Ank is an Argentine fintech that developed a product for money transfers between banks and virtual accounts. It allows you to manage several accounts from different banks from a single app and facilitates quick transfers between them.
Ank’s team needed to fulfill three main objectives within the scope of this project. Create an automated flow of reconciliation transactions to reduce manual work while improving the accuracy and trustworthiness of the process. Second, increase the frequency of the reconciliation process to obtain updated data. Finally, implement a batch data processing architecture based on best practices and technologies that could serve as a model for future pipelines. Together these needs could be solved by the implementation of a Modern Data Stack.
Mutt Data developed a system for automatic reconciliation on an hourly, daily, and weekly basis. The system extracts the information from the different sources, centralizes it in a Data Lake in Amazon Web Services, performs the relevant reconciliation checks and, if it detects inconsistencies, corrects them automatically or creates tickets for cases that require manual attention.
For more information on the implemented solution, check out Ank’s and Mutt’s case study featured on Amazon Web Services.
The system is developed on an Airflow 2.0 installation on Amazon EKS and uses Amazon Athena, DBT, Great Expectations and PostgreSQL. Other tools include Kubernetes, K33, Google Auth for Airflow Login, and Alembic.
The client saw manual conciliation processes reduced to under 3% of their total monetary transactions.
Mutt Data can help you crystallize your data strategy through the design and implementation of technical capabilities and best practices. We study your company’s business goals to understand what has to change so we can help you accomplish it through a robust technical strategy with a clear roadmap and set of milestones. Talk to one of our sales reps at firstname.lastname@example.org or check out our sales booklet and blog.