Bankers, when queried about their primary concerns, often cite the persistent worry of fraud risk keeping them awake at night. Despite implementing various safeguards, the highly digitized world we live in makes fraud nearly unavoidable.

According to a 2022 Deloitte survey , there will be a likely increase in banking fraud in the coming years. Notably, the survey highlights that executives in the banking sector are most apprehensive about specific areas, including loan frauds (24%), mobile/internet banking fraud (14%), and identity/data theft (13%)

The industry average fraud rate in digital loans ranges from 0.4% to 1%. These figures represent users who intentionally provide inaccurate information to manipulate the system. 

At FinBox, we're redefining the fight against fraudulent activities with our revolutionary product, DeviceConnect (DC). As an in-built fraud scanner and underwriting tool, it checks for apps that could potentially indicate fraudulent activity like SMS editor, data editor, fake GPS apps, and it also checks for whether or not your phone was rooted recently. DeviceConnect’s fraud detection capabilities are based on these data points, alongside the triangulations, irregularities, and eccentricities in that data.

Unlike other fraud intelligence solutions that specialise in specific identifiers like IP addresses, fingerprints, or app data, DeviceConnect simplifies the process. With DC, you no longer need to integrate with multiple players for different identifiers. We capture everything at once, providing a holistic approach to fraud prevention

The highlight of DeviceConnect is its exceptional ability to capture 60% of fraud cases. Through sophisticated algorithms and cutting-edge technology, DC analyzes user data to generate multiple intelligence and insights. One key feature is the identification of clusters exhibiting the same mode of origination, such as multiple users applying for loans from the same device. Clusters are categorised by location, device, IP address, and SMS data.

DeviceConnect goes beyond traditional methods by matching the identity of the user to the device. This crucial step ensures that the applicant is who they claim to be, offering a robust layer of identity verification.

Our dedicated data science team has developed machine learning models that excel in identifying fraudulent behaviours over time. For example, DeviceConnect can flag attempts to manipulate location data by downloading apps that fake location. This proactive approach helps prevent fraudulent activities before they can impact your lending operations.

DeviceConnect empowers lenders with rule-based customisation options. If a user displays multiple pieces of evidence indicating fraud, such as the use of a fake GPS app, lenders can set their thresholds. Even in scenarios where users employ VPNs, DeviceConnect provides comprehensive information along with our interpretation, enabling lenders to make informed decisions.

Our fraud flag feature is an amalgamation of various rules and criteria. For instance, if a lender doesn’t want to use location as a fraud identifier,they  have the flexibility to customise their fraud flags, based on IP address for instance. DeviceConnect allows lenders to tailor fraud flags based on their lending policies and individual user consent, offering unparalleled flexibility in fraud prevention.

In conclusion, FinBox's DeviceConnect is not just a solution; it's a strategic advantage in the battle against digital loan fraud. With its ability to capture 60% of fraud attempts, all-encompassing intelligence, and customisable features, DeviceConnect is the partner you need to secure your lending operations in an ever-evolving digital landscape.

We’ve written a comprehensive guide on how FinBox fights fraud, read it here !

For more information on DeviceConnect, get in touch here .