Cyber Fraud in the logistics sector is on the rise in India due to a lack of digital literacy among end users which is why awareness of digital automation is beneficial to detecting cyber crimes and frauds.
In the list of “sectors most affected by cybercrime worldwide,” the logistics sector comes in at number two. According to a report by Infosys, 38% of logistics organizations had unanswered questions about data security and privacy.
Although logistics service providers (LSPs) are sometimes referred to as intermediates, many of them are now actively engaged in the industry’s fight against fraud and cybercrime.
How Can Payment Fraud Prevention Help?
We can check the cardholder’s information against their online social profile to verify if it matches. It assists in extracting more information like a profile photo, full name, biography, etc.
Phone evaluation: The same can be done with phone numbers to get a better understanding of who you’re working with. Is it a landline or a mobile device? Are there any close-by carriers to the shipment address? Do they use a throwaway phone number?
IP analysis: In addition to determining location, you can determine whether a VPN, proxy, or emulator is being used by the user to cloak their connection.
Email analysis: A single piece of information, like a phone number or email address, might disclose a wealth of information. Was it made using a shady domain (a free or temporary address)? Is the verification procedure difficult? Has it been mentioned in any thefts of data? Learn so much about lookup tools for reverse email searches here.
How Can Online Payment Fraud Be Prevented For Transporters On The Vahak App?
To determine whether a user is fraudulent or not, Vahak relies on methods such as whether the user has been reported of fraudulent activity by other Vahak users or if the user is behaving suspiciously on the app. In addition to these traditional approaches, it has developed a predictive model based on Machine Learning algorithms that predicts a user’s likelihood of committing fraud. The higher a user’s probability score, the more likely they are to engage in fraudulent behaviour.
Model Innovation for AI-Assisted Fraud Detection and Prevention:
Vahak has built a fraud detection system based on user behaviour, their profile, engagement pattern, route-related features, and data on how many users have reported or given low ratings to such profiles. This system predicts the Probability Score for a user to commit fraud by using classification algorithms such as Logistic Regression and Random Forest, as well as the independent variables discussed above.
The following proactive measures to combat fraud/fake users have been identified:
The platform threshold was established to require users with a fraud score of more than 0.8 to complete a KYC mandate, and suspicious users in the marketplace get de-boosted based on the fraud score.
The latest version of the model is able to predict 22% of fraudsters, which resulted in higher call quality from customers for load and truck bookings, improving marketplace quality.
Collection and Preparation of Datasets
The redshift database on AWS was used for data collection and preparation. The platform that houses the enterprise data warehouse is Redshift. Using AWS native tools such as DMS and Kinesis, data from the production OLTP system is streamed in real-time to Redshift.
A number of transformations were performed in Redshift on top of the profile attributes and usage information to generate multiple features for the fraud model.
Use of Dependent and Independent Variables
The independent variables are divided into three categories:
Users’ profiles on the platform (such as the number of days spent on Vahak, whether the user is verified or not, the average rating of the user, and so on).
Engagement on the platform (such as the number of views, bid to total load ratio, and so on).
Route particular (like source and destination state of the route).
Fraud is the dependent variable. The data scientists assigned a value of 0 to users who were not identified as fraudsters by Vahak and a value of 1 to users who were identified as fraudsters.
Conclusion
The advantages of fraud detection and prevention ultimately come down to one crucial factor: increased revenue. Fraud can cost you a lot of money if you don’t identify and stop it. Boosting your sales and expanding your business will increase if you prioritize fraud detection and prevention.
Since avoiding fraud is considerably simpler than recovering damages after fraud has been perpetrated, you can download the Vahak online platform which is beneficial to you in avoiding such damages and frauds.
Leave a Reply