Download Data mining in the banking and insurance industry

NorSistemas
MARKETING SYSTEMS:
DATA MINING IN BANKING AND INSURANCE
SEUGI 15 Madrid
May, 1997
Several forces are shaping a new competitive environment ...
FORCES FOR CHANGE IN BANKING AND INSURANCE
y Deregulation and opening to new competitors
y Globalization of markets
y Shrinkage of margins
MARKET
REGULATION
CUSTOMER
S
y Increasing demands and financial
culture
COMPETITOR
S
TECHNOLOGY
y Different tipologies
y Increasing competition among
traditional competitors
y Appearance of new competitors
y Influence in the competitive environment
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MARKETING SYSTEMS
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… where new key strategic factors are becoming important
KEY STRATEGIC FACTORS: MARKETING
FINANCE
MARKETING
Products
y Personalized products in response to the real needs of customers.
y Increasing demands for additional services.
y Segmentation of products.
Prices
y Personalized and competitive prices.
y Discount policy.
y Segmentation of prices.
HUMAN
Distribution
y New channels for distribution and commercialization.
y Specialization in commercial activities.
y Segmentation of channels.
RESOURCE
S
OPERATIONS
Promotion
y Effectiveness in commercial promotion.
y Personalization of promotional activities.
Customer Service
y Closeness to the customer.
y Quality of service.
y Customer loyalty.
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MARKETING SYSTEMS
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The analysis of customer-related information is the answer to these business needs
MARKETING SYSTEMS
Products
Commercialization
MARKETING
SYSTEM
Prices
Customer service and
promotion
ƒ Customer-related information provides competitive advantage.
ƒ In all the industries, companies are gathering, storing and analyzing customer-related information for
decission making in Marketing.
ƒ Technology makes possible Marketing Systems:
y Collection and management of large volumen of data (Data Warehousing Technologies).
y Data analysis (Data Mining Techniques).
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MARKETING SYSTEMS
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Data Warehousing solutions enable the management of large volume of data
DATA WAREHOUSE ADMINISTRATION
Internal DB
EXTRACTION
TRANSFORMATION
LOADING
DATA
WAREHOUSE
EXPLOITATION
External DB
ƒ Data Warehouse management
y Extracting data (access to internal and external sources of data).
y Transforming data (integration, screening, summarization, etc.).
y Warehouse loading (update of warehouse data).
ƒ Data Warehouse exploitation
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MARKETING SYSTEMS
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Data Mining techniques make possible to model relationships in customer-related data
DATA WAREHOUSE EXPLOTATION
Internal DB
EXTRACTION
TRANSFORMATION
LOADING
DATA
WAREHOUSE
EXPLOITATION
External DB
ƒ Explotation: analysis of the information in the Data Warehouse.
ƒ Three different methods exist:
y Q&R: access, manipulation and report generation.
y OLAP: it answers business questions but it isn’t possible to reach conclusions about
relationships and trends in data.
y DATA MINING: advanced methods to modelling relationships in data with a determined
business purpose.
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MARKETING SYSTEMS
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These techniques are giving support to Marketing processes ...
MARKETING PROCESSES
Marketing Research
(Data Mining)
Marketing DB
(Data Warehouse)
Commercial activities
Control
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Execution
Planning
MARKETING SYSTEMS
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These techiques are giving support to Marketing processes ...
MARKETING PROCESSES
Marketing Research
(Data Mining)
Marketing DB
(Data Warehouse)
Commercial activities
Control
Execution
Planning
ƒ Marketing Research
y Customer analysis (market segmentation, market research, customer attrition analysis, prospect
analysis, bad debt, customer potential, …).
y Product analysis (portfolio analysis, complementary and substitutive products, definition of new
products, demand forecasting, etc.).
y Price analysis (policy of prices and discounts, pricing simulation, etc.).
y Distribution channels (distribution policy, coordination of channels, etc.).
y Customer service and promotion (analysis and simulation of promotional campaings, new products
launching, cross-selling, loyalty programs, quality of service, etc.).
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MARKETING SYSTEMS
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These techiques are giving support to Marketing processes ...
