One of the Philippine’s fast-growing micro-finance institutions, with the aim to uplift millions of Filipino lives through micro-financing. But with increasing customer attrition, how can they retain them in order to serve them? Four data science scholars. 14 weeks. Find out how they, together with the guidance of their mentor, harnessed the power of analytics to provide solutions to a company on a mission to improve the economic well-being of the poor

1. F
CHURN
ANALYSIS
01
for a Microfinance Institution
TEAM FAST AND FURR-IOUS

2. F
02
Alleviate
Empower
Grow
Providing financial and non-financial services
to improve the economic well-being of the
poor.
TEAM FAST AND FURR-IOUS

3. 03
Why are clients defaulting?
Why are they dropping out?
"To serve them,
we need to retain them."
F TEAM FAST AND FURR-IOUS

4. F
04
Improved Products
and Services
Reach target loan
portfolio by 2023.
More Happy Clients,
More Loyal Clients
Decrease in client dropouts
Growth and More
Lives Changed
Reach more clients,
touch millions of lives
by 2023.
TEAM FAST AND FURR-IOUS
Value Proposition

5. 05
1 2 3 4 5
50
40
30
20
10
0
F
Tenure in Years
● Business Intelligence
● Descriptive Analytics
● Inferential Analysis
To study the key factors
related to dropout cases
from the identified products
of the company using:

6. 06
Underlying Magic
Extract
Retrieve data from the
database using
Microsoft SQL.
Explore
Gather initial intel on the
structure of the data
using Excel,Tableau and
and Python
Visualize
Extract insights and tell
the story of the data
using Tableau
F
Clean
Data preparation
through the use of
Python
Communicate
Present findings
to the stakeholders
using Tableau
and Powerpoint
Deploy
Turnover of the final data
set, notebooks, tableau
files, and presentations
to our client
Delivered minimum viable products while continuously getting feedback from client on how to further improve the project.
Ways of working: Agile Methodology
SQL

7. 07 Domain
Knowledge
Data
Issues & Validation
F
Challenges Encountered
Data Wrangling
Techniques
Short
Timeline
SQL, Tableau,
Python
Tools

8. 09
F
Data issues uncovered
helped the client realize the
need for better structure of
data and design of the system
light-bulb ideas
Actionable Insights
and gave them
on how to improve their system
application control and data collection

9. 08
F
Actionable Insights
42%DROPOUT CLIENTS
7MUNCOLLECTED PAYMENTS
2 out of 5 clients dropout
Client’s first loan and year
are critical stages in retaining
them.

10. 10
F
Actionable Insights
New clients
are more sensitive in their experience hence,
higher tendency to drop out.

11. 11
F
It’s not just about the product.
It’s also about customer experience.
Actionable Insights

12. 11
Design Referral System
Enhance Data Collection
● Train staff as “brand ambassadors”
● Optimize process for convenience
Conduct Further Studies
● Market segmentation
● Social media analytics
F
Recommendations
Improve Customer Experience
● Collect more customer data
● Regular Customer Satisfaction Surveys
● Data Validation Controls
● Encourage customers to refer
● Make it easy and rewarding

13. 12
Team Fast
and Furr-ious
Grace
Database Master, Query Specialist
Queenie
Pythonista, Data Wrangling Expert
Angel
Pythonista, Data Wrangling Expert
Airees
Tita of Tableau, Visualization Specialist
F