Reach new audiences and convert more users by easily and safely connecting to their financial data, understanding their behavior and enabling instant payments with open finance. Through our API, you can access:
Belvo is an open banking API for Latin America that allows companies to access banking and fiscal information in a secure as well as agile way.
Through our API, you can access:
You can also use our API to make payments in:
If you woud like the response documentation in Excel or CSV form, please download them from our public GitHub Reposiitory: Belvo Open Finance Data Dictionaries.
Our EXCEL and CSV files are additionally localized into Spanish and Portuguese (Brazil).
Available for:
Use our Sandbox environment to build your integration. We offer dummy data that mimics that of real-world use cases, which means you can test out all the endpoints, use the widget, and implement webhooks - just as you would with real-world data!
All you need to get started with the Sandbox environment is to get your API keys. We really recommend that you start creating your integration in this environment.
Available for:
After you have tested your integration in the Sandbox environment and are ready to go live, you'll need to request access to our Production environment. After you request access, our Sales Team will get in contact with you to schedule a meeting just to ensure your needs are met, and then you'll just need to go through a certification process with one of our engineers to make sure that your integration is running optimally. To prepare for the certification meeting, just follow our Integration checklist.
Once your integration is certified, all you'll need to do is:
sandbox.belvo.com to api.belvo.com.We use the following HTTP status code in the response depending on the success or failure:
| Status Code | Description |
|---|---|
200 | ✅ Success - The content is available in the response body. |
201 | ✅ Success - The content was created successfully on Belvo. |
204 | ✅ Success - No content to return. |
400 | ❌ Bad Request Error - Request returned an error, detail in the content. |
401 | ❌ Unauthorized - The Belvo credentials provided are not valid. |
404 | ❌ Not Found - The resource you try to access cannot be found. |
405 | ❌ Method Not Allowed - The HTTP method you are using is not accepted for this resource. |
408 | ❌ Request Timeout - The request timed out and was terminated by the server. |
428 | ❌ MFA Token Required - MFA token was required by the institution to connect. |
500 | ❌ Internal Server Error - The detail of the error is available in the response body. |
Belvo API errors are returned in JSON format. For example, an error might look like this:
[
{
"request_id": "a6e1c493d7a29d91aed4338e6fcf077d",
"message": "This field is required.",
"code": "required",
"field": "link"
}
]Typically, an error response will have the following parameters:
request_id: a unique ID for the request, you should share it with the Belvo support team for investigations.message: human-readable description of the error.code: a unique code for the error. Check the table below to see how to handle each error code.field (optional): The specific field in the request body that has an issue.When you need help with a specific error, include the request identifier (request_id) in your message to the Belvo support team. This will speed up investigations and get you back up and running in no time at all.
For a full list of errors and how to troubleshoot them, please see our dedicated Error Handling article.
Implement an automated exponential backoff of up to five retries. We recommend using a base interval of three seconds with a factor of two. For example, the first retry should be after three seconds, the second retry after six seconds (2 * 3), the third retry after 12 seconds (2 * 6), the fourth retry after 24 seconds (2 * 12), and the fifth retry after 48 seconds (2 * 24).
You should not retry making requests if you receive a 40x response, as this is a client error.
The only exception is the “Too Many Sessions” error, as it means that your end-user is accessing the account from another browser at the same time. In this case, please implement the same retry policy as with 50x errors.
In our schema, you may see that a field has been marked as deprecated. This means that this field is no longer maintained by the Belvo team. You may still receive data for this field depending on the institution, however, you should not rely on this field.
In our API specification, you'll see that some response parameters will have a required annotation. According to the OpenAPI specification, when a response parameter is marked as required, this means that the response key must be returned. However, the value of that response parameter can be null.
📘 Info
In short, any response parameter marked as required will be returned by our API, but the value can be set to null.
An institution is an entity that Belvo can access information from. It can be a:
You can see a complete list of institutions by either consulting our Institutions article or making a List request to this endpoint.
An owner represents the person who has access to a Link and is the owner of all the accounts inside the Link.
You can use this endpoint in order to get useful information about your client, such as:
An account is the representation of a bank account inside a financial institution. A user can have one or more accounts in an institution.
For example, one user (or link) can have a checking account, several credit cards, and a loan account.
Querying for a user's account information is useful as you can get information regarding:
Our employments resource for Brazil lets you get a comprehensive view of your user's current employment history and salary information.
For each user, we return the:
At the moment, the employments resource is available for:
Our employment records resource for Mexico lets you get a comprehensive view of your user’s current social security contributions and employment history.
With Belvo's employment records resource for Mexico, you can access information about your user's current social security contributions and employment history. For the each user, we return the:
At the moment, the employment records resource is available for:
Belvo's Recurring Expenses API allows you to identify a user's regular payments for subscription services, such as Netflix or gym memberships, as well as utility payments, such as electricity or phone bills. We return information for up to 365 days.
📘 Info
The recurring expenses resource is only available for Checking, Savings and Credit Card accounts associated with banking links.
Belvo's unique identifier for the current item.
The link.id the data belongs to.
The ISO-8601 timestamp of when the data point was created in Belvo's database.
An array of Belvo-generated account numbers (UUIDs) that were used during the risk insights analysis. If no accounts were found, we return an empty array.
Aggregate details regarding the assets used in the risk insight analysis. For asset metrics, we only consider checking and savings accounts.
Asset metrics can provide a snapshot of your user's wealth and liquid assets, indicating how they manage their wealth and their current financial status.
An array of institutions from which account information was retrieved for the user.
Note: For most use cases, this array will only return one item.
The total number of accounts found for the user.
The total number of checking accounts found for the user.
The total number of savings accounts found for the user.
The total closing balance of all checking accounts.
Aggregated metrics calculated based on the user's credit card accounts.
Credit card metrics illustrate a customer's credit card habits, revealing how many credit card accounts a customer has, their total credit limit, how much of that limit they're using, and the rate of their credit card limit utilization.
Number of credit cards accounts associated to the user.
Aggregated metrics calculated based on the user's loan accounts and checking accounts that have an overdraft.
Loan metrics help in understanding a customer's borrowing and repayment behavior, which can help in assessing their ability to take on additional credit and potential default risks.
Sum total of the principal for all of the user's loan accounts.
Sum total of the outstanding principal for all the user's loan accounts.
Sum total of the monthly payments for all the user's loan accounts.
The percentage of the loan limit used.
The total overdraft limit of all checking and savings accounts.
Balance metrics calculated based on the user's balances from checking and savings accounts.
The balance of all the accounts at the collected_at time.
The minimum balance in the last three days.
The minimum balance in the last three months.
The minimum balance in the six last months.
The minimum balance in the last twelve months.
The mean balance in the last three days.
The mean balance in the last three months.
The mean balance in the last six months.
The mean balance in the last twelve months.
The maximum balance in the last three days.
The maximum balance in the last three months.
The maximum balance in the last six months.
The maximum balance in the last twelve months.
The balance standard deviation in the last three days.
The balance standard deviation in the last week.
The balance standard deviation in the last month.
The balance standard deviation in the last three months.
The balance standard deviation in the last six months.
The balance standard deviation in the last twelve months.
The balance trend of the user in the last three days.
The balance trend of the user in the last week.
The balance trend of the user in the last month.
