August 14, 2018
Intrum Justitia automates fraud detection, reducing manual review rates and customer friction
Intrum Justitia has more than 75,000 clients worldwide with local and cross-border credit management support. It offers credit information, sales ledger services and debt management, seeking to maximize cash flow and profitability for its customers. However, Intrum Justitia needed a more effective, automated fraud detection solution to protect its customers from high-risk or fraudulent credit decisions.
With ThreatMetrix, Intrum Justitia was able to streamline its fraud detection process, offering more accurate risk assessments, reducing overall operational costs and fraud losses.
As organized fraud attacks continue to grow worldwide, Intrum Justitia’s customers were exposed to greater risk from fraud syndicates and individuals seeking to capitalize on fraudulent credit. Although the company’s manual system could detect fraud patterns, it wasn’t able to keep pace with the volume of attacks.
Intrum Justitia offers its customers the opportunity to sell online via invoice, providing credit decisioning with debt purchase and payment guarantee. It was therefore imperative that it implemented a more robust solution to prevent fraudsters slipping through the net. The key types of fraud it was experiencing were:
- Fraudsters using stolen identities
- Fraudsters using synthetic identities
- Fraud rings placing multiple orders
Leveraging Digital Identity Intelligence to Detect Fraudulent Transactions in Real Time
The ThreatMetrix solution is underpinned by the Digital Identity Network, which harnesses 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.
Digital Identities are created by combining the following key intelligence:
- Device profiling – Device identification, device health and application integrity, as well as detection of location cloaking or spoofing, (proxies, VPNs and the TOR browser).
- Threat intelligence – Harnessing point-in-time detection of malware, Remote Access Trojans (RATs), automated bot attacks, session hijacking and phished accounts, then combining with global threat information such as known fraudsters and botnet participation.
- Identity data – Incorporating anonymized, non-regulated personal information such as user name, email address and more.
- Behavior analytics – Defining a pattern of trusted user behavior by combining identity and transactional metadata with device identifiers, connection and location characteristics. Every event can be analyzed in the context of this behavior pattern and historic context globally.
Securing Measurable Results
Intrum Justitia could authenticate every credit decision against this trusted and unique online digital identity, checking whether credentials of the applicant correlated with anonymized information held by the Network and providing its customers with accurate and constantly updated risk scores. This had the following key benefits:
- Debt collection portfolios performed better due to fewer instances of fraud
- Automated detection meant that it no longer had to stop orders manually after a false approval
- Operational costs fell due to a more streamlined approach
- Instances of identity theft fell significantly
- Intrum Justitia took advantage of the flexibility of the ThreatMetrix policy engine to customize risk scores to suit customer requirements.
- Following successful deployment, Intrum Justitia wants to extend the ThreatMetrix solution to all high-risk payment guarantee customers.