Major Russian Bank

Overview

A Russian bank operating in Europe and Asia was dissatisfied with its current rules based anti-fraud setup. As a major bank providing financial services, it is prone to attacks from cybercriminals, particularly social engineering fraud. The bank therefore required an effective solution to decrease fraud rates with a response time in no more than 500 milliseconds.

The bank also sought a solution that would seamlessly integrate with strict Russian Personal Data Law and Localization requirements that do not permit the processing of bank data outside of the Russian Federation.


Challenges

Social Engineering Fraud
Social Engineering Fraud
One of the most popular techniques deployed by fraudsters. They aim to manipulate victims to divulge their credentials either through phishing, vishing or SMiShing (to install malware) or even gain direct access to their PCs via remote desktop protocols. As fraudsters can hide behind the 'real' identity of a person who may not even be aware of fraud being performed in their name, financial institutions require detailed profiling to recognize if they are dealing with a regular user or fraudsters hiding behind a cover.
Compliance with Russian data protection legislation
Compliance with Russian data protection legislation
Russian data protection laws are very strict, prohibiting the processing of customer’s personal details outside of Russian territory. The bank required that we could effectively deal with fraud, while being fully compliant with national law.

Solution

Using an initial portion of 500,000 unique users on the bank’s mobile app (Android and iOS) and processing over 80 mln transactions on a monthly basis, Nethone’s solution was able to detect 71% instances of fraud against strict requirements about how much traffic we could refuse. Our results included anomalies and suspicious behaviors indicative of potential fraud. Some key takeaways:

  • Fraudsters were frequently restoring factory settings before fraud occurred (difference between total space and free space on a device).
  • Most fraud attempts came from the iOS platform (84%).
  • Fraudulent transactions were statistically of higher value.

Although the data is based on a sample of data for a proof of concept (PoC) demonstration, Nethone’s solution had the potential to limit transaction rejection rates to 0.028% (against a strict bank benchmark of less than 1%). Our advanced solution is able to effortlessly collect over 5,000 pieces of digital fingerprinting data and scan behavioral biometrics, all backed up by advanced machine learning (ML) models on both mobile and desktop platforms.

After analyzing data in real time and quietly in the background of each user browser session, we can confirm (with median response time of 500ms) if a user was genuine or a potential fraudster. In this case, we were able to block numerous fraud attempts, many of which were of high value, originating from only a handful of users connecting through numerous IP addresses. All fraud pattern data is provided in real-time and can be analysed in Nethone’s easy to use control panel, providing the customer with valuable business insights.

Nethone’s advanced solution allows for seamless integration with the EU’s GDPR, eliminating the risk of fines through non-compliance of implementation. As the GDPR is one of the world’s toughest privacy and security laws, we could adapt Nethone’s tools to work within Russian law and easily fulfil the bank’s requirement despite processing data on servers within the EU. We are therefore able to adhere to GDPR standards within the EU and adjust to national law requirements around the world.

Results

0%
of fraud attempts detected in the sample traffic
0ms
response time, no negative impact on UX and website loading speed
0%
recorded false-positives, once processed by our logic set-up

Additionally, the bank appreciated how clearly collected data was presented and how easily they can navigate through Nethone's API responses.


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