Average proximal property value in lending decisions.
Average proximal property value gives average value of comparable properties in the postcode, published modelled with 99.24% coverage across England. Where modelled, review the current dictionary evidence and validate the estimate against your own reference cohort. Attribution and refresh period are in the dictionary.
Pretira publishes average proximal property value modelled at 99.24% coverage across England, refreshed monthly, with declared and modelled kept separate.
IF average_proximal_property_value * max_ltv >= loan_amount AND property_value_confidence = HIGH -> decide on dataThe rule is a pattern, not a policy - you set the operator and the cut-off to your own appetite. On the sample record this field returns [], the kind of value a rule like the above turns into a data decision or an escalation.
Decision-in-principle triage - a view at quote-flow pace, before an adviser picks up the call.
Second-value arbitration - run alongside your incumbent AVM and lend where the two views agree.
LTV banding across the book, and portfolio revaluation context between physical inspections.
Modelled from sold-price evidence and property attributes. Any current dictionary test label is shown with its limitations; a lender evaluation supplies the cohort-specific error distribution. Refresh is monthly, rendered from the dictionary rather than assumed.
Class: Modelled · Refresh: Monthly · England: 99.24%
Three questions on this field.
Core tier. Routing rules on this page are illustrative patterns; coverage figures render from the dictionary. Dictionary: July 2026.
Review this field before you deploy it.
Start with a synthetic record or a controlled standard sample. We will show the field provenance, coverage and testing, then scope the production route.