Since 2013, Robocash has been providing automated financial services in the field of alternative lending and marketplace funding. Their cutting-edge technology uses machine learning to deliver the best investor returns, and now covers 8 key markets worldwide. As one of the most mature P2P lending platforms, they earned $223.6M in revenue in 2019, showing a nearly 100% annual growth rate.
Robocash’s Fraud Challenges
We are proud to provide loans to unbanked and underbanked markets, however, it usually means extra vigilance and costly manual reviews as we cannot always access valid credit information.
Robocash is no stranger to fraudsters who use synthetic IDs to open borrower accounts. But their latest challenge was in creating an efficient digital credit check. The company operates in notoriously risky markets, and the lack of valid data often makes it difficult to trust borrowers.
“We are proud to provide loans to unbanked and underbanked markets,” says Alexey Pogrebnyak, Robocash’s Chief Risk Officer for the APAC region. “However, it usually means extra vigilance and costly manual reviews as we cannot always access valid credit information”.
This was particularly true of phone numbers and email addresses, which required manual validation by the risk team. “We had to check telephone numbers directly with the telecom operators,” Alexey says. “Or we had to ring customers ourselves, and use other services, none of which were fast or automated enough for our large scale operations.”
SEON Integrates Smoothly, Provides Valuable ROI
Our company is always looking for solutions to optimise costs, and using SEON was more economically feasible in comparison with other services.
Alexey and his team clearly needed a solution to automate manual reviews dealing with phone numbers and email addresses. But it also had to be cost-effective, which is why they settled on SEON’s lightweight email and phone analysis modules.
“Our company is always looking for solutions to optimise costs,” says Alexey. “We are constantly testing new services, and in this regard, SEON was more economically feasible in comparison with other services.”
After calculating their potential ROI, it was time to deploy the tools on top of their current fraud detection systems, via API. “Negotiations and implementation were extremely successful,” Alexey says. “The API documentation is clear, and the SEON team quickly answered all our questions, providing excellent support with any of our issues.”
SEON’s Lightweight Data Enrichment Completes The Risk Models
SEON is now part of our comprehensive anti-fraud solution, And according to the results of the implementation, the number of fraud cases has significantly decreased.
Thanks to SEON’s email and phone data enrichment tools, Robocash can automate manual reviews and get more precise information about potential defaulting customers. “SEON is now part of our comprehensive anti-fraud solution,” Alexey explains. “And according to the results of the implementation, the number of fraud cases has significantly decreased.”
Because more data means better insights, the company can now improve their risk model. “The new data expands our data model, and helps us distinguish between ordinary customers by risk level,” Alexey says. “We can also highlight the fraud segment, all in the most cost effective way for the company.”
Robocash can now onboard more borrowers, safe in the knowledge that SEON’s data enrichment modules will:
- Reduce the amount of manual reviews
- Help segment customers by risk level
- Provide valuable data without adding customer friction
- Block potential defaulting customers
Best of all, Alexey knows the company can count on SEON’s team for any fraud-related help. “The communication with SEON has been excellent,” he says. “From implementation to general support, their responsiveness is great, and an excellent reason to stick with them in the future.”
To see how SEON can help your organisation reduce fraud, check out our products.
Chief Risk Officer