CASE STUDY: Morgan Stanley , Global Fortune 100 Financial Institution, Transforms Information & Knowledge Management
Morgan Stanley is one of the largest investment banking and wealth management firms with offices in more than 42 countries and more than 60,000 employees, ranking 67th on the 2018 Fortune 500 list of the largest US corporations by total revenue. Headquartered in New York City, the organization faced challenges for better information retrieval, records retention, and legal hold capabilities or potentially face steep compliance fines. Securing data from outside threats is critical, but information from within the friendly firewall’s hamstrings business ability to operate, even without regulatory pressures. With worldwide data to swell by 10-fold by
2025, a better solution needed to be addressed. Leadership at Morgan Stanley solicited several consulting experts and chose Semantic Arts to guide in strategic resolution of this massive information sprawl while enabling greater information retrieval and easier user consumption.
“Information management” as part of the legal department took lead as it was chartered with knowing about all data sets within the firm: Structured, Unstructured and everything in between. A major undertaking for any group yet alone a global giant with divisions all over the world.
PROBLEM STATEMENT: Information management determined that existing traditional architectures and relational data structures were failing to keep pace with data growth and management of information assets. A solution that offered scale, extend-ability, and an enhanced user search experience was the primary objectives. Like other organizations entrenched in data silos and single ownership, information resided in many data sources (SQL, Oracle, SAP, SharePoint, Excel, PDF, videos, and shared files, to name a few), making for difficult data aggregation with accuracy. Decades of integration have resulted in highly dependent systems and applications. In fact, changes to any data schemas were laborious coding and testing exercises that yielded little business benefit. In short, it was problematic to access the right data and costly to make even simple changes.
STRATEGY: By collaborating with Semantic Arts, experts in Data /Digital transformation, a data strategy was established for better information management. Implementation of Semantic Knowledge Graphs and a flexible Ontology for future information growth was decided after lengthy evaluation. It offered strategic value for supporting numerous domain areas simultaneously; including risk management, regulatory compliance, asset management, adviser information retrieval while linking data from each domain. Additionally, an important use case of a Semantic Knowledge Graph approach is the architectural advantage of limitless extendibility across the enterprise for reuse. This factored into the long-term reasoning and vision of becoming Data Centric.
APPROACH: Starting strategic initiatives like this can be particularly tricky in that achieving a balance between building a foundation for future success and immediate results can be a high wire act in organizational politics. With the advice of Semantic Arts, a “Think Big and Start Small” initial phase of work was proposed and accepted. This involved building a core Ontology in parallel with a Domain model, whereby both will be connected for building data relationships in future phases. This strategy will address the mission of contextually enriching the data organizationally, which in turn can be leveraged for greater insights in making business decisions and improved data governance.
Semantic Arts represents professional management consulting services for untangling the ad hoc patchwork of systems integration; turbo-charging new Knowledge and Information initiatives. We call it the “Data-Centric Revolution” that inverts the dependency between data models and application code. In short order, the code will become dependent on the shared information model. Join the Revolution!
RESULTS: A small team of consultants and Morgan Stanley SME’s assembled for a 6-month assignment. During the engagement, results came quickly. Within the initial weeks, after loading the data into a Triple Store and applying some very simplistic natural language processing routines, the team took the firm from 0.5% tagging of information to 25%, a 50-fold increase in information classification with relatively nominal effort.
By incorporating Semantic Arts strategy of instituting a flexible Ontology and Knowledge Graphs, the improved visibility and harmonization of the information across multiple data sets quickly captured the attention of business capability owners. Amazing is the fact that only 1% accuracy was in place by leveraging existing technologies. Collaboratively, the team captured hundreds of regulatory jurisdictions used for promoting rules. By linking this data with billions of internal documents from disparate databases, it gave contextual information surrounding a document or repository for a self-assembling capability. Previously, aggregation was manually driven, inaccurate, clumsy and time-consuming.
OTHER DOMAINS JOIN IN: Follow up engagements with Equity Research, and Operations Resiliency soon followed as the changes made a tangible impact. Those domain teams have taken on smaller use case purposes to answer difficult questions while leveraging the functionality from the core Ontology foundation developed by the Semantic Arts consultants during the first initiative. The inherent nature of Knowledge Graphs linking data relationships can transform into a Siri like experience by offering answers, recommendations and learn when tied to AI capabilities. Furthermore, the information within the Graph enriches the contextual value because its connected, resulting in a single model. The business value of capturing knowledge for expanding wisdom growth multiples as the connections become realized between domains. Beginnings are taking form: removal of data silos, replication of data, and costly integration of application functionality.
CHANGING WALL STREET: Combining a strategic data plan and incorporating Knowledge Graphs as a companion solution is making a difference. Wall Street reports are now being unlocked with AskResearch Chatbot capabilities to extract value by delivering hard to find information from hundreds of data sources. With coaching in best practice Ontology development, the Equities Research team has successfully continued expansion of this graphs initial use case.
“You have this historical archive sitting in a library and there is so much value embedded in it, but traditionally it has been hard to unlock that value because insights and data are fixed in monolithic PDFs.” -D’Arcy Carr, the global head of research, editorial, and publishing
Claims of future time savings in (Billions/year) are hard to quantify but clearly usage of the Chatbot is steadily increasing. Leveraging Knowledge Graphs as the backbone for information retrieval was critical for intuitive search functionality and giving realization to self-service capability for users.
FINANCIAL INDUSTRY INFORMATION FUTURE: The ability to leverage AI and Machine Learning in tandem with Knowledge Graphs according to Forbes, is the financial industry future. Use will soon shift from a competitive edge to a must-have. Further discussion between Semantic Arts and Marketing and HR innovators at Morgan Stanley are in flight with more dynamic results pending.
Semantic Arts represents professional management consulting services for untangling the ad hoc patchwork of systems integration; turbo charging new Knowledge and Information initiatives. We call it the, “Data-Centric Revolution” that inverts the dependency between data models and application code. In short order, the code will become dependent on the shared information model. Join the Revolution!
