Endpoint
Query Parameters
The Nessie API customer ID to retrieve financial data for.
Response
Returns an aggregated financial profile with calculated metrics.Total liquid assets from checking and savings accounts.
Total credit card debt across all credit card accounts.
Total outstanding loan principal across all loans.
Sum of all monthly loan payment obligations.
Estimated monthly income based on salary deposits. Calculated by identifying direct deposit/salary transactions and converting bi-weekly amounts to monthly (amount × 2).
Sum of all recurring bills associated with the checking account.
Total estimated monthly spending including purchases, recurring bills, and loan payments. Purchases are averaged over 12 months of historical data.
Breakdown of spending by merchant category. Keys are category names, values are total amounts spent in each category.
Calculated volatility metric (0.0 - 0.3) representing variance in spending patterns. Derived from category-level spending variance, with a default of 0.15. Higher values indicate more unpredictable spending.
Example Request
Example Response
Implementation Details
Data Aggregation Process
- Account Retrieval: Fetches all accounts for the customer
- Liquid Assets: Sums balances from Checking and Savings accounts
- Credit Debt: Sums balances from Credit Card accounts
- Transaction Analysis: From the checking account:
- Retrieves all purchases and maps to merchant categories
- Identifies salary/direct deposit transactions
- Fetches recurring bills
- Retrieves loan information
- Calculations:
- Monthly purchases averaged over 12 months
- Monthly income from bi-weekly salary (amount × 2)
- Spending volatility from category variance
Error Responses
Error message describing what went wrong.
Usage Notes
- This endpoint is typically called before running simulations to get current financial state
- The response can be used directly as the
financialProfilefield in simulation requests - Income calculation assumes bi-weekly pay periods; adjust if your data uses different frequencies
- 12 months of purchase history is used for averaging; less data may reduce accuracy