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Engineering · Data Science · SecurityGraph for fraud detection
Fraud detection has become increasingly important in a fast growing business as new fraud patterns arise when a business product is introduced. We need a sustainable framework to combat different types of fraud and prevent fraud from happening. Read and find out how we use graph-based models to protect our business from various known and unknown fraud risks.
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Engineering · Data ScienceQuery expansion based on user behaviour
User behaviour data is a gold mine to gain insights about users and help us improve user experience. In this blog, we explore a query expansion framework based on user rewrite behaviour and how it improves user search experience and conversion.
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Engineering · Data Science · SecurityUsing mobile sensor data to encourage safer driving
Telematics is most commonly used to monitor vehicle movements and track driving safety, profiling, fleet optimisation and possible productivity improvements. Read this to find out more about how Grab uses telematics to encourage safer driving across our driver and delivery partner fleet.
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Engineering · Data ScienceAutomatic rule backtesting with large quantities of data
At Grab, real-time fraud detection is built on a rule engine. As data scientists and analysts, we need to analyse and simulate a rule on historical data to check the performance and accuracy of the rule. Backtesting, also known as Replay, enables analysts to run simulations of either newly-invented rules, or evaluate the performance of existing rules using past events ranging from days to months, and significantly improve rule creation efficiency.
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Engineering · Data ScienceHow we store and process millions of orders daily
The Grab Order Platform is a distributed system that processes millions of GrabFood or GrabMart orders every day. Learn about how the Grab order platform stores food order data to serve transactional (OLTP) and analytical (OLAP) queries.
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EngineeringHow we automated FAQ responses at Grab
Most frequently asked questions (FAQ) are repetitive, which hinder on-call engineers' productivity. Read to find out how we automated FAQ responses at Grab, allowing engineers to focus on operational tasks.
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Engineering · Security · Data ScienceGraph Networks - 10X investigation with Graph Visualisations
As fraud schemes get more complex, we need to stay one step ahead by improving fraud investigation methods. Read to find out more about graph visualisation, why we need it and how it helps with uncovering patterns and relationships.
Engineering
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Design
How KartaCam powers GrabMaps
The foundation for making maps lies in imagery and ensuring that it is fresh, high quality, and collected in an efficient yet low-cost manner. Read this to find out how the Geo team created KartaCam, how it addresses those concerns, and its future enhancements.
