survey
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26. Thank You !
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