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Finance and Payments

Generate commercial reports and send them to BI software or directly to stakeholders

Possible workflow
An SQL example how to retrieve financial data
Generated CSV report

Monitoring of failed payments

Possible workflow
Possible data query
Slack notifications

Monitor overpaid orders

In case an organization accepts payments from customers with direct bank transfers, it opens a potential for mistakes made in the references or amount.
The following workflow can help to control and find overpaid orders or invoices.
Potential workflow
Potential SQL query to retrieve data
Potential message to send to stakeholders

Monitor unallocated bank transfers

Another popular modification of the previous two workflows is to monitor unallocated bank transfers. Meaning bank transfers made by customers that the system was not able to allocate to any order, invoice, or any other purchased item.
In this case, it is up to you to decide what to do with this transfer. Either return it, or try allocating it manually, or contact the customer and ask about it.
That's how the typical workflow may look like:

Filtering data sets by various values

Filtering data from large data sets is one of the most common and important tasks for payment operations. One of the powerful instruments Datamin offers for that is Transformer with GJSON query language.
Let's imagine we have the following dataset and we need to filter it in various ways:
[
{
"amount":250,
"created_at":"2022-10-01 16:01:11",
"currency":"USD",
"id":1,
"organization_id":1,
"status":"dispatched",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":250,
"created_at":"2022-10-01 16:01:11",
"currency":"USD",
"id":2,
"organization_id":1,
"status":"paid",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":3677.2,
"created_at":"2022-10-01 16:01:11",
"currency":"USD",
"id":3,
"organization_id":2,
"status":"completed",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":21.87,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":4,
"organization_id":1,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":21.87,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":5,
"organization_id":4,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":341.76,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":6,
"organization_id":1,
"status":"complete",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":2110.76,
"created_at":"2022-10-01 16:01:11",
"currency":"USD",
"id":7,
"organization_id":3,
"status":"new",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":127.89,
"created_at":"2022-10-01 16:01:11",
"currency":"USD",
"id":8,
"organization_id":3,
"status":"new",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":127.9,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":9,
"organization_id":4,
"status":"new",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":344.44,
"created_at":"2022-10-01 16:01:11",
"currency":"USD",
"id":10,
"organization_id":5,
"status":"paid",
"updated_at":"2022-10-01 16:01:11"
}
]
Let's look at the following 4 examples:
Filter:
#(status == "assembled")#
Result:
[
{
"amount":21.87,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":4,
"organization_id":1,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":21.87,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":5,
"organization_id":4,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":67.01,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":12,
"organization_id":2,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
}
]
Filter:
#(status == "assembled")#.amount
Result:
[
21.87,
21.87,
67.01
]
Filter:
#(status == "assembled").amount
Result: 21.87
Filter:
#(amount < 30)#
Result:
[
{
"amount":21.87,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":4,
"organization_id":1,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
},
{
"amount":21.87,
"created_at":"2022-10-01 16:01:11",
"currency":"EUR",
"id":5,
"organization_id":4,
"status":"assembled",
"updated_at":"2022-10-01 16:01:11"
}
]