> ## Documentation Index > Fetch the complete documentation index at: https://developers.investorlift.com/llms.txt > Use this file to discover all available pages before exploring further. # The Lender ranking row > One lender ranked market-wide or in a ZIP, city, county or area around a point: its rank, window activity, open book and typical loan. Early access: while the developer tier is in beta, the API serves this route to Investorlift's team and trusted partners. Investorlift will restrict the route further before it opens to every key. One row of [`GET /v1/lenders`](/api-reference/endpoints/lenders-list). `lender` is the identity: the id, the display name, the class and the hard-money flag of [the Lender object](/api-reference/objects/lender). The API measures the rest over the window `period` names, by default the 24 months that end on `as_of`. It measures them market-wide, inside the one ZIP, city or county the request named, or inside the geometry it drew. The same lender seen from the other side, one row per place it ranks in, is [the ranking bucket](/api-reference/objects/lender-ranking-bucket). ## Read a row * **`rank` is the row's position in this list**, under its sort and filters, and it continues across pages. The default list hides persons and government lenders, so it differs from the profile's `rankings.rank_24m`, which counts every lender. * **`n` is every instrument of any kind** recorded in the window (purchase money, refinance, HELOC, construction), counted once across the open-lien and recorded-history tables. With `position=1` it counts first liens alone. With `product=` it counts the named products alone. A `GOVERNMENT` row counts the insurance claims and partial-claim seconds recorded under the agency's name, not originations. * **`share` is `n` over every lender's instruments** in the same window and place. The denominator includes persons below the gate and placeholders. It is null under `position=1` or `product=`, because no per-product denominator exists. It stays the share of the whole market under `hard_money=true`. The profile's `rankings.share_of_hard_money_24m` is the share among hard-money lenders. * `volume` sums the priced instruments. It counts a blanket loan once, that is, one loan recorded across 5 or more parcels. It leaves out amounts above \$5,000,000: such an amount is a facility amount the file records on every parcel it covers. `n_unpriced` counts the unpriced rest. It is null inside a place, because the API does not measure it there. * `n_open_liens`, `open_balance`, `n_parcels` and `median_amount` are market-wide whatever the place: the lender's book, not the place's share of it. * `last_recorded_on` is inside the place when the request names one. The API measures recency against `recordings_through`, which is fourteen days before `as_of`. * `n_purchase_money`, `n_investor` and `n_deals_financed` (since 0.16.0) read the deed link. Of `n`, the first is the instruments that financed a purchase: a priced deed on the parcel in the 45 days up to the recording. The second is those whose borrower resolves to a registered investor, and both are inside the place when the request names one. The third is market-wide only: the investor deals whose purchase loan is this lender's in the window, null inside a place. All three are null where the market has no deed link (`purchase_measured` false on the profile). `purpose=purchase` makes the first of them `n`, and `sort=purchase_desc` orders by it. * **`share_by_volume`** (since 0.19.0) is the lender's `volume` over every lender's volume in the same window and place. It uses the same amount rule: a blanket loan once, amounts above \$5,000,000 left out. It is null under `position`, `product` or `purpose` and under a geometry. It is also null where the place's volume is 0. * **`n_borrowers`** (since 0.19.0) is the lender's borrowers in the window. Market-wide it is the profile's `borrowers.n_borrowers_24m`. Inside a place it is the distinct borrower keys on its instruments there. It is null under a geometry, and while the market has no borrower match (`borrowers_measured` false). * **`in_geometry`** (since 0.19.0) is null without a geometry. With one it says what the geometry became: `res` is the resolution, 8. `n_cells` is the H3 cells whose centre lies inside the geometry, about a third of a square mile each. So the edge is a hex boundary and not the circle. `n_cells_lent` is how many of them carry this lender in the window. * Under a geometry `n`, `volume`, the first-lien and product counts, `n_purchase_money`, `n_investor` and `last_recorded_on` are sums and maxima over those cells. `share`, `share_by_volume`, `n_unpriced`, `n_deals_financed` and `n_borrowers` are null, because the API does not measure them per geometry. The history captures about one open loan in five. So a bridge lender, whose loans are short and paid off before the next slice, ranks below its real activity. The bias is the same on every row. So the order among hard-money lenders holds better than a comparison between a hard-money lender and a bank. ## Related topics - [Rank the lenders of a market or a place](/api-reference/endpoints/lenders-list.md) - [API reference](/api-reference/introduction.md) - [Changelog](/changelog.md) - [Prompts and chaining](/mcp/workflows.md) - [The Lender ranking bucket](/api-reference/objects/lender-ranking-bucket.md)