Sift Case Studies How Zirtue keeps relationship-based lending honest and safe

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	How Zirtue keeps relationship-based lending honest and safe Sift

How Zirtue keeps relationship-based lending honest and safe

Sift

Technology Category	Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - API Integration & Management
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Use Cases	Fraud Detection Regulatory Compliance Monitoring
Services	Data Science Services System Integration
Challenge	Zirtue, a mobile relationship-based lending application, was facing a growing issue of friendly fraud where users were disputing their loan payments falsely claiming they had not authorized the transactions. This was compounded by the fact that Zirtue had access to a very limited amount of user data, preventing them from proactively recognizing suspicious behaviors and stopping the fraud before it happened. Additionally, the vetting process for taking out a loan was lengthy and required tedious and time-consuming email exchanges between Zirtue and the borrower, to ensure the borrower could confirm their identity. This manual work frequently delayed loans, creating headaches for the Data Analytics team and borrowers alike, and it was looking as though another team member would need to be hired to help handle the workload. Read More
About Customer	Zirtue is a mobile relationship-based lending application that simplifies loans between family, friends, and trusted relationships with automatic ACH loan payments. Both parties agree to a loan repayment schedule, the payments are made automatically via the payer’s bank account, and the awkwardness of asking to be repaid becomes a thing of the past. Based in the US, Zirtue grows 60% month-over-month as they work to create a more financially inclusive world. The platform is targeted specifically to college students, offering 24/7 study help for topics ranging from business and programming to writing and humanities. Read More
Solution	Zirtue implemented Sift’s Payment Protection product which provided access to a wealth of data that Zirtue didn’t have, completely revolutionizing the way the Data Analytics team managed fraud. The team implemented Workflows that automatically blocked users with certain Sift Scores (risk score based on behavioral attributes), eliminating the need to pore over documents and send multiple emails to ensure users were trustworthy. With the Network feature, Zirtue’s team has been able to identify additional accounts connected with fraudulent users, preventing fraud rings from transacting on the platform. This full-picture understanding of their user base has made the team more knowledgeable overall, and better equipped to spot suspicious behavior and activities. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - API Integration & Management

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Use Cases

Fraud Detection

Regulatory Compliance Monitoring

Services

Data Science Services

System Integration

Challenge

Zirtue, a mobile relationship-based lending application, was facing a growing issue of friendly fraud where users were disputing their loan payments falsely claiming they had not authorized the transactions. This was compounded by the fact that Zirtue had access to a very limited amount of user data, preventing them from proactively recognizing suspicious behaviors and stopping the fraud before it happened. Additionally, the vetting process for taking out a loan was lengthy and required tedious and time-consuming email exchanges between Zirtue and the borrower, to ensure the borrower could confirm their identity. This manual work frequently delayed loans, creating headaches for the Data Analytics team and borrowers alike, and it was looking as though another team member would need to be hired to help handle the workload.

About Customer

Zirtue is a mobile relationship-based lending application that simplifies loans between family, friends, and trusted relationships with automatic ACH loan payments. Both parties agree to a loan repayment schedule, the payments are made automatically via the payer’s bank account, and the awkwardness of asking to be repaid becomes a thing of the past. Based in the US, Zirtue grows 60% month-over-month as they work to create a more financially inclusive world. The platform is targeted specifically to college students, offering 24/7 study help for topics ranging from business and programming to writing and humanities.

Solution

Zirtue implemented Sift’s Payment Protection product which provided access to a wealth of data that Zirtue didn’t have, completely revolutionizing the way the Data Analytics team managed fraud. The team implemented Workflows that automatically blocked users with certain Sift Scores (risk score based on behavioral attributes), eliminating the need to pore over documents and send multiple emails to ensure users were trustworthy. With the Network feature, Zirtue’s team has been able to identify additional accounts connected with fraudulent users, preventing fraud rings from transacting on the platform. This full-picture understanding of their user base has made the team more knowledgeable overall, and better equipped to spot suspicious behavior and activities.

Impact #1	Zirtue’s fraud loss dollars were reduced to 1.6% of what they were prior to implementing Payment Protection.
Impact #2	They were able to trim 14-18 hours off of their manual reviews every week, eliminating the need to hire another data analyst to focus on fraud.
Impact #3	Now the team is able to shift their attention to creating delightful customer experiences, and making transactions between family, friends, and trusted connections easier than ever.

Impact #1

Zirtue’s fraud loss dollars were reduced to 1.6% of what they were prior to implementing Payment Protection.

Impact #2

They were able to trim 14-18 hours off of their manual reviews every week, eliminating the need to hire another data analyst to focus on fraud.

Impact #3

Now the team is able to shift their attention to creating delightful customer experiences, and making transactions between family, friends, and trusted connections easier than ever.

Benefit #1	Fraud loss dollars reduced to 1.6% of what they were prior to Sift
Benefit #2	Manual review reduced by 14-18 hours weekly

Benefit #1

Fraud loss dollars reduced to 1.6% of what they were prior to Sift

Benefit #2

Manual review reduced by 14-18 hours weekly

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Overview

How Zirtue keeps relationship-based lending honest and safe

Operational Impact

Quantitative Benefit