Bpifrance achieves its digital transformation with MongoDB

With the aim of making the French economy more dynamic and competitive, Bpifrance supports companies in their projects relating to development, innovation and environmental and energy transition, and provides export financing in the name and on behalf of the French government. And the needs are so great that the organization is recruiting.

But Bpifrance is also a powerful information system which was already based on a MongoDB platform with 4 applications before 2021. Two years ago, the public entity opted for MongoDB Atlas, which contains 35 applications spread over several clusters for 250 users.

A more modern information system for new opportunities

Thanks to the performance of MongoDB Atlas, the Bpifrance IT team, which specializes in database administration, has greatly improved its chatbot by providing context. A chatbot may have trouble understanding complex queries. By combining several technologies within the project known as MPA, information from Bpifrance will be digitally “sliced" into a MongoDB Atlas database, then compared with information from a chatbot user. For Nizar Salhaji, Head of the Technical and Functional Architecture Department at Bpifrance, “With these tools, we bring back context and the answers are much more relevant.”

The best of Core Banking

A basic banking system is software used to handle the most common banking transactions, such as opening accounts and processing cash deposits and withdrawals. Bpifrance's system was a legacy of the past, with processing on D+1 or in batch mode. Today, we need to calculate outstanding amounts and risk in real time. To succeed in this project, Bpifrance combined the Confluent data streaming platform, connectors and MongoDB, the NoSQL Database, all operating in the Cloud.

Another data-related project concerns access to all Bpifrance information from the different business lines in order to gather and carry out 360° research. In this way, by providing a history that did not exist before, users will be able to carry out audits more easily, which are particularly important in the public sector. MongoDB Atlas provides this function here.

Finally, for reporting and risk analysis, Bpifrance has set up a dataset in clusters and MongoDB. Through Data Federation, Atlas users will be able to combine, enrich, and transform data, run federated queries across multiple data sources, and generate data to their preferred destination. Bpifrance teams, who have to produce a risk analysis report, will be able to find the right information and create their own dataset.