The funding will facilitate the development of their proprietary artificial intelligence (AI) solution designed to support instant payments between large corporates and SMEs.

The funding round is led by company builder, Hambro Perks alongside Founders Factory and high net worth angel investors with extensive networks in high profile multinationals.

Today, three out of five small suppliers are paid late by large corporate buyers. As a result, SMEs are forced to take out expensive, short term credit from banks to cover their cash flow difficulties, ultimately driving up the price of their products. In the UK alone, 50,000 SMEs go bankrupt as a result of late payments each year1.

How it works

As soon as the invoice is issued, Previse uses advanced AI and hundreds of millions of data points to score the likelihood that a corporate buyer will ultimately pay a supplier’s invoice. Previse provides the score to funders, principally banks and asset managers, which pay the supplier instantly on the buyer’s behalf. In exchange, suppliers offer a small discount on their invoices.

This results in reduced transaction costs for buyers; improved working capital for suppliers and a safe, attractive new asset class for funders. Eliminating late payments would boost the UK economy significantly.1

Previse’s co-founder and CEO Paul Christensen, who was previously Global Co-head of Goldman Sachs' Principal Strategic Investments team; said: “SMEs are the backbone of the world economy, generating the majority of growth, employment and innovation. Yet, most of them are consistently paid late by corporate buyers. It is an unsustainable position which damages the entire economy.

“Previse’s AI technology ensures we no longer have to accept this situation. Instant, frictionless and efficient payments can become the new standard for B2B payments. The prize is 50,000 more small businesses kept open in the UK alone, corporates able to exceed their obligations to suppliers and a new £2.4 trillion global market for funders.” 2

Previse’s Chief Data Scientist and co-founder Philipp Schoenbucher said: “Payment decisions are a perfect candidate to apply machine learning. Our advanced proprietary machine learning algorithms were developed using data sets of multiple billion dollars of corporate spending, building upon state of the art binary classifiers and highly innovative domain-specific feature engineering methods.”