Consumers increasingly question why their credit scores sometimes seem inexplicably low. A new Financial Times analysis argues the underlying model, built on decades‑old algorithms, treats timely payments and high balances alike, penalising both the cautious saver and the heavily indebted borrower. By aggregating data from dozens of lenders, the system produces a single number that often masks the nuances of individual credit behaviour.

The piece highlights three structural flaws. First, the weight given to credit utilisation ignores the fact that many borrowers keep low balances deliberately, yet are punished for not using available credit. Second, the absence of real‑time updates means recent repayment improvements can take months to reflect. Third, opaque scoring formulas prevent consumers from correcting errors or understanding which behaviours drive their rating.

Investors watch the credit‑scoring market closely because the sector underpins billions in loan underwriting and fintech valuation. Any regulatory push for greater transparency could reshape revenue models for the few firms that dominate the space, potentially opening the door for challenger platforms that offer alternative, behavior‑based assessments. As it stands, the entrenched system continues to dictate borrowing costs for millions of households.