Our customer-centric strategy is delivered through simple, smart, personalized banking services. ThreatMetrix aligns with this approach by helping us build trust across the entire customer life cycle, reducing unnecessary interventions.
—Head of Fraud Risk
This bank is one of the largest banks in the Middle-East and provides various banking products including corporate banking, personal banking, loans and credit cards. With a customer-centric approach, this bank has a vision to be loved for its passion and excellence, doubling net profit over the next 4 years.
In a landscape of rising fraud levels and a complex user base, the bank strives to make the online banking experience as frictionless as possible.
With ThreatMetrix, this bank can:
- Achieve the perfect balance between minimizing customer friction while more accurately detecting genuine high-risk behavior
- Build user connections across multiple data sources to more effectively detect fraud
- Tap in to the crowd-sourced intelligence from over 20 billion annual global transactions
ThreatMetrix forms a core component of our ongoing strategy. We recently launched our bank. Now banking app and this was developed from day one with the ThreatMetrix solution in place
—Head of Fraud Risk
Two of this bank’s core values include simplicity and innovation. Championing these values in a climate of rising fraud, a diverse user base and a huge proliferation in online interactions has created a number of key challenges. The bank wanted to offer a market-leading mobile banking app that provided users with banking freedom; creating easy, fun and personalized interactions without unnecessary intervention.
At the same time the Gulf region is seeing a huge rise in fraud, with 90% of executives saying their company has experienced a cyber-attack in the last 12 months. To add to this complexity, UAE has an incredibly diverse population of highly-mobile, sometime disparate workers. This has created a complexity in user behavior that incorporates high-frequency travelers, customers making high value payments and people using TOR both legally and for nefarious reasons.
The Power of Global Shared Intelligence to Streamline the User Experience
The best way to tackle complex, global cybercrime is using the power of a global shared network. The ThreatMetrix Digital Identity Network collects and processes global shared intelligence from millions of daily consumer interactions including logins, payments, and new account applications. Using this information, ThreatMetrix creates a unique digital identity for each user by analyzing the myriad connections between devices, locations, and anonymized personal information. Behavior that deviates from this trusted digital identity can be accurately identified in real time, alerting the bank to potential fraud.
This green zone of trusted transactions now makes up the majority of events. The more users interact with us, the more we learn about their behaviors, and the more trust we can associate with them. This all has a profound effect on their online experience
—Head of Fraud Risk
Key Features of the ThreatMetrix / Bank Partnership
- ThreatMetrix Smart ID identifies returning users that wipe cookies, use private browsing, and change other parameters to bypass device fingerprinting. This improves returning user detection and reduces false positives. Derived from the analysis of many browsers, plugin, and TCP/IP connection attributes, Smart ID generates a confidence score that detects multiple fraudulent account registrations or log in attempts.
- Deep connection analysis technologies give the bank a clearer view of suspicious events. Fraudsters often attempt to hide behind location and identity cloaking services such as hidden proxies, VPNs and the TOR browser. With Proxy piercing technology, ThreatMetrix examines TCP / IP packet header information to expose both the Proxy IP address and True IP address. These techniques help the bank gain detailed network level signals for more accurate decision making.
- ThreatMetrix behavioral analytics, called Smart Rules, allows the bank to better model complex user behavior to reduce false positives and better detect fraud. As well as behavior, location and age variables, Smart Rules can incorporate expression variables which allow attributes and variables from a specific transaction to be combined into a mathematical expression. In addition, variables, logical expressions, static values, and attributes can be combined using Expression Condition Rules and used in policies for complex fraud decisioning.