ncur presentation walkmore
TRANSCRIPT
A REPORT FROM THESINGULARITY
SU?
TO USE EXPONENTIALLY GROWING TECHNOLOGIES TOPOSITIVELY IMPACT 1 BILLION PEOPLE IN TEN YEARS
80 STUDENTS FROM 36 COUNTRIES BROUGHT TOGETHER
“EXPONENTIALLY GROWING TECHNOLOGIES?”
COMPUTERS DOUBLE THEIR PROCESSING POWER EVERY TWO YEARS.
“There is a world market for maybe five computers.”
-‐ Tom Watson, Founder of IBM
“Cinema is a fad.”-‐ Charlie Chaplin
“Flight by machines heavier than air is unpracZcal and insignificant, if not
u[erly impossible.” -‐ Canadian mathemaZcian Simon Newcomb, 18 months before the Wright
Brothers’ flight
SINGULARITY TRAINS BUSINESS LEADERS, ENTREPRENEURS, SCIENTISTS, &
INNOVATORS TO THINK EXPONENTIALLY.
MOST BUSINESSES, GOVERNMENTS, SYSTEMS PLANNERS THINK LINEARLY
ABOUT THE FUTURE OF TECHNOLOGY.
Dr. Philipp KallerhoffJumiya, Inc
Eli MohamadJumiya, Inc
MEET CHRIS
THE INTERSECTION OF SYSTEMS
FOR EXAMPLE:CHRIS’ DOCTOR BILLS WERE SENT STRAIGHT TO A COLLECTION AGENCY, HURTING HIS CREDIT BY 100
POINTS.
62OF BANKRUPTCIES ARE
BECAUSE OF MEDICAL DEBTAMERICAN JOURNAL OF MEDICINE, 2012
%
CREDIT SCORING IS A BLACK BOX
Meet the gatekeepers.
IRMA WORKED WITH CHRIS AND WALKED WITH HIM
HAND IN HAND.
HER WORK REQUIRES AN UNDERSTANDING OF HOW MULTIPLE SYSTEMS INTERSECT AND EFFECT
CHRIS’ LIFE.
BUT IRMA’S ONLY ONE PERSON.
HOW CAN WE BETTER UNDERSTAND HOW COMPLEX SYSTEMS AND BEHAVIORS
IMPACT OUR LIVES?
MACHINE LEARNING ISFINDING PATTERNSIN COMPLEXITY
NETFLIX & AMAZON RECOMMENDATIONS
WITH PEOPLE LIKE CHRIS IN MIND: OUR TEAM USED MACHINE LEARNING EXPLORED THE CONNECTIONS IN HEALTH AND FINANCE.
SURVEYED HEALTH
SURVEYED FINANCE
$
THE TEAM FOUND PATTERNS
RUNNING HAS 6x CORRELATION WITH TIMELY BILL PAYMENT
DRINKING HAS A 6x CORRELATION WITH BANKRUPTCY
$80%
ACCURACY
HOW CAN WE LEARN MORE ABOUT THESE CONNECTIONS?
FIRST:
250 million transac5ons500,000 users
Can we predict member behavior, improve profitability, and reduce risk by looking at a dataset including:
PREDICT DEFAULTS WITH 80% ACCURACY
RESULTS DIFFERED FROM TRADITIONAL CREDIT SCORE BY 10%
MODEL APPROVES 1% MORE LOANS AND REDUCES DEFAULTS BY 15%
“For example, 5% of your members would be 10% more profitable if they used a loan product. 15% of
those members are very likely to sign up for the product, and using our new credit risk model we can approve 10%
more people for the loan”
PREDICT PRODUCT LIFE CYCLE • IMPROVE PROFITABILITY • REDUCE RISK
For example:
THE FIRST MINIMUM VIABLE PRODUCT
NEXT:CONNECT THESE FINDINGS WITH
WELLNESS BEHAVIOR.
The account that improves as you do.
Enable members to increase and improve access to financial products and be rewarded for a healthier lifestyle.
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By engaging in healthy behavior, members can posi5vely impact their financial access by
improving rates and balances.
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Use data from devices like Nike+, Fitbit, Runkeeper, or 100+ other providers...
...or just your phone...
Purpose
1. Generate new revenue from exisZng products2. Help retain exisZng and a]ract new CU members 3. Improve overall member profitability, reduce lending risk, and increase repayment
Calls to ac5on
• The research suggests healthy living members are be]er risk and more profitable• Researchers were able to predict the next best product using transacZonal data• The research suggests that quanZfied self data can improve the predic5on model even further• AddiZonal data sets -‐ economic or locaZon data, for example -‐ impact on consumer behavior.
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IS THERE A MEASURABLE CONNECTION
BETWEEN PHYSICAL AND FINANCIAL
HEALTH?
YESCAN WE PREDICT
BEHAVIOR BASED ON THOSE
CONNECTIONS?
YESCAN WE USE DATA TO PREDICT AND
IMPROVE MEMBERS FINANCIAL HEALTH?
YES
CAN WE INTEGRATE HEALTH AND FINANCIAL DATA TO MOVE MEMBERS ALONG A PATH TO TOTAL WELLNESS?
WE NEED OPT-‐IN MEMBER DATA
JOIN THE PILOT PROJECT
Calls to ac5on
Get involved in the pilot project• Pilot starts in July and will last 9 months• 3 credit unions, with 1 more spot available• All necessary infrastructure provided through plagorm at www.walkmo.re• The plagorm will be adapted to fit each credit union’s needs