The balance trend of the user in the last three months.
The balance trend of the user in the last six months.
The balance trend of the user in the last twelve months.
The number of days that the total balance of the account is less than or equal to 0 in the last three days.
The number of days that the total balance of the account is less than or equal to 0 in the last week.
The number of days that the total balance of the account is less than or equal to 0 in the last month.
The number of days that the total balance of the account is less than or equal to 0 in the last three months.
The number of days that the total balance of the account is less than or equal to 0 in the last six months.
The number of days that the total balance of the account is less than or equal to 0 in the last twelve months.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_3d.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_1w.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_1m.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_3m.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_6m.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_12m.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last three days.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last week.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last month.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last three months.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last six months.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last twelve months.
Aggregated metrics calculated based on the user's transactions from checking, savings, credit card, and loan accounts.
ℹ️ Note
If there is not enough transactional data for a given period, we return
nullfor calculated fields and0for 'count-based' fields. For example, if the account has only been open for five days (or you have provided data just for five days), we return values for_3d,_1w, and_1m, however:
mean_num_transactions_3mwill returnnullas there is no data for months two and three (calculated field).num_transactions_3mwill return0as there is no data for months two and three ('count-based' field)
The total number of transactions analyzed to determine the risk insights for the last three days (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last week (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last month (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last three months (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last six months (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last twelve months (incoming and outgoing).
The maximum number of transactions for the last three days.
The maximum number of transactions for the last week.
The maximum number of transactions for the last month.
The maximum number of transactions for the last three months.
The maximum number of transactions for the last six months.
The maximum number of transactions for the last twelve months.
The mean number of transactions for the last three days.
The mean number of transactions for the last week.
The mean number of transactions for the last month.
The mean number of transactions for the last three months.
The mean number of transactions for the last six months.
The mean number of transactions for the last twelve months.
The total number of inflow transactions for the last three days.
The total number of inflow transactions for the last week.
The total number of inflow transactions for the last month.
The total number of inflow transactions for the last three months.
The total number of inflow transactions for the last six months.
The total number of inflow transactions for the last twelve months.
The maximum number of inflow transactions for the last three days.
The maximum number of inflow transactions for the last week.
The maximum number of inflow transactions for the last month.
The maximum number of inflow transactions for the last three months.
The maximum number of inflow transactions for the last six months.
The maximum number of inflow transactions for the last twelve months.
The mean number of inflow transactions for the last three days.
The mean number of inflow transactions for the last week.
The mean number of inflow transactions for the last month.
The mean number of inflow transactions for the last three months.
The mean number of inflow transactions for the last six months.
The mean number of inflow transactions for the last twelve months.
The total sum of all inflow transactions for the last three days.
The total sum of all inflow transactions for the last week.
The total sum of all inflow transactions for the last month.
The total sum of all inflow transactions for the last three months.
The total sum of all inflow transactions for the last six months.
The total sum of all inflow transactions for the last twelve months.
The highest value inflow transaction in the last three days.
The highest value inflow transaction in the last week.
The highest value inflow transaction in the last month.
The highest value inflow transaction in the last three months.
The highest value inflow transaction in the last six months.
The highest value inflow transaction in the last twelve months.
The mean incoming value of all transactions in the last three days.
The mean incoming value of all transactions in the last week.
The mean incoming value of all transactions in the last month.
The mean incoming value of all transactions in the last three months.
The mean incoming value of all transactions in the last six months.
The mean incoming value of all transactions in the last twelve months.
To total number of outflow transactions in the last three days.
To total number of outflow transactions in the last week.
To total number of outflow transactions in the last month.
To total number of outflow transactions in the last three months.
To total number of outflow transactions in the last six months.
To total number of outflow transactions in the last twelve months.
The maximum number of outflow transactions for the last three days.
The maximum number of outflow transactions for the last week.
The maximum number of outflow transactions for the last month.
The maximum number of outflow transactions for the last three months.
The maximum number of outflow transactions for the last six months.
The maximum number of outflow transactions for the last twelve months.
The mean number of outflow transactions for the last three days.
The mean number of outflow transactions for the last week.
The mean number of outflow transactions for the last month.
The mean number of outflow transactions for the last three months.
The mean number of outflow transactions for the last six months.
The mean number of outflow transactions for the last twelve months.
The total sum of all outflow transactions for the last three days.
The total sum of all outflow transactions for the last week.
The total sum of all outflow transactions for the last month.
The total sum of all outflow transactions for the last three months.
The total sum of all outflow transactions for the last six months.
The total sum of all outflow transactions for the last twelve months.
The highest value outflow transaction in the last three days.
The highest value outflow transaction in the last week.
The highest value outflow transaction in the last month.
The highest value outflow transaction in the last three months.
The highest value outflow transaction in the last six months.
The highest value outflow transaction in the last twelve months.
The mean outgoing value of all transaction in the last three days.
The mean outgoing value of all transaction in the last week.
The mean outgoing value of all transaction in the last month.
The mean outgoing value of all transaction in the last three months.
The mean outgoing value of all transaction in the last six months.
The mean outgoing value of all transaction in the last twelve months.
The number of days that no transactions occurred within the last three days.
The number of days that no transactions occurred within the last week.
The number of days that no transactions occurred within the last month.
The number of days that no transactions occurred within the last three months.
The number of days that no transactions occurred within the last six months.
The number of days that no transactions occurred within the last twelve months.
The number of days since the last transaction occurred.
The number of days since the last inflow transaction occurred.
The number of days since the last outflow transaction occurred.
Aggregate metrics calculated based on the user's transactions from checking, savings, credit, and loan accounts. However, internal transfers (transfers between accounts belonging to the same link) are not used in the calculation.
ℹ️ Note
If there is not enough transactional data for a given period, we return
null. For example, if the account has only been open for 15 days (or you have only provided data for just 15 days), we return values for_3d,_1w, and_1m, however for_3mwe will returnnullas there is no data for months two and three.
The highest value of positive cash flow transactions in the last three days.
The highest value of positive cash flow transactions the last week.
The highest value of positive cash flow transactions the last month.
The highest value of positive cash flow transactions the last three months.
The highest value of positive cash flow transactions the last six months.
The highest value of positive cash flow transactions the last twelve months.
The highest value of negative cash flow transactions in the last three days.
The highest value of negative cash flow transactions in the last week.
The highest value of negative cash flow transactions in the last month.
The highest value of negative cash flow transactions in the last three months.
The highest value of negative cash flow transactions in the last six months.
The highest value of negative cash flow transactions in the last twelve months.
The mean value of the positive cash flow transactions in the last three days.
The mean value of the positive cash flow transactions in the last week.
The mean value of the positive cash flow transactions in the last month.
The mean value of the positive cash flow transactions in the last three months.
The mean value of the positive cash flow transactions in the last six months.
The mean value of the positive cash flow transactions in the last twelve months.
The mean value of the negative cash flow transactions in the last three days.
The mean value of the negative cash flow transactions in the last week.
The mean value of the negative cash flow transactions in the last month.
The mean value of the negative cash flow transactions in the last three months.
The mean value of the negative cash flow transactions in the last six months.
The mean value of the negative cash flow transactions in the last twelve months.
The sum total of all transactions leading to a positive cash flow in the last three days.
The sum total of all transactions leading to a positive cash flow in the last week.
