Machine scoring in lending refers to the use of automated algorithms or computer-based models to assess the creditworthiness of loan applicants. It involves advanced analytics and machine learning techniques to evaluate various data points and generate a credit score or risk profile for each borrower.
Traditional lending processes often rely on manual underwriting, where loan officers or credit analysts manually review an applicant's financials, credit history, and other details to make a lending decision. Machine scoring streamlines and automates this by analyzing large volumes of data rapidly, aiming to produce more objective and consistent results.
Often, a loan broker may claim they can negotiate better interest rates on your behalf — but we question how that’s possible when many lenders now use machine-driven scoring models to determine interest rates.
Unless you're a large enterprise or a high-net-worth individual, you're unlikely to need financing structured under a discretionary lending model, which is where such negotiation may be entertained. Most borrowers will fall under program lending, where rates and terms are algorithmically pre-determined even if the credit decision is made by a human. See Program Lending vs Discretionary Lending for more.