Sample Data for Testing

Overview

This guide provides comprehensive sample data for testing Risk Legion end-to-end. All data structures align with the current implementation and can be used for API testing, demonstrations, and development.

For a complete demo scenario using Brazilian banking context, see the DEMO_DATA_INPUT_GUIDE.md in the repository.

Key Data Model Notes

Products no longer have Category field

Products are now defined by their attributes only: customer types, geographic operations, distribution channels, and transaction types. The category field has been removed.

Sub-Controls: Creation vs Assessment

Sub-Controls are created in Governance with only name and description. The ToD/ToE effectiveness ratings are assessed separately in Control Assurance. This separates control definition from control assessment.

Risk Appetite Snapshot

When a BRA transitions to in_progress, the current risk appetite level is captured as snapshot_appetite_level. This ensures changes to enterprise risk appetite don’t affect assessments already in progress.

Quick Start

1. Create Test Users

Use the provided script to create test users with different roles:

cd backend

# Create a Super Admin
python scripts/create_test_user.py \
  --email superadmin@test.com \
  --password SuperAdmin123! \
  --role super_admin

# Create a Client Admin
python scripts/create_test_user.py \
  --email admin@acme.com \
  --password Admin123! \
  --role admin \
  --enterprise "ACME Corporation"

# Create an Assessor
python scripts/create_test_user.py \
  --email assessor@acme.com \
  --password Assessor123! \
  --role assessor \
  --enterprise "ACME Corporation"

# Create a Reviewer
python scripts/create_test_user.py \
  --email reviewer@acme.com \
  --password Reviewer123! \
  --role reviewer \
  --enterprise "ACME Corporation"

2. Get JWT Tokens

Retrieve JWT tokens for API testing:

# Get token for admin user
python scripts/get_token.py \
  --email admin@acme.com \
  --password Admin123!

# Copy the token and use in Postman/curl

Sample Enterprises

-- Create test enterprises
INSERT INTO enterprises (id, name, country, registration_number, status, subscription_tier, mrr_cents, active)
VALUES
  ('550e8400-e29b-41d4-a716-446655440001', 'ACME Corporation', 'US', 'REG-001', 'active', 'enterprise', 199900, true),
  ('550e8400-e29b-41d4-a716-446655440002', 'Global Tech Inc', 'UK', 'REG-002', 'active', 'professional', 99900, true),
  ('550e8400-e29b-41d4-a716-446655440003', 'Startup Labs', 'CA', 'REG-003', 'active', 'starter', 49900, true)
RETURNING id, name, status;

Sample Organization Structure

Legal Entities

-- Create legal entities with hierarchy
INSERT INTO legal_entities (id, enterprise_id, name, legal_name, entity_type, registration_number, country_of_incorporation, parent_id, archived)
VALUES
  -- Parent entity
  ('le-001', '550e8400-e29b-41d4-a716-446655440001', 'ACME Bank Brasil S.A.', 'ACME Bank Brasil S.A.', 'Bank', '33.234.567/0001-89', 'Brazil', NULL, false),
  -- Child entities
  ('le-002', '550e8400-e29b-41d4-a716-446655440001', 'ACME Seguros Ltda.', 'ACME Seguros Ltda.', 'Insurance', '44.345.678/0001-90', 'Brazil', 'le-001', false),
  ('le-003', '550e8400-e29b-41d4-a716-446655440001', 'ACME Investimentos DTVM', 'ACME Investimentos DTVM', 'Investment Firm', '55.456.789/0001-01', 'Brazil', 'le-001', false);

Business Units

-- Create business units
INSERT INTO business_units (id, enterprise_id, legal_entity_id, name, description, archived)
VALUES
  ('bu-001', '550e8400-e29b-41d4-a716-446655440001', 'le-001', 'Retail Banking', 'Consumer banking products and services', false),
  ('bu-002', '550e8400-e29b-41d4-a716-446655440001', 'le-001', 'Corporate Banking', 'Enterprise lending and treasury services', false),
  ('bu-003', '550e8400-e29b-41d4-a716-446655440001', 'le-001', 'Digital Channels', 'Mobile and internet banking', false);

Products

Products no longer have a category field. Instead, they are defined by their attributes: customer types, geographic operations, distribution channels, and transaction types.

