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Lithuanian agricultural and company data API

Official Lithuanian registers joined on the legal entity code: company financials, risk and concentration signals, tax and insolvency status, agricultural prices, livestock, crops and farmland. Available today as fully custom datasets (CSV, JSON, Parquet, an API endpoint or a webhook); the self-serve REST API is in development, with pilot keys issued individually.

Describe your data need →See the data families ↓

Price on request · reply within 1 business day · no personal data of individual farmers

Live coverage · Centre of Registers accounts

What the risk layer covers

3,214

registry companies with filed accounts (latest year, 2023 onward)

87.3%

of their revenue earned by the top 10% of companies

4%

technically insolvent (liabilities exceed assets)

€25.0bn

total revenue analysed

Live figures from the public part of /api/v1/market/overview. Coverage is every registry company with filed statements - not only agriculture: the registry also holds food retail, processing and supply companies, so the revenue total and concentration are not indicators of the agricultural sector alone. For farming companies only (NACE 01), see the largest agricultural companies.

141,266

farms, companies and other subjects in the registry

794,473

animals in 35,077 herds, national animal register, September 2026

27

public state sources from 14 institutions

Data families

Custom datasets are assembled from these families. The cadence shown is the source's publication schedule; the actual coverage of each delivery (up to which date the data reach) is documented with the data.

Farm and company registry

Every agricultural subject in one registry: name, legal form, NACE activity, municipality, coordinates, register dates, joined on the legal entity code.

Monthly

Browse the public data →

Company financials

Revenue, profit, equity, assets and liabilities by legal entity code and financial year, from statements filed with the Centre of Registers.

Monthly

Risk and concentration signals

A transparent 0-100 risk score (margin, solvency, leverage), insolvency and loss-making flags, revenue percentiles, HHI concentration and a stress simulation.

Computed on request

Tax status

VAT registrations, weekly tax-arrears trajectories (accumulated, never deleted) and annual taxes paid from the State Tax Inspectorate (VMI).

Weekly / monthly

Insolvency

Bankruptcy and restructuring proceedings from the Authority of Audit, Accounting, Property Valuation and Insolvency Management (AVNT).

Quarterly (AVNT)

Food and veterinary operators

Operators supervised by the State Food and Veterinary Service (VMVT) with activities, approval numbers and inspection history.

Monthly

Livestock

Herd locations by municipality and eldership, with monthly herd-by-species snapshots of animal numbers from the Agricultural Data Centre (ŽŪDC).

Monthly · history accumulated

Browse the public data →

Declared crops

Year × municipality × crop: declared area in hectares and number of fields from ŽŪDC field declarations.

Yearly

Browse the public data →

Agricultural prices

National purchase price series for grain, oilseeds and cattle (ŽŪDC) and raw milk purchase prices, each with its period.

Weekly / monthly

Browse the public data →

Farmland prices

Agricultural land sale prices and rents by municipality and year from official statistics.

Yearly

Browse the public data →

EU and national support

Archive of National Paying Agency (NMA) beneficiary lists - the portal keeps only the last two years, our archive keeps every year - and the support-call calendar. Payment amounts are not stored.

Yearly archive · weekly calls

Browse the public data →

Certificates and machinery

Organic certificates (Ekoagros, EU TRACES) with validity windows, the plant-health register and registered machinery fleets by legal entity.

Monthly / weekly

Browse the public data →

Who uses it

Credit risk

Banks, credit unions and agricultural lenders

An agricultural loan book needs a fast, objective creditworthiness signal, but public financial statements are scattered and slow to collect. Decisions are often made with too little structured data.

  • One number to assess risk - a 0-100 financial risk score computed from real balance sheets, ready for onboarding and limits.
  • Portfolio review and early warning: see which borrowers are sliding towards insolvency before payments fall behind.
  • Peer comparison - revenue percentile and margin context show whether a company is strong within its group.
  • One consistent, auditable method for the whole portfolio instead of reading statements by hand.
GET /v1/companies/{code}/risk

risk score, solvency (equity/assets), leverage (liabilities/assets), margin, insolvency flag, revenue percentile

GET /v1/risk/distressed

highest-risk companies for watch lists

GET /v1/market/overview

loss-making and insolvency rates as context

Does this replace a credit decision?
No. It is an objective input signal for screening, monitoring and limits - you decide under your own policy. It is not a credit recommendation.
Where do the financial data come from?
From the annual financial statements filed with the Centre of Registers (Registrų centras). The score is a transparent composite of margin, solvency and leverage.

Farm and company registryLargest agricultural companies

Portfolio risk

Agricultural insurers and reinsurers

Pricing and risk appetite for an insurance book require understanding how badly the whole sector can behave at once - not just one client. Shock scenarios are hard to assess without a model.

