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Analytic Modeling in the Age of Cognitive Computing and “Big Data”
! Execu&ng)advanced)analy&c)capabili&es)
! Incorpora&ng)new)and)complex)data)sources))
! Capitalizing)on)today’s)big)data,)dynamic)technologies)and)advanced)analy&cs)
What are we talking about?
! We)are)right)at)the)beginning…)
! Best)prac&ces)are)not)established)
! No)one)has)fully)unlocked)the)poten&al)))
! No)one)is)fully)profi&ng)from)this)capability))
! We)want)to)find)new)ways)to)expand)business)and)profit)
Why are we talking about it?
Defining Trends:
So critical that they are redefining industry
Defining Trends
The Power of Open and Collaboration
)Gartner’s)Magic)Quadrant)for)Advanced)Analy&cs)PlaJorm)
Defining Trends
• Open)plaJorm)for)developers)
• 2)Million)user)community)
• Compe&ng)with)SAS))
Big Data Is About Much More Than Data...
*PWC 2013
Defining Trends
It represents a new way of doing business—one that is driven by data-based decision-making and new types of
products and services enriched with data.*
DATA)
ANALYTICS)TECHNOLOGY)
Robust)Technology)PlaJorms)) Advanced)Analy&cs)
Defining Trends
MongoDB)&)other)NoSQL)PlaJorms)
InUHadoop)Analy&cs)
Challenge:)agility,)volume,)velocity,)and)variety)of)data)
“Cognitive computing systems learn and interact naturally with people to extend what either humans or
machine could do on their own. They help human experts make better decisions by penetrating the
complexity of big data.” -IBM
Defining Trends
Cognitive Computing
Defining Trends
Organization: Additive Analytics Industry: Healthcare Application: Predicting hospital readmission; Using machine learning algorithms to identify which patients are at high risk of readmission Outcome: Improved Care outcomes and reduced costs.
Organization: Rebellion Research Industry: Finance Application: Investment decisions; Using machine learning based AI to manage investment portfolios.
Machine Learning Applications
What’s to become of analytical models in our real-time, machine learning age filled with new and
complex data sources?
Defining Trends
Opportunity: Derive significant value from a segment that has historically been excluded from the “eligible universe” for lending
Capitalize on today’s big data, dynamic technologies and advanced analytics in Consumer Lending
Opportunity in Consumer Lending
More than 1 in 4 households (28.3%) are either unbanked or underbanked, conducting some or all of their financial transactions outside of the mainstream banking system. )
Opportunity in Consumer Lending
Alternative Financial Services (AFS): Check-Cashing Outlets Money Transmitters Car Title Lenders Payday Loan Stores Pawnshops Rent-to-Own Stores
Opportunity in Consumer Lending
" One$quarter*of)households)have)used)at)least)one)AFS)product)in)the)last)year)
" Almost)one*in*ten*households)have)used)two)or)more)AFS)
)" 12*percent*of)households)had)used)an)AFS)
product)in)the)previous)30)days,)including)four*in*ten*unbanked)and)underbanked)households.)
The)FDIC)study)revealed:)
Opportunity in Consumer Lending
The Data Industry Ecosystem
))DATA)Data)
DATA)
data)
Data)
DATA)
data)
OpenUSource)PlaJorms)
Aggregator)
Entrepreneur) Enterprise)
Owner)
Individuals/)Brigades)
Opportunity in Consumer Lending
AFS Data; fragmented and represents opportunity " Where does this data reside?
" How can this data be integrated with established and unstructured data sources?
" Who could be an aggregator?
" What would be the platform?
Where we are and Where we’re going... The state of the industry through the eyes of experts
Finding value in new sources of data, technology platforms and analytic methodologies
Incorporating the new into established practices
Research & Findings
Capitalizing on today’s big data, dynamic technologies and advanced analytics in Consumer Lending
“I believe new modeling techniques that employ machine learning can aid both consumers and financial institutions by developing
more accurate models. “
Research & Findings
3 Key Findings: " We do not spend the appropriate amount of time on
defining the business problem
" Is there a need for a development sample in the world of machine learning and adaptive predictive models?
" We must create a new management system to support and integrate new capabilities with existing tools and processes.
Research & Findings
Connecting Business Leaders with Analytics Experts requires:
" Deep Business Understanding,
" Sophisticated Analytic Domain Expertise,
" Market and Target Segment Definition, and
" A Clear Understanding of the Business Objective.
Research & Findings
We do not spend the appropriate amount of time of defining the business problem
Traditional example: Developing a Model for Revenue Growth in a Credit Card Portfolio
" Establish the mix of balance growth
" Identify the underlying reason for balance growth
" Understand customer attitudes and characteristics
" Analyze various scenarios to focus the business problem and define the objective function
Research & Findings
Finding Value in New Sources of Data: How would we build models to include these 28.3% that have used AFS?
" Understand customer attitudes and characteristics " Identify the underlying reason for balance growth
" Analyze various scenarios to focus the business problem
" Establish the mix of balance growth
" Define the objective function
Research & Findings
The Human Element:
" Defines what a model needs to predict,
" Equips the model with the knowledge of vast data sources,
" Provides the business acumen and experiences to help the machine keep learning, and
" Validates the models success by applying it within the business.
Research & Findings
Is there a need for a development sample in the world of machine learning and adaptive predictive models?
How Machine Learning Will Improve the Accuracy of Predictions AND is Contingent on a Human Contribution.
Research & Findings
The Four Players " The Cognitive Computing Platform
" The Computer Scientist-
" The Data Specialist
" The Business Analyst
Research & Findings
We must create a new management system to support and integrate new capabilities with existing tools and
processes
Summation
“Organizations are looking for a combination of human intuition and machine intelligence that possesses the ability to answer questions they were previously unable to answer”
Re-cap " Critical trends are redefining industry
" Machine learning improves outcomes and is contingent on human contribution
" There is potential to derive value from previously excluded segments
Summation
Vision without action is daydream.
Action without vision is
nightmare.
— Japanese Proverb
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