-- Create products (category field removed per client feedback)
INSERT INTO products (id, enterprise_id, name, description, customer_types, geographic_operations, distribution_channels, transaction_types, archived)
VALUES
  (
    'prod-001', 
    '550e8400-e29b-41d4-a716-446655440001',
    'Checking Accounts (Conta Corrente)',
    'Standard checking accounts with debit cards, online banking, and overdraft facilities',
    '["Retail Customer", "Small & Medium Enterprise"]',
    '["Americas", "Brazil"]',
    '["In-Branch / Physical Office", "Mobile App", "Online / Web Platform"]',
    '["Internal Transfers (A2A)", "Cash Deposits", "Cash Withdrawals", "Domestic Payments"]',
    false
  ),
  (
    'prod-002',
    '550e8400-e29b-41d4-a716-446655440001', 
    'Corporate Credit Lines',
    'Revolving credit facilities for working capital and business expansion',
    '["Large Corporate", "Fintech"]',
    '["Asia–Pacific", "Americas"]',
    '["Online / Web Platform", "Mobile App", "API / Embedded Integration"]',
    '["Card Payments (POS)", "Card-Not-Present (E-Commerce)", "Loan Disbursements", "Loan Repayments"]',
    false
  ),
  (
    'prod-003',
    '550e8400-e29b-41d4-a716-446655440001', 
    'Investment Funds (Fundos de Investimento)',
    'Mutual funds including fixed income, equities, and multi-market strategies',
    '["Large Corporate", "High-Net-Worth Individual"]',
    '["Americas", "Brazil"]',
    '["In-Branch / Physical Office", "Broker / Intermediary"]',
    '["Direct Debits / Standing Orders", "Card-Not-Present (E-Commerce)", "Investment Transactions"]',
    false
  );

Valid Enum Values for Products

Field	Valid Values
customer_types	Financial Institution, Fintech, High-Net-Worth Individual, Large Corporate, Merchant, Public Sector Entity, Retail Customer, Small & Medium Enterprise, Sole Proprietor
geographic_operations	Americas, Asia–Pacific, Europe, Middle East & North Africa, Sub-Saharan Africa (or specific countries)
distribution_channels	API / Embedded Integration, Broker / Intermediary, Call Center / Assisted, In-Branch / Physical Office, Mobile App, Online / Web Platform, Partner Platform / Marketplace, Third-Party Sales Agent
transaction_types	Card Payments (POS), Card-Not-Present (E-Commerce), Cash Deposits, Cash Withdrawals, Direct Debits / Standing Orders, Domestic Payments, Internal Transfers (A2A), International / Cross-Border Payments, Investment Transactions, Loan Disbursements, Loan Repayments, Merchant Settlements, Mortgage Disbursements, Refunds / Chargebacks

Sample Risk Library

Risk Scenarios

Risk Scenarios support multiple risk groups and categories (stored as comma-separated values or arrays). Use the valid enum values below.

-- Create risk scenarios with proper enum values
INSERT INTO risk_scenarios (id, enterprise_id, name, description, category, risk_group, archived)
VALUES
  (
    'rs-001', 
    '550e8400-e29b-41d4-a716-446655440001', 
    'Consumer Loan Default Risk', 
    'Risk of consumer loan defaults due to economic downturn or over-indebtedness', 
    'Fraud', 
    'Customer Risk', 
    false
  ),
  (
    'rs-002', 
    '550e8400-e29b-41d4-a716-446655440001', 
    'Cyberattack on Digital Banking Platform', 
    'Risk of data breach or system downtime due to sophisticated cyber attacks targeting financial infrastructure', 
    'Cybercrime', 
    'Technology & Cyber Risk', 
    false
  ),
  (
    'rs-003', 
    '550e8400-e29b-41d4-a716-446655440001', 
    'Anti-Money Laundering (AML) Control Failure', 
    'Risk of failing to detect and report suspicious transactions in compliance with regulatory requirements', 
    'Money Laundering', 
    'Operational Risk', 
    false
  ),
  (
    'rs-004', 
    '550e8400-e29b-41d4-a716-446655440001', 
    'Interest Rate Risk in Banking Book', 
    'Risk of losses due to adverse movements in interest rates affecting the banking book', 
    'Proliferation Financing', 
    'Operational Risk', 
    false
  );

