BCBS 239
BCBS 239
Assurez une cohérence irréprochable entre tous vos produits de données
Assurez une cohérence irréprochable entre tous vos produits de données
Santiago Viquez
DevRel chez Soda
Ensure accounting data is complete, consistent, and reconcilable to support BCBS 239-compliant risk reporting.
Data contract description
This data contract enforces BCBS 239–aligned controls on the exposures dataset. It validates schema stability, detects orphan counterparties, duplicate records, and invalid exposure amounts via failed_rows checks, enforces LEI format and referential integrity at the column level, and reconciles total exposures against accounting balances. Together, these controls help ensure exposure reporting is complete, accurate, and consistent across risk and finance systems.
bcbs239_data_contract.yml
datasetchecks: - schema: allow_extra_columns: false allow_other_column_order: false - row_count: threshold: must_be_greater_than: 0 - failed_rows: name: exposures_without_valid_counterparty qualifier: counterparty_integrity query: | SELECT e.counterparty_id FROM datasource.db.schema.exposures e LEFT JOIN datasource.db.schema.counterparty_master m ON e.counterparty_id = m.counterparty_id WHERE m.counterparty_id IS NULL threshold: must_be: 0 attributes: bcbs239: - P3 description: "Integrity: every exposure must reference an existing counterparty in the master data." - failed_rows: name: duplicate_exposure_records qualifier: duplicate_records query: | SELECT counterparty_id, facility_id, as_of_date FROM datasource.db.schema.exposures GROUP BY counterparty_id, facility_id, as_of_date HAVING COUNT(*) > 1 threshold: must_be: 0 attributes: bcbs239: - P3 - P4 description: "Accuracy and completeness: no duplicate exposure records per counterparty, facility, and reporting date." - failed_rows: name: invalid_exposure_amount qualifier: exposure_amount_validity query: | SELECT counterparty_id, exposure_amount FROM datasource.db.schema.exposures WHERE exposure_amount IS NULL OR exposure_amount < 0 threshold: must_be: 0 attributes: bcbs239: - P3 description: "Accuracy and integrity: exposure amounts must be populated and non-negative."
columns: - name: lei_code data_type: string checks: - invalid: name: lei_code_format valid_format: name: LEI must be 20 alphanumeric regex: '^[A-Z0-9]{20}$' attributes: bcbs239: - P3 description: LEI format is 20 uppercase alphanumerics - name: counterparty_id checks: - missing: attributes: bcbs239: - P4 description: "Completeness: every exposure must include a counterparty identifier." - invalid: name: counterparty_id_in_master valid_reference_data: dataset: datasource/db/schema/counterparty_master column: counterparty_id attributes: bcbs239: - P3 description: "Integrity: all counterparties in exposures must exist in the master data." - name: exposure_amount data_type: decimal checks: - missing: attributes: bcbs239: - P4 description: "Completeness: exposure amounts must be populated." - invalid: name: exposure_amount_non_negative valid_min: 0 attributes: bcbs239: - P3 description: "Accuracy: exposure amounts must be zero or positive." - name: as_of_date data_type: date checks: - missing: attributes: bcbs239: - P4 description: "Completeness: every exposure record must include a reporting date." - name: facility_id data_type: string checks: - missing: attributes: bcbs239: - P4 description: "Completeness: each exposure must reference a facility." - invalid: name: "facility_id length guardrail" valid_min_length: 1 valid_max_length: 64 reconciliation: source: dataset: datasource/db/schema/accounting_balances checks: - metric_diff: name: total_exposures_vs_total_balance source_expression: SUM(balance_amount) target_expression: SUM(exposure_amount) threshold: must_be_less_than: 1000 attributes: bcbs239: - P3 - P7 description: "Reconciliation vs accounting: overall tolerance across the books (sum vs sum)"
Data contract description
This data contract enforces BCBS 239–aligned controls on the exposures dataset. It validates schema stability, detects orphan counterparties, duplicate records, and invalid exposure amounts via failed_rows checks, enforces LEI format and referential integrity at the column level, and reconciles total exposures against accounting balances. Together, these controls help ensure exposure reporting is complete, accurate, and consistent across risk and finance systems.