MARKETING PROCESSES
Marketing Research
(Data Mining)
Marketing DB
(Data Warehouse)
Commercial activities
Control
Execution
Planning
y Commercial activities
y Scheduling, execution and follow-up of promotional campaigns.
y Management of alarms and customer status indicators.
y Commercial diary.
y Support to distribution channels with qualified information.
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MARKETING SYSTEMS
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… implemented in Marketing systems that support Marketing research and commercial activities
FUNCTIONAL SCOPE OF A MARKETING SYSTEM
Contact Mgmt.
Market
research
Customer
analysis
Product
analysis
Price
analysis
Distribution
channels
Commercial
promotion
Promotional
Campaigns
Modelling and simulation
Alarm
Mgmt
Commercial
Diary
Workflow
Query administrator
Marketing
DB
Extraction, transformation and loading
Other internal
DB
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Trasaccional
DB
External
DB
MARKETING SYSTEMS
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Some key aspects must be considered when undertaking Marketing system projects
KEY ASPECTS IN MARKETING SYSTEM PROJECTS
ƒ Marketing Data Base different from Transactional Data Base.
y In order not to interfere the day-to-day business activity.
y With all the information required by the Marketing Department.
y With advanced capabilities for query and data analysis.
ƒ Design of the system as a set of analysis tools.
y Marketing activities cannot be completely automated; user analysis and decissions are
always required.
y System design not process-oriented.
y Open set of tools used with some business-purpose.
ƒ Undertake the project with an iterative development approach.
y Starting with basic functionality and seeking results in the short-term.
y Adding progressively new functions in later development phases.
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MARKETING SYSTEMS
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CASE STUDY: CUSTOMER ATTRITION ANALYSIS IN BANKING
ƒ Analysis of former-customers to:
y Identify the profiles of those clients who have already abandoned.
y Identify customers with tendency to abandonment in order to conduct retention and
loyalty programs.
y Conduct programs for recovery of former-customers.
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MARKETING SYSTEMS
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METODOLOGY FOR THE ANALYSIS
c
d
e
f
g
c
Identification of former-customer population.
d
Extraction of meaningful random samples.
e
Sample exploration.
f
Inferential statistical analysis (modelling).
g
Extension of conclusions and results to the whole population.
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MARKETING SYSTEMS
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c
d
e
f
g
EXTRACTING DE SAMPLE
ƒ Two samples are extracted:
– Sample 1: Current customers. A size of 100.000 customers is considered meaningful
enough. A flag ‘1’ is added to each of this records.
– Sample 2: Former-customers. Similar size is considered. A flag ‘0’ is added to these
records.
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MARKETING SYSTEMS
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c
d
e
f
g
EXPLORING THE SAMPLE
ƒ The exploration techniques are different depending on the variable type:
– Tables (simple, crosstabulation, nested, etc.).
– Graphics.
– Histograms or bar charts, multidimensional representations.
– Tuckey´s box plots.
– Etc.
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MARKETING SYSTEMS
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c
d
e
f
g
INFERENTIAL STATISTICAL ANAYSIS (MODELLING)
ƒ Reduction of the number of variables:
– Depending on the variable type, different methods are used to reduce the number of
variables:
y Nominal and discrete numeric variables: The chi-squared test is used to
determine which variables have the strongest influence on the response variable.
y Continuous numeric variable: Linear regression is used to study which variables
explain better the response variable.
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MARKETING SYSTEMS
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c
d
e
f
g
INFERENTIAL STATISTICAL ANAYSIS (MODELLING)
ƒ Building the model
– Once the set of variables has been reduced, the next step is to build a model for the
response variable.
– In this case, a CHAID (CHi-squared Automatic Interaction Detector) model is
applied.
– Discriminant analysis is applied to each of the groups that resulted from the Chaid
analysis.
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MARKETING SYSTEMS
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c
d
e
f
g
EXTENDING THE CONCLUSIONS TO THE WHOLE POPULATION
ƒ Two different profiles of customers who abandon have been identified:
– Young people with high income and few products (usually an operating
account and another more) with high balances in deposits and large volume of
movements in account.
– Middle-class people with middle income, low balances in deposits and middle
number of movements in account.
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MARKETING SYSTEMS
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