Normalized Source Data
Agency-published data is ingested, reviewed, normalized, and prepared for lookup, integration, and analysis workflows.
Seamless API access to critical financial data
Enterprise-grade APIs for housing, income-limit, and affordability data.
Finbase turns selected financial data sets into documented APIs for system and analytics integrations. Teams can access maintained data through Finbase, reducing the need to ingest, normalize, and manage source data internally.
Built for financial services, banking, affordable housing, grant management, and other teams that rely on accurate income-limit and affordability data.
Reduce Risk
Reduce manual ingestion, parsing, and internal data-loading errors
Improve Consistency
Use consistent income-limit values in qualification and affordability workflows
Reduce Internal Maintenance
Leave income-limit storage, lookup logic, and common calculations to Finbase
Core Capabilities
Consistent API access to income-limit data sets and derived thresholds.
Finbase provides access to maintained income-limit data and derived thresholds, reducing the need to download, parse, normalize, load, audit, and maintain the same source data across internal systems.
Consistent API Access
Systems can integrate directly with documented REST endpoints, reducing the need to maintain source data and geographic mapping logic internally.
Derived Limits
Custom-calculated AMI band and maximum rent thresholds derived from fixed-value income limits reduce the need to recreate common calculations internally.
Operational Impact
Income-limit management should not become a recurring systems project.
Organizations that rely on published data often have to ingest it into multiple systems, validate the loaded values, and adapt whenever source formats, structures, or geography definitions change.
Reduce Repetitive Ingestion
Finbase reduces or eliminates repeated downloading, parsing, loading, and auditing of the same data across customer systems.
Improve Data Consistency
Incorrect limits can affect qualification, compliance, underwriting, and affordability analysis in regulated programs.
Reduce Costly System Changes
Finbase adapts to source-format, structural, and geography-definition changes so integrated systems can rely on consistent API behavior.
Applied Use Cases
Apply income-limit data where qualification and affordability decisions happen.
These examples show how connected systems can use values sourced from Finbase APIs.
Scenario Overview
A mortgage or grant applicant must be income-qualified against HUD-published income limits, confirming household income is at or below 80% of Area Median Income for the applicable household size and property address.
Household qualification review
Qualified
John Smith
Household Details
Household income
$108,000
Household size
4
Property address
1 Finbase Ave, Brooklyn, NY
County
Kings County, NY
Income Qualification Criteria
Data source
HUD
Fiscal year
2026
Qualification rule
Household income at or below 80% of AMI (Low Income)
Qualification Results
Mapped income area
New York, NY HUD Metro FMR Area
80% limit for household size
$135,700
Income to AMI limit
63.7%
Income qualified
Yes
Example uses HUD 2026 Section 8 limits for Kings County, NY. Example values are shown for illustration.
Scenario Overview
A moderate-income mortgage or grant workflow may require household income to fall within a targeted AMI range, such as 80% to 120%, based on location and household size. This example shows how Finbase can derive the applicable income thresholds from HUD-published 80% income limits for use in qualification workflows.
Moderate income threshold lookup
HUD 2026
San Francisco County, CA
Source: HUD
Baseline: 80%
Derived thresholds: 80%, 120%
Area: San Francisco, CA HUD Metro FMR Area
| Income Threshold | 1 person | 2 person | 3 person | 4 person | 5 person | 6 person | 7 person | 8 person |
|---|---|---|---|---|---|---|---|---|
| Minimum Income (80% of AMI) | $117,700 | $134,500 | $151,300 | $168,100 | $181,550 | $195,000 | $208,450 | $221,900 |
| Maximum Income (120% of AMI) | $176,550 | $201,750 | $226,950 | $252,150 | $272,325 | $292,500 | $312,675 | $332,850 |
1 person
$117,700 - $176,550
4 person
$168,100 - $252,150
8 person
$221,900 - $332,850
Representative values shown. Full table available on larger screens.
Example uses HUD 2026 Section 8 limits for San Francisco County, CA. Values are rounded to the nearest whole dollar and shown for illustration.
Scenario Overview
Renters in grant-funded projects may need unit rents evaluated against affordability thresholds for the applicable AMI band, expense percentage, bedroom size, and location. This example shows how Finbase can derive maximum rent limits from HUD income limits and support comparison of actual rent against program affordability requirements.
Maximum rent threshold lookup
HUD 2026
Fulton County, GA
Source: HUD
Baseline: 50%
Expense limit: 30%
Bedroom factor: 1.5
| Maximum AMI Threshold | Studio | 1 BR | 2 BR | 3 BR | 4 BR |
|---|---|---|---|---|---|
| 50% | $1,031.25 | $1,105.00 | $1,326.25 | $1,531.88 | $1,708.75 |
| 65% | $1,340.63 | $1,436.50 | $1,724.12 | $1,991.44 | $2,221.38 |
| 80% | $1,650.00 | $1,768.00 | $2,122.00 | $2,451.00 | $2,734.00 |
50% AMI
Studio $1,031.25
2 BR $1,326.25 | 4 BR $1,708.75
65% AMI
Studio $1,340.63
2 BR $1,724.12 | 4 BR $2,221.38
80% AMI
Studio $1,650.00
2 BR $2,122.00 | 4 BR $2,734.00
Representative values shown. Full table available on larger screens.
Example uses HUD 2026 Section 8 limits for the Atlanta-Sandy Springs-Roswell, GA HUD Metro FMR Area. Example values are shown for illustration.
API Capabilities
Beyond static income-limit lookups.
Depending on plan access, Finbase APIs can return fixed income limits, derived AMI thresholds, maximum rent calculations, and household-size or bedroom-size outputs. Requests can also be shaped by custom bedroom-size factors, affordability percentages, fiscal-year or effective-date filters, and geography-based lookups by county, area, or state.
Ready to evaluate Finbase?
Start a free evaluation trial, review pricing, or inspect the API documentation before connecting your systems.