How does your AI matching choose which lenders or brokers to introduce?

Our matching uses your declared profile (sector, turnover band, trading age, requested amount, use of funds, broad credit position) and compares it against each lender's published underwriting criteria. We do not run a credit search ourselves. We do not access your bank feed or your accounting data unless you grant explicit access. Matching is rule-based comparison against published lender criteria, not predictive scoring.

The match logic in plain language. Step 1, we filter the panel by hard eligibility: minimum trading age, minimum turnover, minimum facility size, sector inclusions and exclusions. Step 2, we rank the remaining panel by fit: lenders whose typical ticket range and product type best matches your stated need rise to the top. Step 3, we surface the top 1 to 3 matches, with a transparent reason for each (why they fit, what the product is, what their published rate range is, what their decision time is).

We disclose every commercial relationship that would otherwise bias the match. Where we receive a referral fee from a lender we route to, we say so on the lender review and on the disclosure section of how we are funded. Where two lenders are equally well-matched on the underwriting criteria, the order in which they are surfaced is alphabetical, not commercial.

We do not guarantee approval, the lowest available rate, or any specific lender's response. We do not match to brokers without your knowledge: every routing destination is named upfront. See are you a lender, broker or introducer and how does your AI matching process work for the operational version of this question, and our methodology page for the formal scoring framework.