  • Sector stress test: set a revenue shock and see how many agricultural companies would become insolvent - for tail risk and pricing.
  • Accumulation risk: market concentration (HHI, top shares) shows how much a portfolio depends on a few large players.
  • Financial stability check of an individual policyholder before writing or renewing a policy.
  • A deterministic model - the same parameters give the same result, suitable for auditable analysis.
POST /v1/simulate/stress

expected insolvencies, revenue at risk and distribution by risk band under the chosen shock

GET /v1/companies/{code}/risk

an individual policyholder's risk score and insolvency flag

GET /v1/market/overview

concentration (HHI), insolvency rate, total revenue

Is the simulation random?
No. The Monte Carlo simulation is seeded and deterministic: the same parameters always return the same result.
Does it assess my specific portfolio?
The base simulation covers the whole sector. An assessment against your own list of policyholders can be arranged as a custom project.

Livestock numbers in LithuaniaMarket barometerLT

Deals and analysis

Investors, M&A teams and consultants

Before a deal you need to understand market structure quickly, find targets and assess risk - often working from scattered public sources on a tight timeline.

  • Target screening: lists of the highest-risk and thin-margin companies point to possible acquisition or consolidation targets.
  • Market structure: concentration (HHI, revenue share of the top 1% and 10%) shows the room for consolidation.
  • Due diligence input: a company's risk score, solvency and leverage in one place.
  • A risk map of competitors - which players in the sector are vulnerable.
GET /v1/risk/distressed

highest-risk companies with names, revenue and margin

GET /v1/companies/{code}/risk

a single company's risk profile during due diligence

GET /v1/market/overview

concentration and sector summary to support a thesis

Are company names included?
Yes - the distressed list includes names, revenue and margin for legal entities. Personal data of natural persons is not published.
Is this investment advice?
No. It is an informational data product for analysis; decisions are made at your own responsibility.

Largest agricultural companiesAgricultural business dynamicsLT

Counterparty risk

Suppliers, machinery dealers, grain traders and cooperatives

Deferred payment or trade credit risks a bad debt if the client is financially unstable. Manual checks are slow and inconsistent.

  • A quick counterparty check before a deal: is the client solvent, is it loss-making, how leveraged is it.
  • Credit limits set on an objective risk score rather than instinct.
  • Flag risky counterparties and reduce bad debt.
  • Suited to re-checking an existing client base every quarter.
GET /v1/companies/{code}/risk

risk score, insolvency flag, margin and leverage by the client's company code

GET /v1/risk/distressed

highest-risk companies to flag in an existing client base

Is a company code enough?
Yes - the request takes the legal entity code and returns the latest risk profile.
How often is it updated?
Together with the public financial statements. We recommend re-checking an existing base periodically.

Company registry and searchAgricultural purchase prices

REST API endpoints

Pilot access

JSON over HTTPS with bearer keys. Keys are issued individually, so pilot access can be arranged before the public launch. Pricing has not been published: price on request.

GET/api/v1/market/overview

Market summary: number of companies, loss-making and insolvency rates, revenue concentration (HHI, top 1% and top 10% share).

GET/api/v1/companies/{code}/risk

One company's risk score (0-100), margin, solvency and leverage ratios, insolvency flag and revenue percentile.

GET/api/v1/risk/distressed

Legal entities ordered by risk score for building watch lists - signals for a decision you make.

POST/api/v1/simulate/stress

Deterministic Monte Carlo stress simulation over real balance sheets: set a revenue shock and horizon, get expected insolvencies.

curl https://fermos.lt/api/v1/market/overview \
  -H "Authorization: Bearer fmk_live_..."

Frequently asked questions

What can I order today?
A fully custom dataset built from any of the data families on this page - one-off or regularly refreshed. Describe your need through the contact form and we reply within one business day with scope, format and timeline.
How much does it cost?
Price on request. Custom datasets are quoted per project once the scope is clear, and the self-serve API has no published pricing yet.
Where does the data come from?
Only from public Lithuanian state sources: the Centre of Registers, the State Tax Inspectorate (VMI), the State Food and Veterinary Service (VMVT), AVNT, the National Paying Agency (NMA), the Agricultural Data Centre (ŽŪDC), Regitra and other registers. Every update is logged.
Do you provide personal data of individual farmers?
No. Data on individual farmers is provided only at municipality level, fields the source masks stay masked, and NMA recipients published only as codes stay coded. Deliveries are aggregates, legal entities and derived signals (GDPR).
Is the risk score a recommendation?
No. It is an informational data product: the score is a transparent composite of margin, solvency and leverage, and the stress simulation is deterministic. Decisions remain yours.

Tell us which data you need

A sentence or two is enough: which entities, which attributes, which format and how often. We reply within one business day with scope, format and a quote. No commitment.

Contact us about data →

Sources: Centre of Registers, VMI, VMVT, AVNT, NMA, ŽŪDC, Regitra and other public registers. Risk signals are an informational data product, not investment or credit advice.