Today, a bank’s competitive advantage is tied to how well it builds workloads and experiences using data. In addition, working with data is a common key challenge in building and evolving applications. Data architecture within banks is overly complex, creating a tax on innovation, a fragmented developer experience, a significant data integration effort, and unnecessary data duplication.
Our integration with MongoDB Atlas combines Vault Core’s rich data streaming functionality with a best-in-class data platform that gives developers a seamless and scalable experience when building application features that are heavily reliant on data.
Increased understanding of the customer
The aggregation of all customer accounts gives banks the ability to easily count and sort customers by a variety of search factors e.g., by city or average spend. The integration to MongoDB Atlas gives banks access to a single view of banking data, including a customer's account data, across the enterprise.
Improved data visualisation
The integration allows clients to easily generate meaningful data visualisation using Atlas charts, alongside Vault Core’s real-time data feed.
Improved operational reporting
The integration with Vault Core enables the aggregation of
all customer accounts, postings and balances. This can be used to get real-time insights with embeddable dashboards and visualisations which give banks a clear view of key operational metrics, such as a firmwide view of asset and counterparty exposure or a single view of a customer for fraud detection and Know Your Customer (KYC) requirements.
Thought Machine has developed a MongoDB Atlas integration service which works by listening to Kafka streams from Vault Core relating to accounts created, postings, and balances. The MongoDB Kafka connector receives events from Kafka topics, which are then written in documents to the DB collection. This data can then be processed and aggregated for a range of transformations and analytics.