The sum total of all transactions leading to a positive cash flow in the last month.
The sum total of all transactions leading to a positive cash flow in the last three months.
The sum total of all transactions leading to a positive cash flow in the last six months.
The sum total of all transactions leading to a positive cash flow in the last twelve months.
The positive cash flow trend based on the sum of all positive transactions in the last three days.
The positive cash flow trend based on the sum of all positive transactions in the last week.
The positive cash flow trend based on the sum of all positive transactions in the last month.
The positive cash flow trend based on the sum of all positive transactions in the last three months.
The positive cash flow trend based on the sum of all positive transactions in the last six months.
The positive cash flow trend based on the sum of all positive transactions in the last twelve months.
The sum total of all transactions leading to a negative cash flow in the last three days.
The sum total of all transactions leading to a negative cash flow in the last week.
The sum total of all transactions leading to a negative cash flow in the last month.
The sum total of all transactions leading to a negative cash flow in the last three months.
The sum total of all transactions leading to a negative cash flow in the last six months.
The sum total of all transactions leading to a negative cash flow in the last twelve months.
The negative cash flow trend based on the sum of all negative transactions in the last three days.
The negative cash flow trend based on the sum of all negative transactions in the last week.
The negative cash flow trend based on the sum of all negative transactions in the last month.
The negative cash flow trend based on the sum of all negative transactions in the last three months.
The negative cash flow trend based on the sum of all negative transactions in the last six months.
The negative cash flow trend based on the sum of all negative transactions in the last twelve months.
The ratio between sum_positive / sum_negative in the last three days.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last week.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last month.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last three months.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last six months.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last twelve months.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The net cash flow in the last three days.
The net cash flow in the last three months.
The net cash flow in the last six months.
The net cash flow in the last twelve months.
The net cash flow trend in the last three days months.
The net cash flow trend in the last week.
The net cash flow trend in the last month.
The net cash flow trend in the last three months.
The net cash flow trend in the last six months.
An array of aggregate metrics regarding the transaction categories and subcategories that Belvo has identified within the user's transaction history.
In the array, Belvo only returns categories that have been identified.
The name of the transaction category.
Get transaction categorization With Transaction categorization, we clean and categorize transactions for you, turning raw data into actionable insights. To enable this feature, just reach out to us, and we'll get right to it.
We return one of the following enum values:
Bills & UtilitiesCredits & LoansDepositsFees & ChargesFood & GroceriesHome & LifeIncome & PaymentsInsuranceInvestments & SavingsOnline Platforms & LeisurePersonal ShoppingTaxesTransfersTransport & TravelUnknown*Withdrawal & ATMnull* For clients not using our Transaction Categorization product, we return null instead.
The transaction subcategory.
Get transaction categorization For clients not using our Transaction categorization, we return
nullinstead. To enable this feature, just reach out to us, and we'll get right to it.
We return one of the following enum values:
Electricity & EnergyRentTelecommunicationsWaterAutoCredit CardInstalmentInterest & ChargesMortgagePay AdvancePersonalAdjustmentsBank FeesChargebackRefundBlocked BalancesAlimonyAlcohol & TobaccoBakery & CoffeeBars & NightclubsConvenience StoreDeliveryGroceriesRestaurantsEducationGyms & FitnessHair & BeautyHealthHome Decor & AppliancesLaundry & Dry CleaningPharmaciesProfessional ServicesVeterinary ServicesFreelanceInterestRetirementSalaryGovernmentHome InsuranceAuto InsuranceHealth & Life InsuranceSavingsFixed incomeEquityInvestment FundsDerivativesCryptocurrenciesApps, Software and Cloud ServicesEvents, Parks and MuseumsGamblingGamingLotteryMovie & AudioBooks & NewsClothing & AccessoriesDepartment StoreElectronicsE-commerceGiftsOffice SuppliesPet SuppliesAuto Tax & FeesDonationGovernment FeesIncome TaxReal Estate Tax & FeesTax ReturnAccommodationAuto ExpensesAuto RentalFlightsGasMileage ProgramsParking & TollsPublic TransitTaxis & RidesharesOthernullThe net amount of the transactions for this category in the last three months (calculated as the total incoming - total outgoing transactions for this category).
The ratio of net_amount_3m divided by the sum of all incoming categorized transactions (including the current category) for the same period.
Note: If there are no inflow transactions for the period, this value will return null.
{ "id": "0d3ffb69-f83b-456e-ad8e-208d0998d71d", "link": "30cb4806-6e00-48a4-91c9-ca55968576c8", "created_at": "2022-02-09T08:45:50.406032Z", "accounts": [ "0d3ffb69-f83b-456e-ad8e-208d0998d71d", "00293c8e-1152-440b-9892-3c071fb88672", "cf638fba-ef45-4c10-bc6f-adecc4b2bf4e", "3861a5da-ae9b-4f20-a632-a9294489d5ac", "1f60315b-236d-498e-be7a-92bc613d329b", "a2c8da63-ed51-41e6-891a-4ae7e784463a" ], "assets_metrics": { "institutions": [ … ], "num_assets_accounts": 1, "num_checking_accounts": 1, "num_savings_accounts": 1, "checking_accounts_balance": 35901.46, "savings_accounts_balance": 300.02 }, "credit_cards_metrics": { "num_accounts": 2, "sum_credit_limit": 106560, "sum_credit_used": 101020.14, "credit_card_limit_utilization": 0.95 }, "loans_metrics": { "num_accounts": 1, "sum_loans_principal": 5000, "sum_loans_outstanding_principal": 2000, "sum_loans_monthly_payment": 400, "loan_limit_utilization": 0.3, "overdraft_limit": 900, "overdraft_limit_utilization": 0.4 }, "balances_metrics": { "closing_balance": 35901.46, "min_balance_3d": 35417.68, "min_balance_1w": 34150.5, "min_balance_1m": 33990.59, "min_balance_3m": 33990.59, "min_balance_6m": 33990.59, "min_balance_12m": 33990.59, "mean_balance_3d": 35659.57, "mean_balance_1w": 35077.1, "mean_balance_1m": 34816.08, "mean_balance_3m": 34816.08, "mean_balance_6m": 34816.08, "mean_balance_12m": 34816.08, "max_balance_3d": 35901.46, "max_balance_1w": 35901.46, "max_balance_1m": 35901.46, "max_balance_3m": 35901.46, "max_balance_6m": 35901.46, "max_balance_12m": 35901.46, "std_balance_3d": 279.31, "std_balance_1w": 764.03, "std_balance_1m": 586.55, "std_balance_3m": 