For one major Canadian bank, the Capital Markets division plays a critical role in its daily operations. This organization supports institutional investors, corporations, and high-net-worth individuals around the world with mergers and acquisitions advisory, debt and equity financing, corporate banking, trading, and more.
After the division faced exponential growth in the amount of information it managed — and an increase in the complexity of that data — it encountered significant challenges. Fragmented and duplicated information across disparate systems hindered the organization’s ability to gain timely insights and make business decisions. But by working with MongoDB, the organization is modernizing its infrastructure and unlocking the full potential of its data.
Confronting data challenges at the Capital Markets division
To support its services, the bank’s IT team oversaw 76 applications and 113 data domains. The Capital Markets division handled vast amounts of data across these domains, including client information, market data, transactions, and risk metrics. Tens of millions of records flowed through these disparate systems daily, creating a complex and siloed data architecture.
This data was often duplicated across multiple databases, making it difficult to access and use information efficiently. Stakeholders often created localized databases and tools to manage this information. This led to dependencies and roadblocks, particularly as a result of staffing changes, churn, or cross-departmental movement. Without consistent data governance, maintaining data accuracy and reliability became increasingly challenging.
The Capital Markets division had an imperative for a more unified approach. “We needed to implement a central, flexible, scalable, and resilient home for capital markets data,” said a senior director at the bank. “It’s a simple statement, but it required a lot of steps to make it happen and work effectively.”
The organization set out to establish a core data framework that could accommodate its data needs. The solution needed to be flexible and to integrate seamlessly with different analytical tools. The bank also wanted to distribute data ownership to domain-specific teams through a data mesh architecture. This would empower teams to manage, own, and service data as a product to the rest of the organization, thus improving data quality and reducing the rate of duplication.
MongoDB Atlas, an integrated suite of cloud database and data services, emerged as the ideal solution. Its flexible schema, scalability, and rich feature set aligned with the organization’s compliance requirements. “Data security was instrumental in ensuring that stakeholders across the enterprise found the solution suitable and a good fit for our needs,” said the senior director. “MongoDB Atlas checked all the boxes and would let us adopt features like SSO SAML integration, encryption, and different support tiers that fit the criticality of our use cases. We could also quickly integrate several data sources without needing a large number of developers.”
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