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Payroll data fintech Teal closes £1.4m pre-seed round

Teal, a fintech startup building a payroll data platform for the credit industry, has raised £1.4m in a pre-seed funding round.

The London-based group was founded to address the problems with traditional processes for credit checks for lending.

Teal has developed tools to offer firms real-time income and employment data, rather than requiring the use of potentially out-of-date static credit scores and time-consuming manual payslip checks.

“Traditional credit scoring is broken, relying too heavily on outdated processes that fail to deliver for lenders or borrowers,” said Michael Hart, co-founder and chief executive of Teal.

“By being able to securely and accurately share income data, users can unlock access to credit that works for them. This investment is a vote of confidence in our mission to build better infrastructure for financial access and give individuals more control over their financial data.”

The funding round was led by Passion Capital and included backing from ACF Investors, K Fund and a handful of industry angels, including from fintech groups Plaid and Checkout.com.

“Teal’s payroll infrastructure is laying the foundation for a new wave of fintech products, powered by source-level payroll data,” said Will Orde, a partner at Passion Capital.

“It is exactly what the credit ecosystem needs right now, and we are excited to back another great company from the UK’s thriving fintech scene.”

The new funding will support Teal’s goal of expanding its data infrastructure beyond payroll to incorporate additional income and financial sources for a more complete view of borrowers.

Tim Mills, managing partner at ACF Investors, added: “By anchoring credit decisions in verified payroll data, Teal is helping reshape how affordability is measured, how loans are repaid, and ultimately, how people access credit.

“We are pleased to be backing Teal through its next phase of growth.”

The post Payroll data fintech Teal closes £1.4m pre-seed round appeared first on UKTN.

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