GO-JEK dominates the on-demand delivery and transportation market in Indonesia. With a click on a button, customers can order everything from food, groceries to massages.
GO-JEK
Fraud Analytics
Needs
Fraud Detection
Industry
Ride Sharing
Client
Timeline
April 2017 - September 2018
ABOUT GO-JEK
BUSINESS CHALLENGES
They process more than 100 million transactions for over 20 million monthly users. However, the scalability of their platform presents opportunities for users to defraud their services and undermine their user experience.
Organized crime syndicates use advanced technology to circumvent the system and reap rewards. The two major challenges they face are GPS fraud (location spoofing) and incentive fraud.
GPS spoofing occurs when a driver falsely claims they are in a high demand area. This enables them to retrieve more jobs, which results in longer wait times for their matched passenger.
Like Uber, Lyft and Grab, GO-JEK provides incentive programs for drivers that have achieved a high volume of trips. This prompts many drivers to take advantage of the system by creating fake driver profiles to simulate real trips.
GOALS
Initially, their team took at least 30 minutes to detect bad behaviour, which would delay service to customers and allow culpable users to escape.
Consequently, they needed a comprehensive solution to help their team inspect trips and identify negative activity in real-time.
RESULTS
In collaboration with the GOJEK fraud and data science teams, Afi Labs built JARVIS to visualise errant behaviour and respond to changes in a constantly evolving landscape. Using machine learning, we create trip attributes to help classify these trips and ban drivers automatically.
With the help of JARVIS, GO-JEK no longer spends significant amounts of time filtering data. JARVIS seamlessly connects to their trip database and flags fraudulent behavior in seconds.
ADDRESS
595 Burrard Street
Vancouver,
BC V7X1L4
Canada
ADDRESS
12 Marina Boulevard
Marina Bay Financial Center Tower 3,
Level 17-01
Singapore 018982