Operating in the asset and wealth management industry, the company is dealing with a range of market pressures squeezing top-line growth and margins. To support the drive for top-line growth, the company needed a more complete picture of existing customers in order to create personalized experiences and expand the products it delivers to those clients.
To meet client demands and enable business growth, the company’s IT function needed to shift its focus. This meant spending less time running commodity data systems and performing undifferentiated tasks and more time engineering data to generate actionable insights and build market-differentiating functionality.
But its plans were stymied by a complex legacy technology infrastructure, with a tangle of bespoke and third-party software systems providing core investment operations. Data was stored in silos, and relational tables put a ceiling on how much the company could scale its services. There were also processes in widespread use that masked how data records were changed, hindering its ability to understand data lineage and model risk over time. Without robust, instant visibility into its data, the company was hamstrung in deploying new insights and product opportunities.
With MarkLogic, we were able to do in months what we failed to do in years with our previous approach.
Head of Asset Management Technology
Global Top-tier Asset and Wealth Management Company
The company’s data infrastructure required a complete transformation. The first step in this transformation was to simplify core functions by bringing in BlackRock’s hosted service. The next step was to build a Trade Data Hub using MarkLogic with a 360° view of all customer, portfolio and transaction data, enabling, for the first time, differentiated products and services to be built.
The data hub handles a wide variety of data including fund descriptions, client mandates, transactions, and positions. As a data warehouse, MarkLogic ingests and stores a total of 45GB of data daily, including 15GB from external sources. MarkLogic also serves as the integration layer between BlackRock Aladdin and the data warehouse, providing the company with a more flexible and modifiable alternative to legacy extract-transform-load processes.
The MarkLogic solution has created secure, accurate reporting over the global company’s full lifecycle of data, all with minimal disruption to its operations. By creating more ways for systems to harmoniously integrate, MarkLogic builds the capacity of organizations to see and use their data more effectively, and more rapidly move into new services.
Meaningful data analysis: Capable of handling unstructured and structured data types, capturing data lineage, supporting semantics, and providing sophisticated search functionality, MarkLogic allows the company to better harmonize and analyze data sets across the business. MarkLogic also provided the company with a fit-for-purpose platform to support development of advanced analytics and artificial intelligence programs.
Greater agility means faster time-to-market: MarkLogic’s data-first rather than model-first approach were a strong fit with the company’s agile development and DevOps methodologies, with new business functionality built iteratively, delivered in days or weeks, not months or years.
Reduced IT infrastructure: In just six months, the team implemented the data hub and reduced the size and complexity of the company’s IT estate. Total systems were slashed from 31 to 4.
Advanced security: For the company, security and safe sharing of data is mission critical. MarkLogic offers advanced security mechanisms not found in other NoSQL databases, such as fine-grained, role-based access controls, data encryption and redaction.
Cloud services: With no infrastructure to buy and manage, MarkLogic’s fully automated cloud service provides the company with a more cost-effective and predictable data management solution, even as enterprise workloads fluctuate. Using the MarkLogic Data Hub Service will allow the company to free up resources and time to focus on what’s important – using the highest quality data to expand risk analytics and produce differentiated client insights.