WHY MICROFINANCE NEEDS MACHINE LEARNING
Transcript of WHY MICROFINANCE NEEDS MACHINE LEARNING
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WHY MICROFINANCENEEDSMACHINE LEARNING
Abby BilenkinVincent Tandaw
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Roadm ap
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● Prob lem● Machine Learning● Solut ion● Investm ent
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over $60 billiontotal invested in microfinance as of March 2015
200 million clientsof microfinance as of 2015
only 20% reachedby microfinance as of 2015
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An Incomplete PictureRepayment rate misses
the pointWealth creation
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Big Prob lem # 1:
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94%Immediate Consumption
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An Incomplete PictureRepayment rate misses
the pointWealth creation
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Big Prob lem # 1:
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Big Prob lem # 2:Availabil ity
Lack of on-site implementation
Complicated
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MACHINE LEARNING IMPROVES MICROFINANCE
▫ Used in conventional banks
▫ Computers are better than people at reducing mistakes by 13.7%
▫ Neural network models technology
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$600,000,000
1% saved
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45 Seconds of Mach ine Learning
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Non-tradit ional metrics
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Misal locat ion of loans
Easily accessible medium
Tw o Part Prob lem ,Tw o Part Solut ion
Complicated and unavailable
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Who Will Care?
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Proof of Concep t
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Why is it not done?
Scient if ic studies
No scaling activities
“Niche” MFIs
Different target
audience
Banking
Different target
audience
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Finances
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▫ Stipend for two mentors▫ Labor▫ Travel expenses
Total: $750 0
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Siddharta Ghose Data specialist at AidDataSix years banking experience▫ Barclays▫ HSBC
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October 2017Partner outreach
December 2017Algorithm development
January 2018Refine algorithm
March 2018Write report
May 2018Release project
September 2017Obtain datasets
Tim eline
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Deliverab les
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Mobile sitePolicy brief
Strong public relationsRollout partnerships
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Chris Elsner Allie Cooper
Assessing the Gaps in Aid Allocation
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● Gaps in Allocation
● No Metric for Accountability
Constraints on Country Ownership
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Refocusing on Recipients
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Data
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Approach
Step 1 - Adapt SDG coding methodology
Step 2 - Map demand for the SDGs
Step 3 - Compare aid flows to demand
Step 4 - Produce ranking and subnational case study
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Scalability
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Outreach & Distribution
Our Research
Development Agencies NGOs Think Tanks
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Team
AidData
Chris & Allie
JakeRebecca
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Budget:
$7,895
Fall Semester - $4,900● Code data
● Analyze data
● Produce Malawi case study
Spring Semester - $2,995● Create ranking
● Distrib te res lts
Milestones & Financing
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Indexing Taxation George Moss
Caroline Nutter
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$100bn in lost tax revenue each year
10 - 20 % of GDP (Developing Countries)
40 - 50 % of GDP (Developed Countries)
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Tax Revenue Overview
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Regular testimonies before Congress and a primary resource
for country eligibility at MCC
530 regulatory reforms and 45 ministerial committees formed
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What Has Worked
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Downloadable data in a public domain that’s
accessible and user-friendly
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Beneficial to all
at World Bank:
- Tax Administration Modernization Project
- Tax Reform Adjustment Loan Project
at USAID:
- Armenian Tax Reform Project
- Property Tax Reform Project
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Impact
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$5,000
$3,500
$ 490$1,000
$ 10+40
Research
TravelDomain
Mentor
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Phase 1: Publish data-By end of 2017: Indexing for at least 50 countries
-By end of spring 2018: full index completed and published on online domain
Phase 2: Partner takes on report
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Ma p p in g Urb a n Fo o d In se cu rit y in t h e De ve lo p in g W o rld
Max Maiello and Elizabeth Sutterlin
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Urban Grow th - Shrinking Market Access
United Nations The World’s Cities in 2016
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“Data on urban food insecurity is sparse at best.”