Valid Enum Values for Risk Scenarios

Field	Valid Values
risk_group	Customer Risk, Delivery Channel Risk, Employee Risk, Geographic Risk, Governance & Control Risk, Operational Risk, Product & Service Risk, Technology & Cyber Risk, Third-Party / Outsourcing Risk, Transactional Risk
category	Bribery & Corruption, Cybercrime, Fraud, Misconduct / Insider Risk, Money Laundering, Proliferation Financing, Sanctions Risk, Tax Crime / Tax Evasion, Terrorist Financing

Key Controls

-- Create key controls
INSERT INTO key_controls (id, enterprise_id, name, description, archived)
VALUES
  ('kc-001', '550e8400-e29b-41d4-a716-446655440001', 'Automated Credit Scoring and Risk Rating', 'Standardized credit scoring model using bureau data and behavioral analytics', false),
  ('kc-002', '550e8400-e29b-41d4-a716-446655440001', 'Multi-Factor Authentication (MFA)', 'Mandatory MFA for digital banking access', false),
  ('kc-003', '550e8400-e29b-41d4-a716-446655440001', 'Real-Time AML Transaction Monitoring', 'Automated system monitoring all transactions for suspicious patterns', false);

Sub-Controls

Sub-Controls are created in Governance with only name and description. The ToD/ToE ratings are assessed separately in Control Assurance after the sub-control is created. This separates the control definition from the control assessment workflow.

Step 1: Create Sub-Controls (Governance)

-- Create sub-controls with name and description only
-- ToD/ToE ratings are assessed separately in Control Assurance
INSERT INTO sub_controls (id, key_control_id, name, description, archived)
VALUES
  ('sc-001', 'kc-001', 'Bureau Data Verification', 'Automated verification of credit bureau data against major bureaus', false),
  ('sc-002', 'kc-001', 'Income and Employment Verification', 'Cross-checking of stated income against employer databases and tax records', false),
  ('sc-003', 'kc-002', 'Biometric Authentication Enrollment', 'Facial recognition or fingerprint enrollment for mobile app access', false),
  ('sc-004', 'kc-002', 'Failed Authentication Lockout', 'Automatic account lockout after 3 consecutive failed login attempts', false),
  ('sc-005', 'kc-003', 'High-Value Transaction Alerts', 'Real-time alerts for transactions exceeding R$ 50,000', false),
  ('sc-006', 'kc-003', 'PEP Screening', 'Automated screening against Politically Exposed Person databases', false);

Step 2: Assess Sub-Controls (Control Assurance)

-- Update sub-controls with ToD/ToE ratings during Control Assurance
-- ToD: A (Excellent) to E (Inadequate)
-- ToE: 1 (Highly Effective) to 5 (Ineffective)
UPDATE sub_controls SET 
  tod = 'A', 
  toe = '1', 
  total_effectiveness = 'Highly Effective',
  tod_justification = 'Comprehensive design with documented procedures and automated checks',
  toe_justification = 'Sample testing showed 98% effectiveness rate across all tested transactions',
  testing_date = '2026-01-10', 
  tested_by = 'John Smith'
WHERE id = 'sc-001';

UPDATE sub_controls SET 
  tod = 'B', 
  toe = '2', 
  total_effectiveness = 'Effective',
  tod_justification = 'Well-structured verification process with minor documentation gaps',
  toe_justification = 'Sample testing showed 92% effectiveness rate',
  testing_date = '2026-01-10', 
  tested_by = 'John Smith'
WHERE id = 'sc-002';

-- Continue for other sub-controls...