586.55, "std_balance_6m": 586.55, "std_balance_12m": 586.55, "balance_trend_3d": 193.51, "balance_trend_1w": 290.18, "balance_trend_1m": 22.6, "balance_trend_3m": 22.6, "balance_trend_6m": 22.6, "balance_trend_12m": 22.6, "days_balance_below_0_3d": 0, "days_balance_below_0_1w": 0, "days_balance_below_0_1m": 0, "days_balance_below_0_3m": 0, "days_balance_below_0_6m": 0, "days_balance_below_0_12m": 0, "days_balance_below_mean_3d": 2, "days_balance_below_mean_1w": 3, "days_balance_below_mean_1m": 17, "days_balance_below_mean_3m": 17, "days_balance_below_mean_6m": 17, "days_balance_below_mean_12m": 17, "days_balance_below_x_3d": 0, "days_balance_below_x_1w": 0, "days_balance_below_x_1m": 0, "days_balance_below_x_3m": 0, "days_balance_below_x_6m": 0, "days_balance_below_x_12m": 0, "balance_threshold_x": 1000 }, "transactions_metrics": { "num_transactions_3d": 26, "num_transactions_1w": 46, "num_transactions_1m": 168, "num_transactions_3m": 460, "num_transactions_6m": 472, "num_transactions_12m": 496, "max_num_transactions_3d": 10, "max_num_transactions_1w": 10, "max_num_transactions_1m": 18, "max_num_transactions_3m": 18, "max_num_transactions_6m": 18, "max_num_transactions_12m": 18, "mean_num_transactions_3d": 6.5, "mean_num_transactions_1w": 5.75, "mean_num_transactions_1m": 5.42, "mean_num_transactions_3m": 5.05, "mean_num_transactions_6m": 2.61, "mean_num_transactions_12m": 1.37, "num_incoming_transactions_3d": 12, "num_incoming_transactions_1w": 21, "num_incoming_transactions_1m": 80, "num_incoming_transactions_3m": 229, "num_incoming_transactions_6m": 238, "num_incoming_transactions_12m": 256, "max_num_incoming_transactions_3d": 6, "max_num_incoming_transactions_1w": 6, "max_num_incoming_transactions_1m": 10, "max_num_incoming_transactions_3m": 10, "max_num_incoming_transactions_6m": 10, "max_num_incoming_transactions_12m": 10, "mean_num_incoming_transactions_3d": 3, "mean_num_incoming_transactions_1w": 2.62, "mean_num_incoming_transactions_1m": 2.58, "mean_num_incoming_transactions_3m": 2.52, "mean_num_incoming_transactions_6m": 1.31, "mean_num_incoming_transactions_12m": 0.71, "sum_incoming_amount_3d": 17142.16, "sum_incoming_amount_1w": 24825.92, "sum_incoming_amount_1m": 75993.36, "sum_incoming_amount_3m": 198197.28, "sum_incoming_amount_6m": 223697.28, "sum_incoming_amount_12m": 274697.28, "max_incoming_amount_3d": 3000, "max_incoming_amount_1w": 3000, "max_incoming_amount_1m": 3000, "max_incoming_amount_3m": 3000, "max_incoming_amount_6m": 3000, "max_incoming_amount_12m": 3000, "mean_incoming_amount_3d": 1428.51, "mean_incoming_amount_1w": 1182.19, "mean_incoming_amount_1m": 949.92, "mean_incoming_amount_3m": 865.49, "mean_incoming_amount_6m": 939.9, "mean_incoming_amount_12m": 1073.04, "num_outgoing_transactions_3d": 14, "num_outgoing_transactions_1w": 25, "num_outgoing_transactions_1m": 88, "num_outgoing_transactions_3m": 231, "num_outgoing_transactions_6m": 234, "num_outgoing_transactions_12m": 240, "max_num_outgoing_transactions_3d": 6, "max_num_outgoing_transactions_1w": 6, "max_num_outgoing_transactions_1m": 8, "max_num_outgoing_transactions_3m": 9, "max_num_outgoing_transactions_6m": 9, "max_num_outgoing_transactions_12m": 9, "mean_num_outgoing_transactions_3d": 3.5, "mean_num_outgoing_transactions_1w": 3.12, "mean_num_outgoing_transactions_1m": 2.84, "mean_num_outgoing_transactions_3m": 2.54, "mean_num_outgoing_transactions_6m": 1.29, "mean_num_outgoing_transactions_12m": 0.66, "sum_outgoing_amount_3d": 18246.95, "sum_outgoing_amount_1w": 26362.25, "sum_outgoing_amount_1m": 78243.82, "sum_outgoing_amount_3m": 192608.77, "sum_outgoing_amount_6m": 201608.77, "sum_outgoing_amount_12m": 219608.77, "max_outgoing_amount_3d": 3000, "max_outgoing_amount_1w": 3000, "max_outgoing_amount_1m": 3000, "max_outgoing_amount_3m": 3000, "max_outgoing_amount_6m": 3000, "max_outgoing_amount_12m": 3000, "mean_outgoing_amount_3d": 1303.35, "mean_outgoing_amount_1w": 1054.49, "mean_outgoing_amount_1m": 889.13, "mean_outgoing_amount_3m": 833.8, "mean_outgoing_amount_6m": 861.58, "mean_outgoing_amount_12m": 915.04, "days_without_transactions_3d": 0, "days_without_transactions_1w": 0, "days_without_transactions_1m": 0, "days_without_transactions_3m": 0, "days_without_transactions_6m": 87, "days_without_transactions_12m": 261, "days_since_last_transaction": 0, "days_since_last_incoming_transaction": 0, "days_since_last_outgoing_transaction": 0, "days_history": 365 }, "cashflow_metrics": { "max_positive_3d": 1850.12, "max_positive_1w": 3808.99, "max_positive_1m": 4012.61, "max_positive_3m": 5001.08, "max_positive_6m": 8500, "max_positive_12m": 8500, "max_negative_3d": 3375.43, "max_negative_1w": 3375.43, "max_negative_1m": 5305.92, "max_negative_3m": 7535.85, "max_negative_6m": 7535.85, "max_negative_12m": 7535.85, "mean_positive_3d": 1410.54, "mean_positive_1w": 1665.74, "mean_positive_1m": 1827.36, "mean_positive_3m": 1881.58, "mean_positive_6m": 2102.19, "mean_positive_12m": 2502.06, "mean_negative_3d": 3373.48, "mean_negative_1w": 2477.04, "mean_negative_1m": 1904.96, "mean_negative_3m": 1838.47, "mean_negative_6m": 1877.63, "mean_negative_12m": 1948.51, "sum_positive_3d": 5642.16, "sum_positive_1w": 13325.92, "sum_positive_1m": 52993.36, "sum_positive_3m": 163697.28, "sum_positive_6m": 189197.28, "sum_positive_12m": 240197.28, "sum_positive_trend_3d": 98.902, "sum_positive_trend_1w": -84.0393, "sum_positive_trend_1m": 22.7315, "sum_positive_trend_3m": 1.8398, "sum_positive_trend_6m": -17.1869, "sum_positive_trend_12m": -25.9856, "sum_negative_3d": 6746.95, "sum_negative_1w": 14862.25, "sum_negative_1m": 55243.82, "sum_negative_3m": 158108.77, "sum_negative_6m": 167108.77, "sum_negative_12m": 185108.77, "sum_negative_trend_3d": -3.91, "sum_negative_trend_1w": 254.2517, "sum_negative_trend_1m": 58.376, "sum_negative_trend_3m": 2.5895, "sum_negative_trend_6m": -1.4824, "sum_negative_trend_12m": -4.2394, "positive_to_negative_ratio_3d": 0.84, "positive_to_negative_ratio_1w": 0.9, "positive_to_negative_ratio_1m": 0.96, "positive_to_negative_ratio_3m": 1.04, "positive_to_negative_ratio_6m": 1.13, "positive_to_negative_ratio_12m": 1.3, "net_cashflow_3d": -1104.79, "net_cashflow_1w": -1536.33, "net_cashflow_1m": -2250.46, "net_cashflow_3m": 5588.51, "net_cashflow_6m": 22088.51, "net_cashflow_12m": 55088.51, "net_cashflow_trend_3d": 1448.683, "net_cashflow_trend_1w": 163.8856, "net_cashflow_trend_1m": 1.3034, "net_cashflow_trend_3m": -0.472, "net_cashflow_trend_6m": -15.1286, "net_cashflow_trend_12m": -21.5511 }, "category_metrics": [ { … } ] }
With the List Risk Insights method, you can:
link.id (using the link query parameter).risk-insight.id (using the id query parameter).This method returns a paginated response (default: 100 items per page). You can use the page_size query parameter to increase the number of items returned to a maximum of 1000 items. You can use the page query parameter to navigate through the results. For more details on how to navigate Belvo's paginated responses, see our Pagination Tips article.
