DataRobot > Case Studies > Zidisha is Transforming Lives with DataRobot

Zidisha is Transforming Lives with DataRobot

Customer Company Size

Startup

Region

Africa
Asia

Country

Ghana
Kenya

Product

DataRobot Enterprise AI platform

Tech Stack

Machine Learning
SQL
Spreadsheets

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Cost Savings
Productivity Improvements

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Finance & Insurance
Education

Applicable Functions

Procurement

Use Cases

Predictive Quality Analytics
Fraud Detection

Services

Data Science Services

About The Customer

Zidisha is a non-profit online microlending community that connects borrowers directly with lenders. It promotes crowdfunding of micro-loans for people in some of the poorest countries in the world to start and grow a business or fund their education. Zidisha does not charge interest on loans; instead, borrowers pay a 5% service fee to cover the cost of transferring and administering the loan. With Zidisha, entrepreneurs get access to business loans on flexible terms and at an affordable cost, allowing them to keep a majority of their profits and invest them back into their businesses or use them to support their families. Zidisha circumvents traditional approaches to identifying, quantifying, and pricing default risk, removing the need for loan officers or bank specialists. In place of due diligence undertaken by a loan officer, Zidisha fosters direct relationships between borrowers and lenders.

The Challenge

Zidisha, a non-profit online microlending community, aims to transform the lives of people in some of the poorest countries by offering microloans to create businesses, attend school, or improve their living conditions. However, every loan carries the risk of default. Traditional lenders have found ways to identify, quantify, and price default risk, with higher risk loans attracting higher interest rates. The work of assessing risk commonly falls to a loan officer and the costs are passed on to the borrower. In developed economies where loans of thousands or hundreds of thousands of dollars are common, these costs can be comfortably absorbed without undermining the case for taking a loan, but this is not the case in developing countries. Employing a loan officer to assess default risk for a microloan results in interest rates as high as 40%, undermining promotion of economic development. Zidisha's challenge was to improve levels of repayments by identifying applicants most likely to be high-risk borrowers.

The Solution

Zidisha partnered with DataRobot to develop and deploy machine learning models that radically improve the loan application and screening processes. A customer facing data scientist (CFDS) at DataRobot suggested Zidisha would benefit from two predictive models: one to detect fraudulent applications and a second to identify applicants with a high propensity to default on their loan. Protecting their lenders’ money is fundamental to Zidisha’s long term success, as it makes more loans available to trustworthy borrowers who truly need them and increases the rate at which money is recycled to other worthy borrowers. Julia and her colleague worked with the DataRobot team to integrate the platform with their systems, and simply read the DataRobot user docs to start developing their own predictive models for Zidisha. The two models created by Julia and her colleague in less than two weeks have profoundly improved the percentage of loans repaid to lenders on Zidisha by reducing loan defaults by 5%.

Operational Impact

Zidisha's models are directing more capital to people who otherwise wouldn’t be able to afford to attend university, send their children to high school, or start a business that will improve their family’s standard of living and boost the local economy.
By reducing the risks of losing lenders disheartened by poor rates of repayment and keeping capital in the hands of reliable borrowers, DataRobot is helping Zidisha to achieve its mission and improve the lives of thousands of people across the world.
Zidisha admits greater numbers of borrowers but only advances small loans to individuals assigned a high risk score.

Quantitative Benefit

Zidisha advanced loans worth $500,000 in a recent month.
If the DataRobot Enterprise AI platform helped Zidisha lift loan repayments by only 1%, the platform would pay for itself.
Zidisha's machine learning model had a 5% lower default rate measured in dollars repaid.