Risk Triggers

-- Create risk triggers
INSERT INTO risk_triggers (id, enterprise_id, name, description, archived)
VALUES
  ('rt-001', '550e8400-e29b-41d4-a716-446655440001', 'Rising Unemployment Rate', 'Unemployment rate exceeds 12%', false),
  ('rt-002', '550e8400-e29b-41d4-a716-446655440001', 'Increased Cyber Threat Alerts', 'Critical security alerts targeting financial institutions', false),
  ('rt-003', '550e8400-e29b-41d4-a716-446655440001', 'Regulatory Inspection Notice', 'Formal inspection notice from regulator', false);

Sample Business Risk Assessment

Create BRA

When a BRA transitions from draft to in_progress, the system captures the current risk appetite level as snapshot_appetite_level. This ensures that changes to the enterprise’s risk appetite don’t affect assessments already in progress.

-- Create a BRA (requires legal_entity_id)
-- snapshot_appetite_level is captured automatically when status changes to in_progress
INSERT INTO business_risk_assessments (
  id, enterprise_id, legal_entity_id, business_unit_id, 
  name, description, status, period, assessor, start_date,
  snapshot_appetite_level
)
VALUES (
  'bra-001',
  '550e8400-e29b-41d4-a716-446655440001',
  'le-001',  -- ACME Bank Brasil S.A.
  'bu-001',  -- Retail Banking
  'Q1 2026 Retail Banking Assessment',
  'Comprehensive risk assessment for retail operations',
  'in_progress',
  'Q1 2026',
  'assessor@acme.com',
  '2026-01-01',
  'Medium'  -- Captured from enterprise risk appetite at time of BRA creation
);

BRA Status Workflow

Status	Description	Risk Appetite
`draft`	Initial creation, not started	Uses current enterprise appetite
`in_progress`	Assessment underway	Uses `snapshot_appetite_level` (frozen)
`pending_review`	Submitted for review	Uses `snapshot_appetite_level`
`approved`	Reviewed and approved	Uses `snapshot_appetite_level`
`rejected`	Returned for revisions	Uses `snapshot_appetite_level`

Add Risk Scenarios to BRA

-- Link risk scenarios to BRA
INSERT INTO bra_risk_scenarios (id, bra_id, risk_scenario_id, name, description, category, included)
VALUES
  ('brs-001', 'bra-001', 'rs-001', 'Consumer Loan Default Risk', 'Risk of consumer loan defaults', 'Credit Risk', true),
  ('brs-002', 'bra-001', 'rs-002', 'Cyberattack on Digital Banking Platform', 'Risk of cyber attacks', 'Operational Risk', true),
  ('brs-003', 'bra-001', 'rs-003', 'AML Control Failure', 'Risk of failing to detect suspicious transactions', 'Compliance Risk', true);

Create Risk Ratings

-- Create inherent and residual risk ratings
-- Risk Score = Impact × Likelihood (1-25)
-- Risk Level is determined by the 5×5 risk matrix (not by score thresholds)
-- See "Risk Matrix" section below for the complete mapping

INSERT INTO bra_risk_ratings (id, bra_id, bra_risk_scenario_id, rating_type, impact_score, likelihood_score, risk_score, risk_level, justification)
VALUES
  -- Inherent ratings (risk_level based on matrix lookup, not score)
  -- Impact 4 (High) × Likelihood 4 (Likely) = Very High
  ('brr-001', 'bra-001', 'brs-001', 'inherent', 4, 4, 16, 'Very High', 'High economic uncertainty and rising consumer debt levels'),
  -- Impact 5 (Severe) × Likelihood 4 (Likely) = Very High
  ('brr-002', 'bra-001', 'brs-002', 'inherent', 5, 4, 20, 'Very High', 'Sophisticated threat landscape targeting financial institutions'),
  -- Impact 5 (Severe) × Likelihood 3 (Possible) = Very High
  ('brr-003', 'bra-001', 'brs-003', 'inherent', 5, 3, 15, 'Very High', 'Complex transaction patterns and evolving regulatory requirements'),
  
