Replica databases

If you process over 250k payment transactions a month and have opted for a single-tenant BankTech account, we can also provide you with the ability to directly query your transactional data. This data can be used for business intelligence, payments strategy development and payments management. Data is provided in a near-real-time fashion and places no load on your production services from BankTech.

Replica databases can also serve as convenient ways to query large amounts of data conveniently and reliably instead of requesting them from our server through our APIs. With a database user, you can also set up Extract Transform Load (ETL) operations to routinely pull subsets of your data into other repositories with common data connectors that are compatible with Structured Query Language (SQL).

Three typical solution models exist:

Model

SyncRefresh

Reconciliation

Max records

Development DB

Once off

None

2 mil

QA DB

Sat 04:00

Weekly

10 mil

Production DB

Daily at 04:00

Daily

50 mil

Mandates

The mandates table provides all the basic and metadata associated with mandates; including their verification statuses, their authentication statuses and various calculated fields to track the performance of collections associated with mandates. This table is great for payments management and data science teams looking to optimise billing strategies and manage the status of recurring billing.

Scheduled collections

The scheduled collections table provides a rolling 6-month forecast of all collections that are scheduled to bill. Collections related to mandates and ad hoc collections are displayed together with scheduled debit dates, adjusted debit dates and submission dates. This table is great for payments management and data science teams looking to implement billing strategies and manage ad hoc billing.

Processed collections

The processed collections table provides a history of all processed collections including their reported results. This table is great for payments management and data science teams looking to develop data sets from which to train their models and develop reporting dashboards that give their stakeholders the near-real-time reporting they need to make improve the payments strategy.