bcbs239_data_contract.yml
datasetchecks: - schema: allow_extra_columns: false allow_other_column_order: false - row_count: threshold: must_be_greater_than: 0 - failed_rows: name: exposures_without_valid_counterparty qualifier: counterparty_integrity query: | SELECT e.counterparty_id FROM datasource.db.schema.exposures e LEFT JOIN datasource.db.schema.counterparty_master m ON e.counterparty_id = m.counterparty_id WHERE m.counterparty_id IS NULL threshold: must_be: 0 attributes: bcbs239: - P3 description: "Integrity: every exposure must reference an existing counterparty in the master data." - failed_rows: name: duplicate_exposure_records qualifier: duplicate_records query: | SELECT counterparty_id, facility_id, as_of_date FROM datasource.db.schema.exposures GROUP BY counterparty_id, facility_id, as_of_date HAVING COUNT(*) > 1 threshold: must_be: 0 attributes: bcbs239: - P3 - P4 description: "Accuracy and completeness: no duplicate exposure records per counterparty, facility, and reporting date." - failed_rows: name: invalid_exposure_amount qualifier: exposure_amount_validity query: | SELECT counterparty_id, exposure_amount FROM datasource.db.schema.exposures WHERE exposure_amount IS NULL OR exposure_amount < 0 threshold: must_be: 0 attributes: bcbs239: - P3 description: "Accuracy and integrity: exposure amounts must be populated and non-negative."
columns: - name: lei_code data_type: string checks: - invalid: name: lei_code_format valid_format: name: LEI must be 20 alphanumeric regex: '^[A-Z0-9]{20}$' attributes: bcbs239: - P3 description: LEI format is 20 uppercase alphanumerics - name: counterparty_id checks: - missing: attributes: bcbs239: - P4 description: "Completeness: every exposure must include a counterparty identifier." - invalid: name: counterparty_id_in_master valid_reference_data: dataset: datasource/db/schema/counterparty_master column: counterparty_id attributes: bcbs239: - P3 description: "Integrity: all counterparties in exposures must exist in the master data." - name: exposure_amount data_type: decimal checks: - missing: attributes: bcbs239: - P4 description: "Completeness: exposure amounts must be populated." - invalid: name: exposure_amount_non_negative valid_min: 0 attributes: bcbs239: - P3 description: "Accuracy: exposure amounts must be zero or positive." - name: as_of_date data_type: date checks: - missing: attributes: bcbs239: - P4 description: "Completeness: every exposure record must include a reporting date." - name: facility_id data_type: string checks: - missing: attributes: bcbs239: - P4 description: "Completeness: each exposure must reference a facility." - invalid: name: "facility_id length guardrail" valid_min_length: 1 valid_max_length: 64 reconciliation: source: dataset: datasource/db/schema/accounting_balances checks: - metric_diff: name: total_exposures_vs_total_balance source_expression: SUM(balance_amount) target_expression: SUM(exposure_amount) threshold: must_be_less_than: 1000 attributes: bcbs239: - P3 - P7 description: "Reconciliation vs accounting: overall tolerance across the books (sum vs sum)"
Data contract description
This data contract enforces BCBS 239–aligned controls on the exposures dataset. It validates schema stability, detects orphan counterparties, duplicate records, and invalid exposure amounts via failed_rows checks, enforces LEI format and referential integrity at the column level, and reconciles total exposures against accounting balances. Together, these controls help ensure exposure reporting is complete, accurate, and consistent across risk and finance systems.
