Solventa Leverages SEON’s Machine Learning to Reduce Fraudulent Transactions by 25%
Solventa is the leading Fintech provider of immediate loans in Colombia. The company provides loans for individuals and SMEs in minutes, facilitating greater financial inclusion. At Solventa, credit isn’t something that should be inaccessible. Rather, they think of it as a benefit that everyone should have access to, anywhere. With this in mind, their straightforward and effective lending process helps save users money and time in the US, Colombia, and Peru.
For Solventa and other companies in the consumer lending sector, fraud has a sadly widespread impact. Fraudsters are constantly attempting to steal IDs and supplant or impersonate them for their own benefit. Other bad actors will use personal information in order to receive a loan that they will not pay back.
Therefore, Solventa needed a solution to identify potential fraudsters, without adding unnecessary friction and thus maintaining their rapid loan disbursements – a key factor to their service. Lucrecia Vera, partner at Solventa, stated:
Our mission is to provide credit to all legitimate customers we are able to, and we aim to do this fast, often in under 9 minutes, so we have to make sure we are doing our due diligence and doing it as quickly as possible. We were using mostly manual checks such as cumbersome ID validations in public databases, phone calls, and security profiles based on highly qualitative data, but we were unsatisfied with the time and resources required.
It was imperative that Solventa implement comprehensive checks while also speeding up the customer experience. This is where Solventa found SEON to be the best fit. By implementing SEON’s rapid real-time API module to check phone, email, and IP addresses, their fraud team had an in-depth risk scoring system to apply to their customers, immediately opting them in, or to the review stage if the likelihood of fraud was high.
Lucrecia further commented:
SEON’s implementation resulted in a 25% drop in fraudulent transactions, while also showing a 15% increase in the effectiveness of the machine learning models, enabling better overall fraud detection. This immediately equated to savings on costly biometric and ID validations, fewer portfolio losses, and increased productivity in terms of approvals.
In her final comments on the partnership with SEON, Lucrecia mentioned the great collaboration with SEON’s customer support team:
We are delighted with the timely turnarounds, quick responses, and effective problem-solving skills of all the analysts/staff working on Solventa’s account.
For more information on Solventa, please visit www.solventa.co
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