  -- Residual ratings (after controls)
  ('brr-004', 'bra-001', 'brs-001', 'residual', 3, 2, 6, 'Medium', 'Credit scoring and collection processes reduce risk'),
  ('brr-005', 'bra-001', 'brs-002', 'residual', 3, 2, 6, 'Medium', 'MFA and security operations significantly mitigate risk'),
  ('brr-006', 'bra-001', 'brs-003', 'residual', 3, 2, 6, 'Medium', 'Real-time monitoring and PEP screening reduce risk');

Sample Risk Appetite

Risk Appetite is configured at the enterprise level. When a BRA is created and transitions to in_progress, the current appetite level is captured as snapshot_appetite_level on the BRA. This ensures that subsequent changes to the enterprise’s risk appetite don’t affect assessments already in progress.

-- Configure enterprise risk appetite
-- This sets the maximum acceptable risk level for new assessments
INSERT INTO risk_appetite (id, enterprise_id, risk_level, threshold_value, description, legal_entity_id)
VALUES
  ('ra-001', '550e8400-e29b-41d4-a716-446655440001', 'Medium', 9, 'Enterprise accepts Medium risk (score ≤9) as maximum tolerance', NULL);

-- Optional: Entity-specific override for stricter requirements
INSERT INTO risk_appetite (id, enterprise_id, risk_level, threshold_value, description, legal_entity_id)
VALUES
  ('ra-002', '550e8400-e29b-41d4-a716-446655440001', 'Low', 4, 'Lower appetite for insurance subsidiary per regulatory requirement', 'le-002');

Risk Appetite Snapshot Behavior

Scenario	Behavior
Enterprise changes appetite from Medium → High	Existing `in_progress` BRAs keep their `snapshot_appetite_level` (Medium)
New BRA created	Captures current enterprise appetite as `snapshot_appetite_level`
BRA in `draft` status	Uses current enterprise appetite (not yet snapshotted)
BRA transitions to `in_progress`	`snapshot_appetite_level` is captured and frozen

Sample Mitigation Actions

-- Create mitigation actions (table is 'mitigation_actions', not 'action_plans')
INSERT INTO mitigation_actions (
  id, enterprise_id, bra_id, bra_risk_scenario_id,
  action, owner, status, priority, due_date, action_type, archived
)
VALUES
  (
    'ma-001',
    '550e8400-e29b-41d4-a716-446655440001',
    'bra-001',
    'brs-002',
    'Implement additional endpoint detection and response (EDR) solution',
    'security@acme.com',
    'in_progress',
    'high',
    '2026-03-31',
    'Technology',
    false
  ),
  (
    'ma-002',
    '550e8400-e29b-41d4-a716-446655440001',
    'bra-001',
    'brs-001',
    'Enhance credit scoring model with additional economic indicators',
    'credit.risk@acme.com',
    'created',
    'medium',
    '2026-06-30',
    'Process',
    false
  ),
  (
    'ma-003',
    '550e8400-e29b-41d4-a716-446655440001',
    'bra-001',
    'brs-003',
    'Conduct AML training for all customer-facing staff',
    'compliance@acme.com',
    'created',
    'high',
    '2026-04-30',
    'Training',
    false
  );

API Testing Examples

Create BRA via API

curl -X POST http://localhost:8000/api/v1/bras \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Q1 2026 Corporate Banking Assessment",
    "description": "Risk assessment for corporate banking operations",
    "legal_entity_id": "le-001",
    "business_unit_id": "bu-002",
    "period": "Q1 2026",
    "assessor": "assessor@acme.com"
  }'

