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Tools for importing open data of Lithuania's legal entities

Tools provided here allow you to download open data provided by the center of registers (Registrų centras) and Sodra, store that data in the MySQL database and perform further analyses.

I used this tool to create a dataset that could be used for training ML models to calculate legal entity probability of bankruptcy.

Sources used:

Collect open data of the legal entities

  1. Run docker-compose up, this command spins up the local MySQL database, where all legal entities' data will be stored
  2. Execute pip install -r requirements.txt to install libraries needed for importing the legal entities' data
  3. Run import by executing python import_open_data.py

Database structure

Table name Description
stg_legal_entities_addresses Addresses of legal entities registered in the center of registers
stg_legal_entities_authorized_capital Authorized capital of registered legal entities
stg_legal_entities_balance_sheets Balance sheets provided by legal entities by finance year
stg_legal_entities_management Information on the management of registered legal entities
stg_legal_entities_profit_loss_statements Profit loss statements provided by legal entities by finance year
stg_registered_legal_entities Legal entities currently registered in the center of registers
stg_unregistered_legal_entities Legal entities currently registered in center of registers
stg_sodra_monthly Monthly legal entities data provided for Sodra (average salaries, employees count, social security debt, etc.)

Generate bankruptcy dataset

  1. Perform steps listed here
  2. Execute dataset generation by executing python generate_bankruptcy_dataset.py

Basic EDA of dataset could be find here

Bankruptcy dataset fields description

Field Description
registration_date Company registration date (company creation date), e.g. 2021-01-27
legal_form_name Name of company legal form, e.g. Small Partnership, Private Limited Liability Company
status_name Legal status of the company (latest status, not the one that was on a particular year), e.g. Bankrupt, Under Reorganization
finance_year_start_date Start of the financial year for which information is registered, e.g. 2019-01-01
finance_year_end_date End of the financial year for which information is registered, e.g. 2019-12-31
document_registration_date Date when finance documents were registered, e.g. 2020-06-01
equity Equity of the company
liabilities Liabilities of the company
long_term_financial_assets Long-term financial assets of the company
short_term_financial_assets Short-term financial assets of the company
profit_before_taxes Profit before taxes of the company
net_profit Company net profit
sales_revenue Sales revenue of the company
idx_eq_lia_ratio Radio of equity / liabilities
idx_lia_fin_as_ratio Ratio liabilities / (long term + short term financial assets)
idx_sh_fin_as_lia_ratio Ratio short term financial assets / liabilities
idx_fin_as_eq_ratio Ratio (long term + short term financial assets) / equity
idx_fin_as_lia_ratio Ratio (long term + short term financial assets) / liabilities
idx_n_prof_fin_as_ratio Ratio net profit / (long term + short term financial assets)
idx_s_rev_fin_as_ratio Ratio sales revenue / (long term + short term financial assets)
idx_prof_tax_eq_ratio Ratio profit before taxes / equity
idx_prof_tax_fin_as_ratio Ratio profit before taxes / (long term + short term financial assets)

null - indicates that data was not provided in finance year balance sheets or profit/loss statements

Statuses Under Restructuring, Going Bankrupt, Bankrupt, Liquidation due to bankruptcy were used as bankruptcy indicators.

Two different bankruptcy labels are created:

  1. is_bankrupted_last_year - when only the last financial years of the company being active are labeled as bankrupted
  2. is_bankrupted_all_years - when all companies' financial years (despite the company went bankrupt only during the last years) are marked as bankrupted

Sample of is_bankrupted_last_year and is_bankrupted_all_years

code finance_year_start_date ... is_bankrupted_last_year is_bankrupted_all_years
11111 2018-01-01 ... 0 1
11111 2019-01-01 ... 0 1
11111 2020-01-01 ... 0 1
11111 2021-01-01 ... 1 1

Bankruptcy data cleaning

For the preparation of the dataset some raw data were removed:

  1. Removed rows where finance year start and financial year end were equal
  2. Removed rows that did not had matching in balance and profit-loss tables when using registration code and finance year start date fields

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Dataset of Lithuania legal entities

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