Please see the query list below for a list of fields that you can filter your responses by. For more information on how to use filters, see our Filtering responses article.
The link.id you want to filter by.
ℹ️ We highly recommend adding the link.id filter in order to improve your performance.
Indicates how many results to return per page. By default we return 100 results per page.
ℹ️ The minimum number of results returned per page is 1 and the maximum is 1000. If you enter a value greater than 1000, our API will default to the maximum value (1000).
Omit certain fields from being returned in the response. For more information, see our Filtering responses DevPortal article.
Return only the specified fields in the response. For more information, see our Filtering responses DevPortal article.
Return results only for these link.ids.
The account.id you want to filter by.
ℹ️ We highly recommend adding either the link.id or the account.id filters in order to improve your performance.
Return results only for these account.ids.
Return information only for this resource id.
curl -i -X GET \
-u <username>:<password> \
'https://developers.belvo.com/_mock/apis/belvoopenapispec/api/risk-insights/?account=8848bd0c-9c7e-4f53-a732-ec896b11d4c4&account__in=85b77707-90ef-46fd-9059-5a757f24247a&fields=string&id=24ccab1d-3a86-4136-a6eb-e04bf52b356f&id__in=6b3dea0f-be29-49d1-aabe-1a6d588642e6&link=8848bd0c-9c7e-4f53-a732-ec896b11d4c4&link__in=5722d0ba-69d7-42dc-8ff5-33767b83c5d6&omit=string&page=1&page_size=100'Ok
The URL to next page of results. Each page consists of up to 100 items. If there are not enough results for an additional page, the value is null.
In our documentation example, we use {endpoint} as a placeholder value. In production, this value will be replaced by the actual endpoint you are currently using (for example, accounts or owners).
The URL to the previous page of results. If there is no previous page, the value is null.
{ "count": 130, "next": "https://sandbox.belvo.com/api/{endpoint}/?link=1bd948f7-245d-4313-b604-34d1044cb908page=2", "previous": null, "results": [ { … } ] }
Omit certain fields from being returned in the response. For more information, see our Filtering responses DevPortal article.
Return only the specified fields in the response. For more information, see our Filtering responses DevPortal article.
The link.id you want to retrieve information for.
The MFA token generated by the institution which is required to continue a session.
curl -i -X POST \
-u <username>:<password> \
'https://developers.belvo.com/_mock/apis/belvoopenapispec/api/risk-insights/?fields=string&omit=string' \
-H 'Content-Type: application/json' \
-d '{
"link": "c81a1dea-6dd6-4999-8b9f-541ee8197058",
"token": "1234ab",
"save_data": true
}'Ok (when save_data=false)
Belvo's unique identifier for the current item.
The link.id the data belongs to.
The ISO-8601 timestamp of when the data point was created in Belvo's database.
An array of Belvo-generated account numbers (UUIDs) that were used during the risk insights analysis. If no accounts were found, we return an empty array.
Aggregate details regarding the assets used in the risk insight analysis. For asset metrics, we only consider checking and savings accounts.
Asset metrics can provide a snapshot of your user's wealth and liquid assets, indicating how they manage their wealth and their current financial status.
An array of institutions from which account information was retrieved for the user.
Note: For most use cases, this array will only return one item.
The total number of accounts found for the user.
The total number of checking accounts found for the user.
The total number of savings accounts found for the user.
The total closing balance of all checking accounts.
Aggregated metrics calculated based on the user's credit card accounts.
Credit card metrics illustrate a customer's credit card habits, revealing how many credit card accounts a customer has, their total credit limit, how much of that limit they're using, and the rate of their credit card limit utilization.
Number of credit cards accounts associated to the user.
Aggregated metrics calculated based on the user's loan accounts and checking accounts that have an overdraft.
Loan metrics help in understanding a customer's borrowing and repayment behavior, which can help in assessing their ability to take on additional credit and potential default risks.
Sum total of the principal for all of the user's loan accounts.
Sum total of the outstanding principal for all the user's loan accounts.
Sum total of the monthly payments for all the user's loan accounts.
The percentage of the loan limit used.
The total overdraft limit of all checking and savings accounts.
Balance metrics calculated based on the user's balances from checking and savings accounts.
The balance of all the accounts at the collected_at time.
The minimum balance in the last three days.
The minimum balance in the last three months.
The minimum balance in the six last months.
The minimum balance in the last twelve months.
The mean balance in the last three days.
The mean balance in the last three months.
The mean balance in the last six months.
The mean balance in the last twelve months.
The maximum balance in the last three days.
The maximum balance in the last three months.
The maximum balance in the last six months.
The maximum balance in the last twelve months.
The balance standard deviation in the last three days.
The balance standard deviation in the last week.
The balance standard deviation in the last month.
The balance standard deviation in the last three months.
The balance standard deviation in the last six months.
The balance standard deviation in the last twelve months.
The balance trend of the user in the last three days.
The balance trend of the user in the last week.
The balance trend of the user in the last month.
The balance trend of the user in the last three months.
The balance trend of the user in the last six months.
The balance trend of the user in the last twelve months.
The number of days that the total balance of the account is less than or equal to 0 in the last three days.
The number of days that the total balance of the account is less than or equal to 0 in the last week.
The number of days that the total balance of the account is less than or equal to 0 in the last month.
The number of days that the total balance of the account is less than or equal to 0 in the last three months.
The number of days that the total balance of the account is less than or equal to 0 in the last six months.
The number of days that the total balance of the account is less than or equal to 0 in the last twelve months.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_3d.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_1w.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_1m.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_3m.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_6m.
The number of days that the mean balance of the account is less than or equal to the amount specified in mean_daily_balance_12m.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last three days.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last week.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last month.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last three months.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last six months.
The number of days that the total balance of the account is less than or equal to the amount specified in balance_threshold_x in the last twelve months.
Aggregated metrics calculated based on the user's transactions from checking, savings, credit card, and loan accounts.
ℹ️ Note
If there is not enough transactional data for a given period, we return
nullfor calculated fields and0for 'count-based' fields. For example, if the account has only been open for five days (or you have provided data just for five days), we return values for_3d,_1w, and_1m, however:
mean_num_transactions_3mwill returnnullas there is no data for months two and three (calculated field).num_transactions_3mwill return0as there is no data for months two and three ('count-based' field)
The total number of transactions analyzed to determine the risk insights for the last three days (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last week (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last month (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last three months (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last six months (incoming and outgoing).
