Trade Ledger and Wiserfunding today announced a partnership that allows banks and alternative finance providers to more accurately assess their mid-market commercial customers for secured and unsecured credit. Trade Ledger, the specialist mid-market commercial Lending-as-a-Service platform, confirmed that Wiserfunding’s leading business credit score, the SME Z-Score, would be made available within both their loan origination and management portals, to help their rapidly growing client base access the fastest and most precise business credit score available.
Roger Vincent, Chief Innovation Officer at Trade Ledger said, “Inaccurate and slow credit risk assessment, for SME commercial loan requests is one of the major reasons that over 50% loans are currently declined by financial institutions (FIs). This has created a £1.2 trillion global credit gap and is stunting economic growth and social mobility.”
Roger continues “To address this issue risk assessments must be exceptionally accurate and utilise unstructured, as well as structured, big data inputs and machine learning techniques in this continually evolving environment. WiserFunding, uniquely does just that, but offers the reassurance of the best of academia and its established client base, while drastically reducing the time taken to underwrite counterparties.”
Gabriele Sabato, CEO of Wiserfunding highlighted that “Trade Ledger were the perfect fit for our credit risk assessment solution. As one of the fastest growing lending technology providers in the world, their data-driven approach to commercial lending provides the ideal platform for underwriting and portfolio management teams to accelerate their risk management capabilities. With Wiserfunding’s SME Z-Score embedded within the platform, these institutions can now start to think about more advanced segmentation, automation and straight-through-processing, advancing the accuracy to record levels and profiting from this hugely underserved market.”
The new global partnership will aim to target mainly mid-market lenders and banks, who have traditionally used manual risks assessments to identify high-risk customers. The score is tailored specifically for SMEs with revenue between £500K and £200M. On average, the score delivers between 83% and 95% default prediction accuracy, 20-30% higher than other than other industry benchmarks in this space.