Sift Case Studies How Studypool proactively prevents fraudsters from cheating the system

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	How Studypool proactively prevents fraudsters from cheating the system Sift

How Studypool proactively prevents fraudsters from cheating the system

Sift

Technology Category	Analytics & Modeling - Machine Learning Application Infrastructure & Middleware - API Integration & Management
Applicable Industries	Education
Applicable Functions	Business Operation
Use Cases	Fraud Detection
Services	Cybersecurity Services
Challenge	When Studypool first launched, the platform saw users who were taking advantage of tutors by posting questions and later filing chargebacks, in an attempt to get free study help. Some users also tried to game the system by creating fake student accounts so they could pay themselves and later file a chargeback, ultimately getting their money back and a payout from Studypool. At the time, their internal fraud prevention tools couldn’t keep up with the types of fraud surfacing on the platform. The tools were only able to track IP addresses and weren’t accurate or reliable, so Studypool decided to look for a better solution. Read More
About Customer	Studypool is a two-sided online marketplace that connects students with questions with tutors that can answer them. The ed-tech platform is on a mission to provide students with access to high-quality tutors, regardless of their time, location, or budget constraints. Studypool has adopted an innovative microtutoring concept, which connects students with thousands of verified tutors to help them with specific academic questions through on-demand tutoring sessions. Targeted specifically to college students, the platform offers 24/7 study help for topics ranging from business and programming to writing and humanities. Read More
Solution	To mitigate fraud on the platform, Studypool’s trust and safety priorities include both identifying fraudulent activity and accurately anticipating ill-willed schemes. This is where Sift comes in, providing the necessary tools and information Studypool relies on for its fraud-fighting processes. The Studypool team uses Sift specifically for case management to study user behavior and aid in their decision-making process. Studypool relies on Sift to identify user geolocation, which accounts are linked to each other, and see user activity including if those users have been flagged in the past under different accounts. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Application Infrastructure & Middleware - API Integration & Management

Applicable Industries

Education

Applicable Functions

Business Operation

Use Cases

Fraud Detection

Services

Cybersecurity Services

Challenge

When Studypool first launched, the platform saw users who were taking advantage of tutors by posting questions and later filing chargebacks, in an attempt to get free study help. Some users also tried to game the system by creating fake student accounts so they could pay themselves and later file a chargeback, ultimately getting their money back and a payout from Studypool. At the time, their internal fraud prevention tools couldn’t keep up with the types of fraud surfacing on the platform. The tools were only able to track IP addresses and weren’t accurate or reliable, so Studypool decided to look for a better solution.

About Customer

Studypool is a two-sided online marketplace that connects students with questions with tutors that can answer them. The ed-tech platform is on a mission to provide students with access to high-quality tutors, regardless of their time, location, or budget constraints. Studypool has adopted an innovative microtutoring concept, which connects students with thousands of verified tutors to help them with specific academic questions through on-demand tutoring sessions. Targeted specifically to college students, the platform offers 24/7 study help for topics ranging from business and programming to writing and humanities.

Solution

To mitigate fraud on the platform, Studypool’s trust and safety priorities include both identifying fraudulent activity and accurately anticipating ill-willed schemes. This is where Sift comes in, providing the necessary tools and information Studypool relies on for its fraud-fighting processes. The Studypool team uses Sift specifically for case management to study user behavior and aid in their decision-making process. Studypool relies on Sift to identify user geolocation, which accounts are linked to each other, and see user activity including if those users have been flagged in the past under different accounts.

Impact #1	Using Sift, Studypool has learned how to apply rules efficiently and lower false positives by pinpointing fraudulent behavior with reliable accuracy.
Impact #2	After initially using Sift to lower chargebacks, their disputes are now under control at a low and steady rate, and have also seen significant improvements in operational efficiency.
Impact #3	Implementing Sift has also allowed Studypool to extend fraud detection across touchpoints and protect some of the features offered to users, such as their partner program.

Impact #1

Using Sift, Studypool has learned how to apply rules efficiently and lower false positives by pinpointing fraudulent behavior with reliable accuracy.

Impact #2

After initially using Sift to lower chargebacks, their disputes are now under control at a low and steady rate, and have also seen significant improvements in operational efficiency.

Impact #3

Implementing Sift has also allowed Studypool to extend fraud detection across touchpoints and protect some of the features offered to users, such as their partner program.

Benefit #1	Chargebacks are no longer a concern
Benefit #2	Invaluable insights into users
Benefit #3	Maintaining a fraud-free platform

Benefit #1

Chargebacks are no longer a concern

Benefit #2

Invaluable insights into users

Benefit #3

Maintaining a fraud-free platform

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Overview

How Studypool proactively prevents fraudsters from cheating the system

Operational Impact

Quantitative Benefit