The financial industry is an industry where an organization needs to know about any good or positive event related to customers' accounts as fast as possible. Therefore receiving such information is a real-time mode is vital for many departments from BI to risk, operations, or compliance. And that's what Datamin is good at.
Schedule generation of commercial reports and send them to BI software or directly to stakeholders
Possible pipeline
An SQL example how to retrieve financial data
Generated CSV report
Streaming monitoring information about failed payments
Possible pipeline
Possible data query
Slack notifications
Streaming monitoring information about 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 pipeline can help to control and find overpaid orders or invoices.
Potential pipeline
Potential SQL query to retrieve data
Potential message to send to stakeholders
Streaming monitoring information about unallocated bank transfers
Another popular modification of the previous two pipelines is to monitor unallocated bank transfers. This means 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, try allocating it manually, or contact the customer and ask about it.
That's how the typical pipeline may look like:
Filtering data sets by various factors on the fly
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: