Finqle case

Predictive Flagging Engine for fast-growing factoring start-up

The Business – Finqle offers financial factoring solutions for SMEs. They believe factoring does not have to be expensive and complicated. Clients can upload their invoices to the online platform, then Finqle buys the invoice and pays within 24 hours. They take the credit risk and take care of debtor management on every invoice they purchase. This service is called American Factoring.

The Challenge – Since Finqle carries all the risks, they want to work towards predictive flagging to early detect fraud and anomalies in payments by using Machine Learning. However, before a predictive model like that can be used in production, a certain data maturity level should be reached.

The Solution – Before starting to build solutions, we gain insights in the whole process and data maturity of Finqle with our thorough ML audit. Once we established a plan of action, we go through with building scalable and future-proof solutions. We work use-case driven, making sure Finqle has the right data and data infrastructure in place to kick-start data science. Enjins helps Finqle to connect to all relevant data sources and become AI-ready for smarter prediction of fraud & anomalies in payments and thus reduce risk.

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