Add Risk Scenario via API

curl -X POST http://localhost:8000/api/v1/bras/$BRA_ID/scenarios \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "risk_scenario_id": "rs-001",
    "included": true
  }'

Create Risk Rating via API

curl -X POST http://localhost:8000/api/v1/bras/$BRA_ID/ratings \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "bra_risk_scenario_id": "brs-001",
    "rating_type": "inherent",
    "impact_score": 4,
    "likelihood_score": 3,
    "justification": "Based on current economic conditions and portfolio analysis"
  }'

Create Product via API

# Note: Products no longer have a category field
curl -X POST http://localhost:8000/api/v1/products \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Mobile Banking App",
    "description": "Full-featured mobile banking application for retail customers",
    "customer_types": ["Retail Customer", "Small & Medium Enterprise"],
    "geographic_operations": ["Americas", "Brazil"],
    "distribution_channels": ["Mobile App"],
    "transaction_types": ["Internal Transfers (A2A)", "Domestic Payments", "Card Payments (POS)"]
  }'

Update Control Effectiveness via API (Control Assurance)

# ToD/ToE ratings are assessed in Control Assurance, not during sub-control creation
curl -X PATCH http://localhost:8000/api/v1/controls/sub-controls/sc-001 \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "tod": "A",
    "toe": "2",
    "testing_date": "2026-01-15",
    "tested_by": "John Smith",
    "tod_justification": "Control design is comprehensive with documented procedures and automated checks",
    "toe_justification": "Sample testing showed 95% effectiveness rate across 150 transactions"
  }'

Create Sub-Control via API (Governance)

# Sub-controls are created with name and description only
# ToD/ToE ratings are assessed separately in Control Assurance
curl -X POST http://localhost:8000/api/v1/controls/kc-001/sub-controls \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Debt-to-Income Ratio Check",
    "description": "Automated check ensuring borrower debt-to-income ratio is within acceptable limits"
  }'

Approve BRA via API

curl -X POST http://localhost:8000/api/v1/bras/$BRA_ID/approve \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "final_comment": "Assessment reviewed and approved. All risks adequately assessed with appropriate controls."
  }'

Verification Queries

Check Data Counts

SELECT 
  (SELECT COUNT(*) FROM enterprises) as enterprises,
  (SELECT COUNT(*) FROM legal_entities WHERE archived = false) as legal_entities,
  (SELECT COUNT(*) FROM business_units WHERE archived = false) as business_units,
  (SELECT COUNT(*) FROM products WHERE archived = false) as products,
  (SELECT COUNT(*) FROM risk_scenarios WHERE archived = false) as risk_scenarios,
  (SELECT COUNT(*) FROM key_controls WHERE archived = false) as key_controls,
  (SELECT COUNT(*) FROM sub_controls WHERE archived = false) as sub_controls,
  (SELECT COUNT(*) FROM business_risk_assessments) as bras,
  (SELECT COUNT(*) FROM mitigation_actions WHERE archived = false) as actions;

Check BRA Status

SELECT 
  bra.name,
  bra.status,
  le.name as legal_entity,
  bu.name as business_unit,
  COUNT(brs.id) as scenario_count
FROM business_risk_assessments bra
JOIN legal_entities le ON le.id = bra.legal_entity_id
LEFT JOIN business_units bu ON bu.id = bra.business_unit_id
LEFT JOIN bra_risk_scenarios brs ON brs.bra_id = bra.id
GROUP BY bra.id, bra.name, bra.status, le.name, bu.name;

Check Control Effectiveness

SELECT 
  kc.name as key_control,
  sc.name as sub_control,
  sc.tod,
  sc.toe,
  sc.total_effectiveness,
  sc.testing_date
FROM sub_controls sc
JOIN key_controls kc ON kc.id = sc.key_control_id
WHERE sc.archived = false
ORDER BY kc.name, sc.name;

