How analytics will transform banking in luxembourg
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How Analytics will transform Banking in Luxembourg TOMMY LEHNERT
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Transcript of How analytics will transform banking in luxembourg
How Analytics will transform Banking in Luxembourg
TOMMY LEHNERT
•Disruptive Client behavior
•Data will become Big Data
•Big Data will become Analytical Data
•Analytics Culture
•Resources, Talents
•Technology
Client behavior
• Previously • Today
PERSPECTIVE Data is EVERYWHERE
Data was digital19866%
Data is digitalToday99%
PERSPECTIVE
Where is the wisdom we have lost in knowledge?Where is the knowledge we have lost in information?T.S. Eliot
Source: IDC Digital Universe Study, sponsored by EMC, May 2010
Evolution
20158
ZETTABYTES
VOLUME
VELOCITY
VARIETY
TODAY THE FUTURE
DA
TA
SIZ
ETHRIVING IN THE BIG DATA ERA
VARIABILITYCOMPLEXITY
Big Data STEPS TO CONQUER
COMPLEXITY
TURN CHALLENGE INTO OPPORTUNITY
• 36% annual increase in business data
• 93% believe in revenue increase
• 97% significant changes over the next 2 years in leveraging data
GAIN MAXIMUM VALUE FROM YOUR DATA
• Advanced Analytics +
• Powerful Visualizations +
• Sharing
• High Speed Performance +
• Cost Efficient ScalabilitySource: Economist Intelligence Unit 2011 Report, 2011
Source: Lavastorm Report, 2015 - IBM Report, 2014
Trusted, analytical-based decisions are needed across the organization
IMPACT SPANS THE ENTIRE
ORGANIZATION
WHY SHOULD YOU CARE?
YOURCOMPETITIVEADVANTAGE
Orient
Observe
Act
Act
Orient
DecideMARKET
OPPORTUNITY
Decide
Source: The Current State of Business Analytics: Where Do We Go From Here?Prepared by Bloomberg Businessweek Research Services, 2011
EXTERNAL VIEWPOINT CHALLENGES IN ANALYTICS ADOPTION
Analytics Culture
• Analytically new
Level 1
• Analytically Aware
Level 2 • Analytica
lly InformedLevel
3
• Analytically Driven
Level 4 • Analytica
lly Innovative Level
5
ANALYTICALLY
NEW
ANALYTICALLY AWARE
ANALYTICALLY INFORMED
ANALYTICALLY
DRIVEN
ANALYTICALLY
INNOVATIVE
LEVEL 1
LEVEL 2
LEVEL 3
LEVEL 4
LEVEL 5
Isolated analytics use.
Basic tools and limited or
no best practices
Predictive analytics usage
is part of mission critical
applications only.
Full benefits are not understood by a majority in
the organization.
Analytics usage consists
primarily of tactical and ad
hoc approaches.
Analytics dev. and
deployment is constrained,
yet departments
have their own experts and/or
initiatives.
Analytics talent is centralized
into larger groups.
Management understands
and supports analytics for
strategic value, thus bringing
business units into alignment
Company is committed to
analytics as part of its
future growth plan.
Business units embrace their
own transformation
al analytical plans.
ANALYTICS USAGE
Varying Levels of Analytics Use and Expertise
IDENTIFY /FORMULATE
PROBLEM
DATAPREPARATION
DATAEXPLORATION
TRANSFORM& SELECT
BUILDMODEL
VALIDATEMODEL
DEPLOYMODEL
EVALUATE /MONITORRESULTS
Domain ExpertMakes DecisionsEvaluates Processes and ROI
BUSINESSMANAGER
Model ValidationModel DeploymentModel Monitoring Data Preparation
IT SYSTEMS /MANAGEMENT
Data ExplorationData VisualizationReport Creation
BUSINESSANALYST
Exploratory AnalysisDescriptive SegmentationPredictive Modeling
DATA MINER /STATISTICIAN
How can you
create strategi
c advanta
ge?
THE ANALYTICS LIFECYCLE
Hybrid approach to analytics
Automated Business Rules
Anomaly Detection
Predictive Modeling
Text Mining
Entity Matching
Network Generatio
n
Generation Process
Yesterday’s methods are insufficient to address tomorrow’s challenges
Resources & Expert Knowledge
Technology & Advanced Analytics
It takes more than…
ANALYSTVS. PREDICTIVE MODEL
Indicator
Age
Gender
Marital Status
Indicator Weight
Age 13%
Gender 18%
Language 14%
Marital status 17%
Monetary inflow 22%
Postal Code 2%
Education Level 3%
Client relationship age 2%
99% accura
te
InnovativeStrategies for
Data Analytics
• A flexible enterprise architecture that supports many data types and usage patterns
• Upstream use of analytics to optimize data relevance
• Real-time visualization and advanced analytics to accelerate understanding and action
• Common analytical framework across the enterprise
Copy r igh t © 2012 , SAS Ins t i t u t e I nc . A l l r i gh t s res erved .
Cosmos Bank BANKING
BUSINESS ISSUE
• Provide access to risk, customer information and analytic results to all affiliates, business units
• Give executives access to big data insights to make more informed decisions
• Improve costly, timely process to produce monthly/quarterly reports due to many different data sources resulting in inconsistent data
SOLUTION
• Analytics
RESULTS
A solution with instant access to large stores of information and data analysis that is fast, smart and mobile, resulting in:
• A more accurate view of customer behavior
• Real-time insights for risk management, customer development, product marketing and finance
• Integrated corporate and consumer data
• User generation and sharing of reports, dashboards and visualizations
“This is an era of visualization. We provide ranking officers and board members with eye-catching tables and charts, so they can quickly grasp the data's meaning and make informed decisions. If they want more details, they have immediate access to relevant tables or charts.”
James Lin
Chief Risk Officer
CONCLUSION Final Thoughts
Big Data and Analytics affect people and businesses everywhere.
Era of Analytics has begun and represents the opportunity to transform obsolete business models.
Invest in people and technology. Especially in Luxembourg, we can be
capable of becoming an example in analytics adoption.
“The Greatest Value Of A Picture
Is When It Forces Us To Notice
What We Never Expected To See.”John W. Tukey, Exploratory Data Analysis 1977