bcbs239_data_contract.yml
datasetchecks: - schema: allow_extra_columns: false allow_other_column_order: false - row_count: threshold: must_be_greater_than: 0 - failed_rows: name: exposures_without_valid_counterparty qualifier: counterparty_integrity query: | SELECT e.counterparty_id FROM datasource.db.schema.exposures e LEFT JOIN datasource.db.schema.counterparty_master m ON e.counterparty_id = m.counterparty_id WHERE m.counterparty_id IS NULL threshold: must_be: 0 attributes: bcbs239: - P3 description: "Integrity: every exposure must reference an existing counterparty in the master data." - failed_rows: name: duplicate_exposure_records qualifier: duplicate_records query: | SELECT counterparty_id, facility_id, as_of_date FROM datasource.db.schema.exposures GROUP BY counterparty_id, facility_id, as_of_date HAVING COUNT(*) > 1 threshold: must_be: 0 attributes: bcbs239: - P3 - P4 description: "Accuracy and completeness: no duplicate exposure records per counterparty, facility, and reporting date." - failed_rows: name: invalid_exposure_amount qualifier: exposure_amount_validity query: | SELECT counterparty_id, exposure_amount FROM datasource.db.schema.exposures WHERE exposure_amount IS NULL OR exposure_amount < 0 threshold: must_be: 0 attributes: bcbs239: - P3 description: "Accuracy and integrity: exposure amounts must be populated and non-negative."
columns: - name: lei_code data_type: string checks: - invalid: name: lei_code_format valid_format: name: LEI must be 20 alphanumeric regex: '^[A-Z0-9]{20}$' attributes: bcbs239: - P3 description: LEI format is 20 uppercase alphanumerics - name: counterparty_id checks: - missing: attributes: bcbs239: - P4 description: "Completeness: every exposure must include a counterparty identifier." - invalid: name: counterparty_id_in_master valid_reference_data: dataset: datasource/db/schema/counterparty_master column: counterparty_id attributes: bcbs239: - P3 description: "Integrity: all counterparties in exposures must exist in the master data." - name: exposure_amount data_type: decimal checks: - missing: attributes: bcbs239: - P4 description: "Completeness: exposure amounts must be populated." - invalid: name: exposure_amount_non_negative valid_min: 0 attributes: bcbs239: - P3 description: "Accuracy: exposure amounts must be zero or positive." - name: as_of_date data_type: date checks: - missing: attributes: bcbs239: - P4 description: "Completeness: every exposure record must include a reporting date." - name: facility_id data_type: string checks: - missing: attributes: bcbs239: - P4 description: "Completeness: each exposure must reference a facility." - invalid: name: "facility_id length guardrail" valid_min_length: 1 valid_max_length: 64 reconciliation: source: dataset: datasource/db/schema/accounting_balances checks: - metric_diff: name: total_exposures_vs_total_balance source_expression: SUM(balance_amount) target_expression: SUM(exposure_amount) threshold: must_be_less_than: 1000 attributes: bcbs239: - P3 - P7 description: "Reconciliation vs accounting: overall tolerance across the books (sum vs sum)"
How to Enforce Data Contracts with Soda
Embed data quality through data contracts at any point in your pipeline.
Embed data quality through data contracts at any point in your pipeline.
# pip install soda-{data source} for other data sources
# pip install soda-{data source} for other data sources
pip install soda-postgres
pip install soda-postgres
# verify the contract locally against a data source
# verify the contract locally against a data source
soda contract verify -c contract.yml -ds ds_config.yml
soda contract verify -c contract.yml -ds ds_config.yml
# publish and schedule the contract with Soda Cloud
# publish and schedule the contract with Soda Cloud
soda contract publish -c contract.yml -sc sc_config.yml
soda contract publish -c contract.yml -sc sc_config.yml
Check out the CLI documentation to learn more.
Check out the CLI documentation to learn more.
How to Automatically Create Data Contracts.
In one Click.
Automatically write and publish data contracts using Soda's AI-powered data contract copilot.
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Commencez à faire confiance à vos données. Aujourd'hui.
Trouvez, comprenez et corrigez tout problème de qualité des données en quelques secondes.
Du niveau de la table au niveau des enregistrements.
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Solutions
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Commencez à faire confiance à vos données. Aujourd'hui.
Trouvez, comprenez et corrigez tout problème de qualité des données en quelques secondes.
Du niveau de la table au niveau des enregistrements.
Adopté par
Solutions
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