Data Model Reference

ToD Rating Scale

Grade	Meaning
A	Excellent - Comprehensive design
B	Good - Well-structured with minor gaps
C	Adequate - Meets minimum requirements
D	Weak - Significant gaps
E	Inadequate - Fundamentally flawed

ToE Rating Scale

Grade	Meaning
1	Highly Effective (95%+)
2	Effective (85-95%)
3	Moderately Effective (70-85%)
4	Less Effective (50-70%)
5	Ineffective (<50%)

Risk Matrix

Risk level is determined by the combination of Impact and Likelihood using the following 5×5 matrix:

Impact ↓ / Likelihood →	A (Rare)	B (Unlikely)	C (Possible)	D (Likely)	E (Frequent)
5 - Severe	Medium	High	Very High	Very High	Very High
4 - High	Medium	High	High	Very High	Very High
3 - Moderate	Low	Medium	High	High	Very High
2 - Minor	Low	Low	Medium	High	High
1 - Negligible	Low	Low	Low	Medium	Medium

Risk Level Colors

Level	Color	Meaning
Low	Green	Acceptable risk, monitor only
Medium	Yellow	Requires attention, consider mitigation
High	Orange	Significant risk, mitigation required
Very High	Red	Critical risk, immediate action required

Next Steps

Create Test Users

Use scripts to create users with all roles

Seed Enterprise Data

Run SQL scripts to populate organization structure

Create Risk Library

Add scenarios, controls, and triggers

Create and Complete BRA

Walk through full BRA workflow

Test API Endpoints

Verify all endpoints work correctly

​Overview

​Key Data Model Notes

​Quick Start

​1. Create Test Users

​2. Get JWT Tokens

​Sample Enterprises

​Sample Organization Structure

​Legal Entities

​Business Units

​Products

​Valid Enum Values for Products

​Sample Risk Library

​Risk Scenarios

​Valid Enum Values for Risk Scenarios

​Key Controls

​Sub-Controls

​Step 1: Create Sub-Controls (Governance)

​Step 2: Assess Sub-Controls (Control Assurance)

​Risk Triggers

​Sample Business Risk Assessment

​Create BRA

​BRA Status Workflow

​Add Risk Scenarios to BRA

​Create Risk Ratings

​Sample Risk Appetite

​Risk Appetite Snapshot Behavior

​Sample Mitigation Actions

​API Testing Examples

​Create BRA via API

​Add Risk Scenario via API

​Create Risk Rating via API

​Create Product via API

​Update Control Effectiveness via API (Control Assurance)

​Create Sub-Control via API (Governance)

​Approve BRA via API

​Verification Queries

​Check Data Counts

​Check BRA Status

​Check Control Effectiveness

​Data Model Reference

​ToD Rating Scale

​ToE Rating Scale

​Risk Matrix

​Risk Level Colors

​Next Steps

Overview

Key Data Model Notes

Quick Start

1. Create Test Users

2. Get JWT Tokens

Sample Enterprises

Sample Organization Structure

Legal Entities

Business Units

Products

Valid Enum Values for Products

Sample Risk Library

Risk Scenarios

Valid Enum Values for Risk Scenarios

Key Controls

Sub-Controls

Step 1: Create Sub-Controls (Governance)

Step 2: Assess Sub-Controls (Control Assurance)

Risk Triggers

Sample Business Risk Assessment

Create BRA

BRA Status Workflow

Add Risk Scenarios to BRA

Create Risk Ratings

Sample Risk Appetite

Risk Appetite Snapshot Behavior

Sample Mitigation Actions

API Testing Examples

Create BRA via API

Add Risk Scenario via API

Create Risk Rating via API

Create Product via API

Update Control Effectiveness via API (Control Assurance)

Create Sub-Control via API (Governance)

Approve BRA via API

Verification Queries

Check Data Counts

Check BRA Status

Check Control Effectiveness

Data Model Reference

ToD Rating Scale

ToE Rating Scale

Risk Matrix

Risk Level Colors

Next Steps