- Arif Husain Chief Economist, World Food Programme
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Remote Mobile (SMS)
Surveys
City Population
Data
Using Data to Understand Food Insecurity
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● Distance traveled for food
● Physical obstacles to food
● Informal markets and vendors
● Tradit ional markets
● Ability to cook in households
Pilot Study: Hyderabad, India
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Available Data Mobile (SMS) Surveys
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Policy Relevance
● Ident ify the most in-need neighborhoods and city sectors
● Target efficient locat ions for food aid
● Recommend improvements in planning for urban planners and city officials
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Deliverab les
● Collected data on neighborhoods and food sources in our pilot city (Hyderabad, India)
● Report summarizing and analyzing the results of our data collect ion
● Disseminat ion of results through online publicat ion and through food aid and urban development organizat ions
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Project Tim eline
Fall 2017 Semester●Gathe r and catalogue population and poverty data
from pilot city of Hyderabad, India ● Remote mobile survey ce rtification● Deve lop list of survey questions ● Identify translator(s) for survey● Implement survey
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Project Tim eline
Spring 2018 Semester●Catalogue and analyze translated survey re sults● Produce de live rable report
Visual summariesBreakdowns of re sultsFurthe r applications
● Present and distribute report
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Budget Item Cost
Mentor stipend $1,000
Research stipends $3,000
Survey Implementation $1000
Mobile phone credits for survey participants
$500
Salary for translator(s) $500
TOTAL ASK $6,000
Project Budget
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Global Media Perceptions of U.S. Foreign Policy
Katherine ArmstrongJack Shangraw
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Deteriorating U.S. Image
-The Guardian (UK), September 29, 2004
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-Der Spiegel (Germany), October 3, 2013
Deteriorating U.S. Image
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-The Independent (UK), June 29, 2017
Deteriorating U.S. Image
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Deteriorating U.S. Image
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HonoredInvaluableProblem-solver
DispleasedTyrannical
Self-serving
Sentiment Tracking Tool
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e.g. Refugee
Crisis
Methodology
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Sentiment Trends
Perc
ent P
ositi
vity
Positive wordsNegative wordsNeutral words
Date
Methodology
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● Continuous
● Readily available
● Cost-efficient
● Near real-time
Why Media?
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MediaNGOsGovernment
Beneficiaries
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Preserving Global Leadership
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Michael GiovannielloAnatoly Osgood
IDENTITY MESSAGING AND ENVIRONMENTAL DEVELOPMENT
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CLIMATE-RELATED DEVELOPMENT AID
30
20
10
0
USD
Bill
ion
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Project Outcomes in Malawi
-Transition to drought resistant crops hailed as saving the country
-Still has the highest deforestation rate in Africa
-Why such different outcomes?
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Receptive communities are essential
It’s the Communication, Stupid
How to convince recipients
Shortcomings in issue-specific
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HYPOTHESIS
If individuals perceive their group as prioritizing climate change action then, they will have higher support for local environmental
development projects.
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METHODOLOGY
MEASURE MODERATING VARIABLE
How closely respondent aligns with group-identity used in treatment
APPLY TREATMENT
Information suggesting prominent identity-group supports action
MEASURE TREATMENT EFFECT
Inform recipients about a potential environmental development project in their community
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TARGET AUDIENCE
UNDPPEACE CORPS CONSERVATION INTERNATIONALWORLD BANK
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APPROACH AND MILESTONES
PLANNING
DESIGN
EXECUTION
ANALYSIS
DISSEMINATIONSept. 2017 Feb. 2018
Mar. 2018
Apr. 2018
Nov. 2017
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PROBLEM
Environmental development communication often fails
SOLUTION$9,970 → how group-identity increase support for climate change development projects
IMPACT AND SCALABILITY
Potential to improve communication strategies throughout all development fields
CONCLUSION
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TRACKING TARGETSIDENTIFYING ETHNIC MINORITY VIOLENCESami Tewolde and Lincoln Zaleski
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PROBLEM
● Data is SCATTERED
● Lack of access to WHERE specifically this ethnic violence occurs
● Organizations are aiming in the DARK
Significant gaps in the understanding of the geopolitical implications of
minority relations
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SOLUTION
Creation of a tool that will bring criticalgeospatial information to organizations that
affect change
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OPTION 1: Series of Static Maps
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OPTION 2: Interactive Map
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“A geocoded map of ethnic violence would be an essential tool for the international community...This is not something we already have, and we need to.” - Arslan Malik (Former UN Peacekeeping Senior Policy Advisor)
“A geocoded map would be extremely useful...and this is an enormously important area. -Johanna Birnir (Director, All Minorities at Risk)
“Enormously important area”
“This is not something we have… we need to”
“Extremely useful”“Essential tool”
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IMPACT POTENTIAL
Building Block
Tool for Analysis
Public Good
Uighurs in China
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MILESTONESOct. 1st, 2017: ArcGIS Learned
Oct. 15th, 2017: Merge GTD + AMAR
November 15th, 2017: MENA data
geocoded onto the maps
March 1st, 2018: Asia data geocoded onto
the maps
May 1st, 2018: Africa data geocoded onto
the maps
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Budget: Option 1$5,340
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Budget: Option 2$8,340
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Ethnic discrimination or violence affects ALL countries in Asia and the
Middle East but three.
This is not an anomalyThis pattern is seen worldwide
Millions of people are affected
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