Research shows that multi-accounting increases fraud risks by 30–60%, while financial institutions' losses from secondary fraud can reach 15–20% of the credit portfolio turnover. Even managing already verified clients after the initial application leads to significant operational losses. Despite lower fraud rates among such clients, the volume of returning customers can generate losses exceeding those from new customers.
What’s new in JuicyID v16?
In the latest version of JuicyID, we have made significant changes to 15 variables and introduced 20 new ones, enhancing protection not only for personal accounts and mobile applications but also for preventing credit shopping and multi-accounting among verified clients. These risks, along with remote access and social engineering, account for the majority of losses among repeat customers.
JuicyID now analyzes not only primary behavioral anomalies but also secondary signals, such as attempts to bypass restrictions, advanced signs of rooting, and remote access. This enables early detection of repeated fraud attempts.
Key Updates in JuicyID v16
- 12 new variables for identifying secondary fraud.
- 2 new variables for detecting randomization scenarios.
- 3 new variables for detecting network anomalies.
- Enhanced rooting tests and bot detection.
- Significantly improved index informativeness.
The updated IDX1, IDX5, and IDX9 indices allow for a deeper analysis of fraud risks by assessing behavioral anomalies and fraud likelihood at different stages of the credit cycle.
IDX1 – Identifies primary fraud risks by analyzing key anomalies. Its effectiveness depends on the credit cycle stage where it is applied—whether for initial screening or during repeat applications.
IDX5 – Assesses device quality, detecting signs of reliability or potential fraud. It helps determine whether a device is stable and aligns with normal user behavior.
IDX9 – Analyzes software and device-related risks, including proxy detection, use of high-risk applications (gambling, micro-lending, unofficial services), and suspicious actions such as factory resets, frequent reboots, and other fraud indicators.
How does JuicyID combat secondary fraud?
Filtering fraudsters at the entry point is only the first step. They may return, test the system, and look for vulnerabilities.
Common fraud scenarios observed across different regions:
- Credit Shopping – Verified users, facing financial difficulties (often due to social engineering), attempt to take out as many loans as possible in a short period, leading to a sharp rise in default rates.
- Account Takeover – Fraudsters gain access to personal accounts through password leaks, phishing, and social engineering. Using different devices and randomizers, they withdraw funds or take out loans.
- Use of "Dormant" Accounts – Fraudsters may exploit long-inactive phone numbers to access accounts if they have not been updated for an extended period.
These scenarios confirm that previously approved clients require additional verification.
JuicyID helps detect recurring fraud patterns, track behavioral trends, and identify fraud at later stages, where traditional methods are no longer effective.
JuicyID is reaching a new level
The enhanced JuicyID is already being used in multiple countries, helping to uncover hidden risks and strengthen financial platform security.
The product delivers real results: it not only effectively blocks fraudsters at the entry point but also prevents repeat attacks—critical for fintech, marketplaces, and classifieds.
For example, in eight years of successful collaboration with a leading anti-fraud solutions provider, a top international fintech group implemented JuicyID to reduce risks in repeat lending. The new technology enabled the detection of additional risk markers, including unusual language usage, virtual machines, and non-standard devices. As a result, the company reduced early-stage repeat loan risks by several percentage points, demonstrating JuicyID’s effectiveness in combating secondary fraud.
One study on JuicyID’s applicability revealed a 30%+ reduction in overall losses among verified clients.
Analysis showed that traditional security measures, such as 2FA+ and standard risk assessment procedures, are insufficient to fully neutralize fraudulent schemes. The key loss structure highlighted:
Based on the study, additional protection measures were proposed:
- Filtering technical fraud using identified stop-markers.
- Reducing social fraud through stricter repeat application approval processes and multi-accounting monitoring (Device ID analysis).
- Optimizing credit risk by incorporating additional behavioral data.
JuicyID continues to evolve, offering fintech companies and banks a new level of fraud protection. Its innovative approach—based on hidden digital marker analysis and behavioral insights—not only effectively detects fraudsters at the entry stage but also prevents complex secondary fraud schemes. By combining deep analytics, alternative data processing, and adaptive algorithms, JuicyID provides a powerful tool against digital threats, helping companies optimize risk models, minimize losses, and enhance resilience against fraud attacks.