The total number of transactions analyzed to determine the risk insights for the last twelve months (incoming and outgoing).
The maximum number of transactions for the last three days.
The maximum number of transactions for the last week.
The maximum number of transactions for the last month.
The maximum number of transactions for the last three months.
The maximum number of transactions for the last six months.
The maximum number of transactions for the last twelve months.
The mean number of transactions for the last three days.
The mean number of transactions for the last week.
The mean number of transactions for the last month.
The mean number of transactions for the last three months.
The mean number of transactions for the last six months.
The mean number of transactions for the last twelve months.
The total number of inflow transactions for the last three days.
The total number of inflow transactions for the last week.
The total number of inflow transactions for the last month.
The total number of inflow transactions for the last three months.
The total number of inflow transactions for the last six months.
The total number of inflow transactions for the last twelve months.
The maximum number of inflow transactions for the last three days.
The maximum number of inflow transactions for the last week.
The maximum number of inflow transactions for the last month.
The maximum number of inflow transactions for the last three months.
The maximum number of inflow transactions for the last six months.
The maximum number of inflow transactions for the last twelve months.
The mean number of inflow transactions for the last three days.
The mean number of inflow transactions for the last week.
The mean number of inflow transactions for the last month.
The mean number of inflow transactions for the last three months.
The mean number of inflow transactions for the last six months.
The mean number of inflow transactions for the last twelve months.
The total sum of all inflow transactions for the last three days.
The total sum of all inflow transactions for the last week.
The total sum of all inflow transactions for the last month.
The total sum of all inflow transactions for the last three months.
The total sum of all inflow transactions for the last six months.
The total sum of all inflow transactions for the last twelve months.
The highest value inflow transaction in the last three days.
The highest value inflow transaction in the last week.
The highest value inflow transaction in the last month.
The highest value inflow transaction in the last three months.
The highest value inflow transaction in the last six months.
The highest value inflow transaction in the last twelve months.
The mean incoming value of all transactions in the last three days.
The mean incoming value of all transactions in the last week.
The mean incoming value of all transactions in the last month.
The mean incoming value of all transactions in the last three months.
The mean incoming value of all transactions in the last six months.
The mean incoming value of all transactions in the last twelve months.
To total number of outflow transactions in the last three days.
To total number of outflow transactions in the last week.
To total number of outflow transactions in the last month.
To total number of outflow transactions in the last three months.
To total number of outflow transactions in the last six months.
To total number of outflow transactions in the last twelve months.
The maximum number of outflow transactions for the last three days.
The maximum number of outflow transactions for the last week.
The maximum number of outflow transactions for the last month.
The maximum number of outflow transactions for the last three months.
The maximum number of outflow transactions for the last six months.
The maximum number of outflow transactions for the last twelve months.
The mean number of outflow transactions for the last three days.
The mean number of outflow transactions for the last week.
The mean number of outflow transactions for the last month.
The mean number of outflow transactions for the last three months.
The mean number of outflow transactions for the last six months.
The mean number of outflow transactions for the last twelve months.
The total sum of all outflow transactions for the last three days.
The total sum of all outflow transactions for the last week.
The total sum of all outflow transactions for the last month.
The total sum of all outflow transactions for the last three months.
The total sum of all outflow transactions for the last six months.
The total sum of all outflow transactions for the last twelve months.
The highest value outflow transaction in the last three days.
The highest value outflow transaction in the last week.
The highest value outflow transaction in the last month.
The highest value outflow transaction in the last three months.
The highest value outflow transaction in the last six months.
The highest value outflow transaction in the last twelve months.
The mean outgoing value of all transaction in the last three days.
The mean outgoing value of all transaction in the last week.
The mean outgoing value of all transaction in the last month.
The mean outgoing value of all transaction in the last three months.
The mean outgoing value of all transaction in the last six months.
The mean outgoing value of all transaction in the last twelve months.
The number of days that no transactions occurred within the last three days.
The number of days that no transactions occurred within the last week.
The number of days that no transactions occurred within the last month.
The number of days that no transactions occurred within the last three months.
The number of days that no transactions occurred within the last six months.
The number of days that no transactions occurred within the last twelve months.
The number of days since the last transaction occurred.
The number of days since the last inflow transaction occurred.
The number of days since the last outflow transaction occurred.
Aggregate metrics calculated based on the user's transactions from checking, savings, credit, and loan accounts. However, internal transfers (transfers between accounts belonging to the same link) are not used in the calculation.
ℹ️ Note
If there is not enough transactional data for a given period, we return
null. For example, if the account has only been open for 15 days (or you have only provided data for just 15 days), we return values for_3d,_1w, and_1m, however for_3mwe will returnnullas there is no data for months two and three.
The highest value of positive cash flow transactions in the last three days.
The highest value of positive cash flow transactions the last week.
The highest value of positive cash flow transactions the last month.
The highest value of positive cash flow transactions the last three months.
The highest value of positive cash flow transactions the last six months.
The highest value of positive cash flow transactions the last twelve months.
The highest value of negative cash flow transactions in the last three days.
The highest value of negative cash flow transactions in the last week.
The highest value of negative cash flow transactions in the last month.
The highest value of negative cash flow transactions in the last three months.
The highest value of negative cash flow transactions in the last six months.
The highest value of negative cash flow transactions in the last twelve months.
The mean value of the positive cash flow transactions in the last three days.
The mean value of the positive cash flow transactions in the last week.
The mean value of the positive cash flow transactions in the last month.
The mean value of the positive cash flow transactions in the last three months.
The mean value of the positive cash flow transactions in the last six months.
The mean value of the positive cash flow transactions in the last twelve months.
The mean value of the negative cash flow transactions in the last three days.
The mean value of the negative cash flow transactions in the last week.
The mean value of the negative cash flow transactions in the last month.
The mean value of the negative cash flow transactions in the last three months.
The mean value of the negative cash flow transactions in the last six months.
The mean value of the negative cash flow transactions in the last twelve months.
The sum total of all transactions leading to a positive cash flow in the last three days.
The sum total of all transactions leading to a positive cash flow in the last week.
The sum total of all transactions leading to a positive cash flow in the last month.
The sum total of all transactions leading to a positive cash flow in the last three months.
The sum total of all transactions leading to a positive cash flow in the last six months.
The sum total of all transactions leading to a positive cash flow in the last twelve months.
The positive cash flow trend based on the sum of all positive transactions in the last three days.
The positive cash flow trend based on the sum of all positive transactions in the last week.
The positive cash flow trend based on the sum of all positive transactions in the last month.
The positive cash flow trend based on the sum of all positive transactions in the last three months.
The positive cash flow trend based on the sum of all positive transactions in the last six months.
The positive cash flow trend based on the sum of all positive transactions in the last twelve months.
The sum total of all transactions leading to a negative cash flow in the last three days.
The sum total of all transactions leading to a negative cash flow in the last week.
The sum total of all transactions leading to a negative cash flow in the last month.
The sum total of all transactions leading to a negative cash flow in the last three months.
The sum total of all transactions leading to a negative cash flow in the last six months.
The sum total of all transactions leading to a negative cash flow in the last twelve months.
The negative cash flow trend based on the sum of all negative transactions in the last three days.
The negative cash flow trend based on the sum of all negative transactions in the last week.
The negative cash flow trend based on the sum of all negative transactions in the last month.
The negative cash flow trend based on the sum of all negative transactions in the last three months.
The negative cash flow trend based on the sum of all negative transactions in the last six months.
The negative cash flow trend based on the sum of all negative transactions in the last twelve months.
The ratio between sum_positive / sum_negative in the last three days.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last week.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last month.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last three months.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last six months.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The ratio between sum_positive / sum_negative in the last twelve months.
ℹ️ If the ratio is greater than 1, it means that the user has more income than outgoing, indicating that they spend less than they earn.
Note: In the case that there have been no outgoing transactions, the value will be null.
The net cash flow in the last three days.
The net cash flow in the last three months.
The net cash flow in the last six months.
The net cash flow in the last twelve months.
The net cash flow trend in the last three days months.
The net cash flow trend in the last week.
The net cash flow trend in the last month.
The net cash flow trend in the last three months.
The net cash flow trend in the last six months.
An array of aggregate metrics regarding the transaction categories and subcategories that Belvo has identified within the user's transaction history.
In the array, Belvo only returns categories that have been identified.
The name of the transaction category.
Get transaction categorization With Transaction categorization, we clean and categorize transactions for you, turning raw data into actionable insights. To enable this feature, just reach out to us, and we'll get right to it.
We return one of the following enum values:
Bills & UtilitiesCredits & LoansDepositsFees & ChargesFood & GroceriesHome & LifeIncome & PaymentsInsuranceInvestments & SavingsOnline Platforms & LeisurePersonal ShoppingTaxesTransfersTransport & TravelUnknown*Withdrawal & ATMnull* For clients not using our Transaction Categorization product, we return null instead.
The transaction subcategory.
Get transaction categorization For clients not using our Transaction categorization, we return
nullinstead. To enable this feature, just reach out to us, and we'll get right to it.
We return one of the following enum values:
Electricity & EnergyRentTelecommunicationsWaterAutoCredit CardInstalmentInterest & ChargesMortgagePay AdvancePersonalAdjustmentsBank FeesChargebackRefundBlocked BalancesAlimonyAlcohol & TobaccoBakery & CoffeeBars & NightclubsConvenience StoreDeliveryGroceriesRestaurantsEducationGyms & FitnessHair & BeautyHealthHome Decor & AppliancesLaundry & Dry CleaningPharmaciesProfessional ServicesVeterinary ServicesFreelanceInterestRetirementSalaryGovernmentHome InsuranceAuto InsuranceHealth & Life InsuranceSavingsFixed incomeEquityInvestment FundsDerivativesCryptocurrenciesApps, Software and Cloud ServicesEvents, Parks and MuseumsGamblingGamingLotteryMovie & AudioBooks & NewsClothing & AccessoriesDepartment StoreElectronicsE-commerceGiftsOffice SuppliesPet SuppliesAuto Tax & FeesDonationGovernment FeesIncome TaxReal Estate Tax & FeesTax ReturnAccommodationAuto ExpensesAuto RentalFlightsGasMileage ProgramsParking & TollsPublic TransitTaxis & RidesharesOthernullThe net amount of the transactions for this category in the last three months (calculated as the total incoming - total outgoing transactions for this category).
The ratio of net_amount_3m divided by the sum of all incoming categorized transactions (including the current category) for the same period.
Note: If there are no inflow transactions for the period, this value will return null.
{ "id": "0d3ffb69-f83b-456e-ad8e-208d0998d71d", "link": "30cb4806-6e00-48a4-91c9-ca55968576c8", "created_at": "2022-02-09T08:45:50.406032Z", "accounts": [ "0d3ffb69-f83b-456e-ad8e-208d0998d71d", "00293c8e-1152-440b-9892-3c071fb88672", "cf638fba-ef45-4c10-bc6f-adecc4b2bf4e", "3861a5da-ae9b-4f20-a632-a9294489d5ac", "1f60315b-236d-498e-be7a-92bc613d329b", "a2c8da63-ed51-41e6-891a-4ae7e784463a" ], "assets_metrics": { "institutions": [ … ], "num_assets_accounts": 1, "num_checking_accounts": 1, "num_savings_accounts": 1, "checking_accounts_balance": 35901.46, "savings_accounts_balance": 300.02 }, "credit_cards_metrics": { "num_accounts": 2, "sum_credit_limit": 106560, "sum_credit_used": 101020.14, "credit_card_limit_utilization": 0.95 }, "loans_metrics": { "num_accounts": 1, "sum_loans_principal": 5000, "sum_loans_outstanding_principal": 2000, "sum_loans_monthly_payment": 400, "loan_limit_utilization": 0.3, "overdraft_limit": 900, "overdraft_limit_utilization": 0.4 }, "balances_metrics": { "closing_balance": 35901.46, "min_balance_3d": 35417.68, "min_balance_1w": 34150.5, "min_balance_1m": 33990.59, "min_balance_3m": 33990.59, "min_balance_6m": 33990.59, "min_balance_12m": 33990.59, "mean_balance_3d": 35659.57, "mean_balance_1w": 35077.1, "mean_balance_1m": 34816.08, "mean_balance_3m": 34816.08, "mean_balance_6m": 34816.08, "mean_balance_12m": 34816.08, "max_balance_3d": 35901.46, "max_balance_1w": 35901.46, "max_balance_1m": 35901.46, "max_balance_3m": 35901.46, "max_balance_6m": 35901.46, "max_balance_12m": 35901.46, "std_balance_3d": 279.31, "std_balance_1w": 764.03, "std_balance_1m": 586.55, "std_balance_3m": 586.55, "std_balance_6m": 586.55, "std_balance_12m": 586.55, "balance_trend_3d": 193.51, "balance_trend_1w": 290.18, "balance_trend_1m": 22.6, "balance_trend_3m": 22.6, "balance_trend_6m": 22.6, "balance_trend_12m": 22.6, "days_balance_below_0_3d": 0, "days_balance_below_0_1w": 0, "days_balance_below_0_1m": 0, "days_balance_below_0_3m": 0, "days_balance_below_0_6m": 0, "days_balance_below_0_12m": 0, "days_balance_below_mean_3d": 2, "days_balance_below_mean_1w": 3, "days_balance_below_mean_1m": 17, "days_balance_below_mean_3m": 17, "days_balance_below_mean_6m": 17, "days_balance_below_mean_12m": 17, "days_balance_below_x_3d": 0, "days_balance_below_x_1w": 0, "days_balance_below_x_1m": 0, "days_balance_below_x_3m": 0, "days_balance_below_x_6m": 0, "days_balance_below_x_12m": 