Which metric each bar reports, AND what the bars are ranked by — the list is ordered by the measure you ask for, descending. Defaults to units, so an unqualified "top originators" means the busiest; pass volume for the biggest by dollars, or an average to rank by that average. Two things to know about the averages specifically. Buckets built from fewer than 5 documents are dropped from an average chart entirely, because a mean says nothing about how many transactions produced it and a single-transaction bucket would otherwise outrank real ones; no floor is applied to units or volume, where a lone large transaction is a legitimate top bar. And ranking a bucket list by a sub-aggregated average is approximate in the search engine — each shard contributes its own local top-N before they are merged — so treat the ordering of an average chart as indicative near the boundary rather than exact. Every bucket publishes its own count, so the sample size behind a value is never implicit.
Default"units"
Value in"volume" | "units" | "avgSalePrice" | "avgListPrice"
nmlsId?string
nmlsIds?array<string>
period?Period
Pre-aggregated period block. Rolling windows (last30Days, last60Days, last90Days, previousMonth, currentMonth) are NOT accepted here and return 400; they are supported on the loans, sales and market endpoints (list, count, breakdowns, analytics summary / time-series / chart) (see DatedPeriod).
Which of a loan's party roles make it this company's loan. loanCompany (default): the company named on the loan document — one company per loan. all: the company appears in ANY role — loan-document company, the originating LO's employer at time of loan, the LO's organization, broker, or funding lender; a loan matching several roles counts once. employer: the company employed the originating LO when the loan closed. broker: the company brokered the loan. lender: the company funded the loan. tpo: third-party origination — the company is the loan company or lender but did NOT employ the originating LO (the channel dimension's tpo bucket as a population; employer is its inHouse counterpart). Use all for a broker shop's full production — its loans are often recorded under the funding lender's name, so loanCompany undercounts it.
Dimension to group by. Most are the loan's own field (loanType, transactionType, state, …). lender groups on the normalized lender (label = display name, id = filter key). propertyType is the recorder's land-use code of the collateral (SFR single-family, PUD planned unit development, CND condo, RES residential-other, MFD multi-family dwelling, 2ND second home, MFG manufactured, TWN townhouse, LAN land, COM commercial, …); loans with no code are not grouped (≈20% of recent loans). conforming splits on the conforming-loan-limit flag: conforming vs nonConforming (above the county conforming limit — i.e. jumbo, not Non-QM), raw true/false on id. channel (companies only) splits the company's loans into inHouse — the company employed the originating loan officer — and tpo — the company is the loan company or funding lender but did NOT employ the LO (third-party origination). The two never overlap; under roleScope: "all" they need not sum to the total (broker-only and LO-organization-only matches are in neither). Both buckets are always returned.
