Farm Financial Benchmarking Data
Revenue, expenses, and profit margins by farm size, crop, and region -- the financial data that lenders use to underwrite ag loans and farmers use to benchmark performance.
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What Is Farm Financial Benchmarking Data?
Farm financial benchmarking data provides revenue, expenses, and profit margins organized by farm size, crop type, and geographic region. This data enables farmers and agricultural lenders to compare individual operation performance against peer groups and industry standards. The primary national repository is FINBIN, a centralized database maintained through partnerships with farm management associations and state agricultural extension programs. Data is collected from geographically and operationally diverse farms and ranches, then made publicly accessible through online tools that allow queries filtered by farm attributes, enterprise type, and production practices. Financial benchmarking helps producers assess their current position, identify operational strengths and weaknesses, and shape business goals for future growth and profitability.
Market Data
FINBIN - open access to summary financial information and benchmarks
Primary Public Database
Source: University of Minnesota
Farm size, type, whole-farm attributes, enterprise-level production practices
Query Filters Available
Source: University of Minnesota
Geographically and operationally diverse farms and ranches nationwide
Data Collection Focus
Source: University of Minnesota
FINPACK, RankEm, FINAN for financial analysis and data integrity
Software Tools
Source: University of Minnesota
Who Uses This Data
What AI models do with it.do with it.
Agricultural Lenders
Use benchmarking data to underwrite loans and assess farm creditworthiness by comparing applicant financials against peer operations of similar size and crop type.
Farm Managers & Producers
Compare their own financial ratios and operational metrics against cohorts to identify performance gaps, evaluate growth over time, and develop strategic business goals.
Farm Management Associations
Collect year-end financial data from member farms and use analysis tools to provide benchmarking insights and advisory services to producers.
Agricultural Consultants & Advisors
Use benchmarking databases to advise clients on financial positioning, operational efficiency, and competitive standing within their market segment.
Pricing depends on the proposed terms
We do not have a verified, comparable price for your dataset. Consider the permitted uses, license term, exclusivity, provenance, coverage and quality. A seller asking price is a proposal, not an appraisal or guaranteed sale. Compare prices only when the source, date, currency, unit and license scope are known.
What Buyers Expect
What makes it valuable.valuable.
Data Integrity & Accuracy
High-quality benchmarking data requires year-end financial analysis from individual farms, error-checking protocols, and technical data dictionaries for balance sheet and enterprise-level calculations.
Comprehensive Financial Metrics
Data must include complete whole-farm financial variables, crop and enterprise-level information, production practices, and standardized ratio calculations aligned with FINAN analysis standards.
Geographically & Operationally Diverse Coverage
Buyers expect benchmarking databases to represent diverse farm sizes, types, regions, and production methods to ensure relevant peer comparisons and broad applicability.
Accessible Query Capabilities
Data must be organized to allow filtering by farm size, crop type, region, marketing channels, and other attributes so users can identify true peer groups for meaningful comparison.
Potential applications and organizations
Who's buying.buying.
Agricultural lender using benchmarking data for loan underwriting and providing financial officers who advise farmers on balance sheet structure and benchmarking insights.
Collects financial data from member farms and provides benchmarking tool allowing farmers and ranchers to compare financial ratios against cohorts.
Maintains FINBIN national database, develops FINPACK and RankEm software, hosts annual benchmarking leaders meeting, and collaborates with state farm management associations.
FAQ
Common questions.questions.
What is FINBIN and how can I access it?
FINBIN is the national farm financial benchmarking database maintained by the University of Minnesota. It is open to anyone and allows public queries for summary financial information and benchmarks on financial metrics. Data can be filtered by farm size, type, and various whole-farm attributes, as well as by specific production practices for crop and livestock enterprises.
How often is benchmarking data updated?
The national benchmarking database receives annual data submissions from farm management associations and partners. Software tools like FINPACK and RankEm are typically updated in November and December respectively, with the most recent versions improving data integrity and error checking prior to submission.
What specific financial metrics are included in benchmarking datasets?
Benchmarking data includes revenue, expenses, profit margins, balance sheet variables, whole-farm financial variables and calculations, crop and enterprise-level analysis, and financial ratios that indicate operational strengths and weaknesses. Data is organized to support both whole-farm and enterprise-level comparisons.
Who contributes data to the national benchmarking database?
Farm management associations, agricultural extension programs, and emerging benchmarking efforts collect year-end financial data directly from farmers and ranchers. These organizations work with producers to develop comprehensive financial analyses, which are then submitted to FINBIN for inclusion in the national database.
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