Problem Importance
A study revealed that all mobile subscribers in Nigeria receive spam SMS, receiving an average of 2.45 spam SMS daily. In recent times, the proliferation of fraud and fake information has made it challenging to identify trustworthy messages and information. Fraudsters specifically use this window as a major agent of fraud, thus increasing the need to provide a clear perception into the reliability of online content.
All mobile subscribers in Nigeria are affected and this made everyone with a mobile phone in Nigeria susceptible to fraud.
Solution Description
NaLie is a solution that provides a real time validation system for text messages. It uses CrowdML and NLP for Detection and verification of Text-based Financial Fraud and Fake messages. It was first released in 2019.
Solution output description
The output of the solution is a response of the class the text the message belongs to. Text classes are Fake BVN, Investment Scam, 419 Scam, Fake job and Good Text. The solution validates input text based on two major criteria. One is Database method (i.e., Sender Id, Profile and author) and the other is Feature based method (Message Content and Linguistic feature).
Solution Usage
The intended use of the solution
The aim of the solution is to proactively detect and prevent text-based financial fraud and fake messages. For instance, a mobile subscriber receives a text message to click on a link to update her Bank Verification Number (BVN) details as a result of the system update currently going on in her bank. Immediately the message drops, a NaLie notification pops up to warn the user that the message is fraudulent.
The key procedures followed while using the solution
The solution receives text as input from the user and returns a response/notification to the user’s screen.
Steps to reproduce the solution
To reproduce the solution: