Transaction Monitoring #

Not all transaction monitoring tools are created equal; they do not all perform the same function. Some are primarily built for e-commerce platforms to reduce losses and chargebacks. Others are built to help fintech companies determine the likelihood of users defaulting on payments, which can create program losses for the business. Our tool is designed to keep fintech founders from going to federal prison for enabling criminal and terrorist financing, to reduce the likelihood of money laundering, and to detect anomalies in transaction patterns that may be due to fraud and theft.

We use a scoring model to score each transaction in realtime, a score similar to the FICO scoring model which starts at 850 and drops all the way to 100 for the most risky transactions. We also provide the factors that were involved in our scoring so that you are also aware of them and can make an informed decision on your own.

While we provide a pretty accurate risk score, scoring factor and result on each transaction, as a fintech platform, you are also able to set rule based actions and decide what happens when a certain rule is triggered, allowing you to tweak our model to basically almost any type of fraud you are facing.

Once a rule based action is set, subsequent API responses will include an action body parameter and you can use that to make your transaction decisions.

There are two major parts to using Stack's Transaction monitoring;

• Linking an entity
• Reporting (scoring) a transaction

Link an entity #

Before you link an entity, ensure that you have already created either an individual entity or a business entity

Endpoint #

{BASE_URL}/transactions/monitor/entity

Method: POST.

Sample Request #

curl --location --request POST 'https://api.stack-ft.com/transactions/monitor/entity' \
--header 'Authorization: API_KEY' \
--header 'Content-Type: application/json' \
--data-raw '{
    "entity_id": "i_uuid_5b240456-ff05-4d9c-908c-241525a6ca36"
}'

Sample Response #

{
    "status": "success",
    "entity": {
        "entity_id": "i_uuid_5b240456-ff05-4d9c-908c-241525a6ca36"
    },
    "request_id": "89a0948f-9dfa-4d5e-9aab-f35ff8cb29e7"
}

Report / Score a transaction #

This is a very important step as it is where we determing, in real-time how risky a transaction is based on data, history and patterns. Our system uses a scoring model similar to the FICO scoring which starts at 850 for less risky transactions and drops all the way to 100 for transactions with the highest risk.

We require a set of data points to be provided in the request in order to make the most accurate decision on a transaction. The less information provided, the less accurate the system will be in scoring the transaction's risk.

Endpoint #

{BASE_URL}/transactions/monitor/report

Method: POST.

origin object #

destination object #

Sample Request #

curl --location --request POST 'https://api.stack-ft.com/transactions/monitor/report' \
--header 'Authorization: API_KEY' \
--header 'Content-Type: application/json' \
--data-raw '{
    "entity_id": "i_uuid_5b240456-ff05-4d9c-908c-241525a6ca36",
    "amount": 5000.25,
    "direction": "debit",
    "entity_ip_address": "146.70.53.35",
    "destination": {
        "entity_name": "Example Company Inc",
        "country": "RU"
    }
}'

Sample Response #

{
    "status": "success",
    "entity_id": "i_uuid_5b240456-ff05-4d9c-908c-241525a6ca36",
    "transaction_report": {
        "score": 395,
        "scoring_factors": [
            "entity_sanctioned",
            "amount_over_individual_threshold",
            "deceptive_location_risk",
            "transaction_destination_sanctioned"
        ],
        "result": "high_risk",
        "transaction_amount": 5000.25,
        "transaction_direction": "debit"
    },
    "request_id": "3a7af4f0-361e-4c3a-a819-7ac79074cbe9"
}

Supported Currencies #