0, "balance_threshold_x": 1000 }, "transactions_metrics": { "num_transactions_3d": 26, "num_transactions_1w": 46, "num_transactions_1m": 168, "num_transactions_3m": 460, "num_transactions_6m": 472, "num_transactions_12m": 496, "max_num_transactions_3d": 10, "max_num_transactions_1w": 10, "max_num_transactions_1m": 18, "max_num_transactions_3m": 18, "max_num_transactions_6m": 18, "max_num_transactions_12m": 18, "mean_num_transactions_3d": 6.5, "mean_num_transactions_1w": 5.75, "mean_num_transactions_1m": 5.42, "mean_num_transactions_3m": 5.05, "mean_num_transactions_6m": 2.61, "mean_num_transactions_12m": 1.37, "num_incoming_transactions_3d": 12, "num_incoming_transactions_1w": 21, "num_incoming_transactions_1m": 80, "num_incoming_transactions_3m": 229, "num_incoming_transactions_6m": 238, "num_incoming_transactions_12m": 256, "max_num_incoming_transactions_3d": 6, "max_num_incoming_transactions_1w": 6, "max_num_incoming_transactions_1m": 10, "max_num_incoming_transactions_3m": 10, "max_num_incoming_transactions_6m": 10, "max_num_incoming_transactions_12m": 10, "mean_num_incoming_transactions_3d": 3, "mean_num_incoming_transactions_1w": 2.62, "mean_num_incoming_transactions_1m": 2.58, "mean_num_incoming_transactions_3m": 2.52, "mean_num_incoming_transactions_6m": 1.31, "mean_num_incoming_transactions_12m": 0.71, "sum_incoming_amount_3d": 17142.16, "sum_incoming_amount_1w": 24825.92, "sum_incoming_amount_1m": 75993.36, "sum_incoming_amount_3m": 198197.28, "sum_incoming_amount_6m": 223697.28, "sum_incoming_amount_12m": 274697.28, "max_incoming_amount_3d": 3000, "max_incoming_amount_1w": 3000, "max_incoming_amount_1m": 3000, "max_incoming_amount_3m": 3000, "max_incoming_amount_6m": 3000, "max_incoming_amount_12m": 3000, "mean_incoming_amount_3d": 1428.51, "mean_incoming_amount_1w": 1182.19, "mean_incoming_amount_1m": 949.92, "mean_incoming_amount_3m": 865.49, "mean_incoming_amount_6m": 939.9, "mean_incoming_amount_12m": 1073.04, "num_outgoing_transactions_3d": 14, "num_outgoing_transactions_1w": 25, "num_outgoing_transactions_1m": 88, "num_outgoing_transactions_3m": 231, "num_outgoing_transactions_6m": 234, "num_outgoing_transactions_12m": 240, "max_num_outgoing_transactions_3d": 6, "max_num_outgoing_transactions_1w": 6, "max_num_outgoing_transactions_1m": 8, "max_num_outgoing_transactions_3m": 9, "max_num_outgoing_transactions_6m": 9, "max_num_outgoing_transactions_12m": 9, "mean_num_outgoing_transactions_3d": 3.5, "mean_num_outgoing_transactions_1w": 3.12, "mean_num_outgoing_transactions_1m": 2.84, "mean_num_outgoing_transactions_3m": 2.54, "mean_num_outgoing_transactions_6m": 1.29, "mean_num_outgoing_transactions_12m": 0.66, "sum_outgoing_amount_3d": 18246.95, "sum_outgoing_amount_1w": 26362.25, "sum_outgoing_amount_1m": 78243.82, "sum_outgoing_amount_3m": 192608.77, "sum_outgoing_amount_6m": 201608.77, "sum_outgoing_amount_12m": 219608.77, "max_outgoing_amount_3d": 3000, "max_outgoing_amount_1w": 3000, "max_outgoing_amount_1m": 3000, "max_outgoing_amount_3m": 3000, "max_outgoing_amount_6m": 3000, "max_outgoing_amount_12m": 3000, "mean_outgoing_amount_3d": 1303.35, "mean_outgoing_amount_1w": 1054.49, "mean_outgoing_amount_1m": 889.13, "mean_outgoing_amount_3m": 833.8, "mean_outgoing_amount_6m": 861.58, "mean_outgoing_amount_12m": 915.04, "days_without_transactions_3d": 0, "days_without_transactions_1w": 0, "days_without_transactions_1m": 0, "days_without_transactions_3m": 0, "days_without_transactions_6m": 87, "days_without_transactions_12m": 261, "days_since_last_transaction": 0, "days_since_last_incoming_transaction": 0, "days_since_last_outgoing_transaction": 0, "days_history": 365 }, "cashflow_metrics": { "max_positive_3d": 1850.12, "max_positive_1w": 3808.99, "max_positive_1m": 4012.61, "max_positive_3m": 5001.08, "max_positive_6m": 8500, "max_positive_12m": 8500, "max_negative_3d": 3375.43, "max_negative_1w": 3375.43, "max_negative_1m": 5305.92, "max_negative_3m": 7535.85, "max_negative_6m": 7535.85, "max_negative_12m": 7535.85, "mean_positive_3d": 1410.54, "mean_positive_1w": 1665.74, "mean_positive_1m": 1827.36, "mean_positive_3m": 1881.58, "mean_positive_6m": 2102.19, "mean_positive_12m": 2502.06, "mean_negative_3d": 3373.48, "mean_negative_1w": 2477.04, "mean_negative_1m": 1904.96, "mean_negative_3m": 1838.47, "mean_negative_6m": 1877.63, "mean_negative_12m": 1948.51, "sum_positive_3d": 5642.16, "sum_positive_1w": 13325.92, "sum_positive_1m": 52993.36, "sum_positive_3m": 163697.28, "sum_positive_6m": 189197.28, "sum_positive_12m": 240197.28, "sum_positive_trend_3d": 98.902, "sum_positive_trend_1w": -84.0393, "sum_positive_trend_1m": 22.7315, "sum_positive_trend_3m": 1.8398, "sum_positive_trend_6m": -17.1869, "sum_positive_trend_12m": -25.9856, "sum_negative_3d": 6746.95, "sum_negative_1w": 14862.25, "sum_negative_1m": 55243.82, "sum_negative_3m": 158108.77, "sum_negative_6m": 167108.77, "sum_negative_12m": 185108.77, "sum_negative_trend_3d": -3.91, "sum_negative_trend_1w": 254.2517, "sum_negative_trend_1m": 58.376, "sum_negative_trend_3m": 2.5895, "sum_negative_trend_6m": -1.4824, "sum_negative_trend_12m": -4.2394, "positive_to_negative_ratio_3d": 0.84, "positive_to_negative_ratio_1w": 0.9, "positive_to_negative_ratio_1m": 0.96, "positive_to_negative_ratio_3m": 1.04, "positive_to_negative_ratio_6m": 1.13, "positive_to_negative_ratio_12m": 1.3, "net_cashflow_3d": -1104.79, "net_cashflow_1w": -1536.33, "net_cashflow_1m": -2250.46, "net_cashflow_3m": 5588.51, "net_cashflow_6m": 22088.51, "net_cashflow_12m": 55088.51, "net_cashflow_trend_3d": 1448.683, "net_cashflow_trend_1w": 163.8856, "net_cashflow_trend_1m": 1.3034, "net_cashflow_trend_3m": -0.472, "net_cashflow_trend_6m": -15.1286, "net_cashflow_trend_12m": -21.5511 }, "category_metrics": [ { … } ] }
To receive inflow payments to your organization's bank account, you must register the bank accounts (individual and business) using Belvo's Payments API.
A payment intent is a single point of access to create payments using any payment method offered by Belvo.
A payment intent captures all payment information (such as the amount to be charged, the description of the payment, the provider, and so on) and guides your customers through the payment flow.
Note: For institutions that require the
username_typein theform_fieldsarray, you must send through this value in your PATCH request.