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How analytics will transform banking in luxembourg

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Tommy Lehnert
Tommy Lehnert

This document discusses how analytics will transform banking in Luxembourg. It notes that data is now digital and ubiquitous, creating opportunities for insights through big data analytics. The analytics life cycle is described, from problem identification to model deployment and evaluation. Different levels of analytics usage and culture in organizations are outlined. The document advocates for a hybrid approach to analytics using automated rules, anomaly detection, predictive modeling and other techniques. A case study describes how a bank used analytics for improved risk management, customer insights, and executive decision making. The conclusion is that Luxembourg can become a leader in analytics adoption to transform outdated business models.

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How Analytics will transform Banking in Luxembourg TOMMY LEHNERT
How analytics will transform banking in luxembourg
Client behavior • Previously • Today
PERSPECTIVE Data is EVERYWHERE Data was digital 1986 6% Data is digital Today 99%
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 2015 8 ZETTABYTES
VOLUME VELOCITY VARIETY TODAY THE FUTURE DATASIZE THRIVING IN THE BIG DATA ERA VARIABILITY COMPLEXITY
Big Data STEPSTO CONQUER COMPLEXITY TURNCHALLENGE 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 MAXIMUMVALUE FROMYOUR DATA • Advanced Analytics + • PowerfulVisualizations + • Sharing • High Speed Performance + • Cost Efficient Scalability Source: Economist Intelligence Unit 2011 Report, 2011 Source: Lavastorm Report, 2015 - IBM Report, 2014
Trusted, analytical-based decisions are needed across the organization IMPACT SPANSTHE ENTIRE ORGANIZATION
WHY SHOULDYOU CARE? YOUR COMPETITIVE ADVANTAGE Orient Observe Act Act Orient Decide MARKET 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 ANALYTICSADOPTION
Analytics Culture • Analytically new Level 1 • Analytically Aware Level 2 • Analytically Informed Level 3 • Analytically Driven Level 4 • Analytically 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 transformational analytical plans. ANALYTICS USAGE Varying Levels ofAnalytics Use and Expertise
IDENTIFY / FORMULATE PROBLEM DATA PREPARATION DATA EXPLORATION TRANSFORM & SELECT BUILD MODEL VALIDATE MODEL DEPLOY MODEL EVALUATE / MONITOR RESULTS Domain Expert Makes Decisions Evaluates Processes and ROI BUSINESS MANAGER Model Validation Model Deployment Model Monitoring Data Preparation IT SYSTEMS / MANAGEMENT Data Exploration Data Visualization Report Creation BUSINESS ANALYST Exploratory Analysis Descriptive Segmentation Predictive Modeling DATA MINER / STATISTICIAN How can you create strategic advantage ? THE ANALYTICS LIFECYCLE
Hybrid approach to analytics Automated Business Rules Anomaly Detection Predictive Modeling Text Mining Entity Matching Network Generation Generation Process
Yesterday’s methods are insufficient to address tomorrow’s challenges Resources & Expert Knowledge Technology & Advanced Analytics It takes more than…
ANALYST VS. 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% accurate
Innovative Strategies 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
Copyright © 2012, SAS Institute Inc. All rights reserv ed. 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
Thank you tommy.lehnert@sas.com How Analytics will transform Banking in Luxembourg T O M M Y L E H N E R T

More Related Content

How analytics will transform banking in luxembourg

  • 1. How Analytics will transform Banking in Luxembourg TOMMY LEHNERT
  • 4. PERSPECTIVE Data is EVERYWHERE Data was digital 1986 6% Data is digital Today 99%
  • 5. PERSPECTIVE Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information? T.S. Eliot
  • 6. Source: IDC Digital Universe Study, sponsored by EMC, May 2010 Evolution 2015 8 ZETTABYTES
  • 7. VOLUME VELOCITY VARIETY TODAY THE FUTURE DATASIZE THRIVING IN THE BIG DATA ERA VARIABILITY COMPLEXITY
  • 8. Big Data STEPSTO CONQUER COMPLEXITY TURNCHALLENGE 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 MAXIMUMVALUE FROMYOUR DATA • Advanced Analytics + • PowerfulVisualizations + • Sharing • High Speed Performance + • Cost Efficient Scalability Source: Economist Intelligence Unit 2011 Report, 2011 Source: Lavastorm Report, 2015 - IBM Report, 2014
  • 9. Trusted, analytical-based decisions are needed across the organization IMPACT SPANSTHE ENTIRE ORGANIZATION
  • 11. Source: The Current State of Business Analytics: Where Do We Go From Here? Prepared by Bloomberg Businessweek Research Services, 2011 EXTERNAL VIEWPOINT CHALLENGES IN ANALYTICSADOPTION
  • 12. Analytics Culture • Analytically new Level 1 • Analytically Aware Level 2 • Analytically Informed Level 3 • Analytically Driven Level 4 • Analytically Innovative Level 5
  • 13. 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 transformational analytical plans. ANALYTICS USAGE Varying Levels ofAnalytics Use and Expertise
  • 14. IDENTIFY / FORMULATE PROBLEM DATA PREPARATION DATA EXPLORATION TRANSFORM & SELECT BUILD MODEL VALIDATE MODEL DEPLOY MODEL EVALUATE / MONITOR RESULTS Domain Expert Makes Decisions Evaluates Processes and ROI BUSINESS MANAGER Model Validation Model Deployment Model Monitoring Data Preparation IT SYSTEMS / MANAGEMENT Data Exploration Data Visualization Report Creation BUSINESS ANALYST Exploratory Analysis Descriptive Segmentation Predictive Modeling DATA MINER / STATISTICIAN How can you create strategic advantage ? THE ANALYTICS LIFECYCLE
  • 15. Hybrid approach to analytics Automated Business Rules Anomaly Detection Predictive Modeling Text Mining Entity Matching Network Generation Generation Process
  • 16. Yesterday’s methods are insufficient to address tomorrow’s challenges Resources & Expert Knowledge Technology & Advanced Analytics It takes more than…
  • 17. ANALYST VS. 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% accurate
  • 18. Innovative Strategies 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
  • 19. Copyright © 2012, SAS Institute Inc. All rights reserv ed. 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
  • 20. 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.
  • 21. “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
  • 22. Thank you tommy.lehnert@sas.com How Analytics will transform Banking in Luxembourg T O M M Y L E H N E R T