Br-fox is a Singapore-focused fraud prevention product that leverages on anonymized behavioral data and machine learning to prevent and detect identity fraud, right at account creation level for e-commerce platforms, lending platforms and any platform that require identity verification before doing transactions. Beyond the usual identity verification methods such as credit or transaction history, Br-fox can accurately identify anomalous profiles in real-time even before a transaction takes place. It does not matter if a fraudster plans to execute sophisticated scams on your platform, Br-fox prevents fraud even before a fraudster can create an account to perform any transactions; protecting customers and building trust while ensuring the highest level of compliance to our local data protection act.

For lenders and Buy-Now-Pay Later providers:
It can effectively complements traditional credit metrics and can be used as a substitute when traditional credit metrics are absent, hence users can safely capitalize on opportunities that are largely overlooked due to traditional scoring methods. Br-fox gives Buy-Now-Pay-Later (BNPL) players and lenders an unbeatable edge. It prevents fraud effectively and keep negative rates under control, even for customers without credit history building on our anonymized behavioral data that has been processed and designed to be secure, non-intrusive and confidential in real-time, seamlessly.

For e-commerce platforms and businesses:
The rise in eCommerce has unfortunately meant a rise in scams. According to the Singapore Police Force 2020 annual crime brief report, overall crime rate in Singapore has increased by 6.5% from 2019 to 2020 due to a rise in scam cases, especially with e-commerce scams being the top scam type, with a startling 3,354 reported cases in 2020. Br-fox prevents fraud at merchant and buyer account creation level. With the rise of online scams and fraud in Singapore, our project will help businesses effectively and efficiently prevent fraud using machine learning and AI, especially for cases such as identity theft.


1. Built on anonymized behavioural data, Br-fox allows for 120,000 possible scenarios for fraud identification.
2. Faster and improved decisions with instant real time generation of results.
3. Efficient prevention of fraud from taking place early on before a transaction takes place.
4. Seamless use on all platform types - API integration, web-based options are available.