How JuicyScore Drives Fintech Growth in Mexico

The rapid development of digital finance in Mexico has made the market especially attractive for innovative players. However, new companies—especially those operating for less than a year—struggle to compete with more established players. Many lack a mature antifraud infrastructure, and the fast-changing market demands rapid adaptation. To stay competitive and ensure sustainable growth, it’s critical to identify high-risk segments early and minimize losses during business scaling.

JuicyScore has become a key tool for several fintech companies in Mexico processing 15,000 to 30,000 applications per month. It enabled them to identify weaknesses in incoming traffic and rapidly build an effective risk assessment system, including high-risk traffic filtering — without complex or costly in-house development.

High Volume – Low Transparency

A major challenge was unstable traffic quality. A significant portion of applications came from foreign IPs and masked network setups, including VPNs and proxies. This type of traffic exceeded typical market levels by 50–300%, and the device/network configurations signaled attempts to obscure real digital footprints, which impacts both risk levels and collection prospects.

Device quality scores — based on JuicyScore’s proprietary methodology — were 40% lower than the market average. This directly affects credit risk, re-loan conversion, and the ability to achieve sustainable unit economics.

Technical Anomalies & Repetitive Traffic

The unstable traffic flow also featured a high share of technical anomalies, emulators, and randomizers. Reuse of devices and IP addresses was 50%+ higher than the market norm.

Additionally, many loan applications were submitted from identical digital environments — often used across multiple lenders — but rarely led to actual loan approvals. This indicated the presence of low-quality, recycled traffic.

Solution: Risk Segmentation with JuicyScore

JuicyScore helped clients implement precise filtering of high-risk applications using a combination of behavioral and technical attributes:

• Thresholds combining behavioral markers and low-quality device indicators
• Flags for poor network infrastructure paired with suspicious device behavior
• Session clones, browser anomalies, language settings
• High volume of short-term loan requests + volatile device parameters
• Battery behavior markers
• Risky IP usage types
• Key variables included frequency metrics, battery behavior analytics, and IP type profiling.

Results: Risk Control & Improved Efficiency

JuicyScore enabled young alt-lending companies to significantly improve the quality of incoming traffic and gain better control over early-stage risks.

Outcomes included: detection of up to 5% of loans with 2x+ elevated risk. This allowed clients to reduce portfolio risk, increase re-loan conversion, improve unit economics for new borrowers, and scale operations without proportional growth in losses.

Portfolio analysis over time showed:

• Higher average revenue per borrower due to lower default rates
• More flexible product targeting based on behavioral and technical segmentation

JuicyScore proved to be a lightweight yet powerful antifraud solution that helped young lenders build robust risk strategies without heavy infrastructure investments — strengthening their market position in a competitive environment.