Big Data Presentation Mar 2015 Washington Summit

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SINK OR SWIM IN BIG DATA NEW POSSIBILITIES FOR FINANCIAL PROFESSIONALS AND EMPOWERMENT OF COMMUNITIES Andrew Garrett Director Development Analytics

Transcript of Big Data Presentation Mar 2015 Washington Summit

Page 1: Big Data Presentation Mar 2015 Washington Summit

SINK OR SWIM IN BIG DATA

NEW POSSIBILITIES FOR FINANCIAL PROFESSIONALS AND EMPOWERMENT OF COMMUNITIES

Andrew Garrett

Director Development Analytics

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What is Big Data? What’s New?

Variety

Velocity

Volume

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What is a Petabyte? Zettabyte?

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Tyson’s Galleria, McLean, VA

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Typical Shopper Profile

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Journey of 1000 Shoppers

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On-line Browse

Parking & Path

Apps

• 80% Mall Directory

• 10% Map

• 1% Ordered Gift Card

• 54% Clicked on Women’s Apparel

• 33% West lot

• 65% Entrance 7

• Avg. Apple visitor, 20% P( ) they visit Starbucks

• 10% have Disney app on phone

• 3% have Twitter post with negative comment about the mall

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Journey of 1000 Financial Professionals

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Sector

Advancement

Network Weighting

•27% Insurance

•50% Wealth Management

•10% Real Estate

•54% Accounting / Other

•33% Title Change

•65% Left sector

•24% Retention rate in Insurance

•Endorsements by VP correlated with promotion in 2yrs

•10% have linked to Directors within own firm

•3% underemployed. CPA holders, leaving sector

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Journey of 1000 Underbanked Minorities

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Networth

Advancement

Financial Products

• $25K avg. HHI

• $50 avg. interest fees

• 17% Denied Credit

• 33% Checked local Trust Co.

• 65% built >$1000 savings due to auto saving deduction

• 24% Retention rate in Insurance

• 10% Used mobile app

• 3% denied Credit

• 43% offered high interest rate credit card

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Simple, Novel, Unstructured problems

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Google Cat Recognition Software:

o Human Baby can ID a million cats having only seen one

o Big Data, google vision needs to scan and ‘see’ a million cats to try to ID one

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Spurious Correlations

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Privacy Concerns / Legislation

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Financial Professionals:

A Catalyst For Change

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Public Sector Data • Federal Spending • Demographic • Underserved Areas

Private Sector Data • Linkedin • Annual reports • C-Suite & Board Profiles

Individual & Assoc. Data • UFSC, NUL, • Workshops • University’s

Data Ware-house

Data Mining and Analysis

New Solutions to Old Problems: • Career

Advancement • Company Profits • Community

Empowerment