Does Your Right Hand Know That Your Left Hand Just Lost You a Billion Dollars?

Knowledge Graphs Bring Vital Changes to Connected Inventories for Financials

April 22, 2021 5 mins. read Jarred McGinnis

In the autumn 2020, one of the ‘Too Big To Fail’ global brands in finance learned a new way to lose a billion dollars in finance. The lost cash and fines were only part of the problem. The regulatory body also imposed restrictions on the bank making new acquisitions. That lack of dexterity in the competitive market of finance will hamper the company for years after the lawsuits are over. When you consider the eye-watering amount was lost by a manual error and that it happened after a decade-worth of mounting fines that warned the company that there were significant problems in their inventory control, you are right in thinking the bank could have avoided learning that billion dollar lesson.

Ontotext clients have used enterprise knowledge graphs to ensure inventory control is done in an intelligent and automated way. Inventory here refers to the vast amounts of information and data that financial institutions need on a daily basis, which are core assets to the business. If the bank had taken its problems seriously years ago, it could have saved itself lost revenues and a damaged reputation. The problem was the left hand had no way of knowing the systemic issues around data governance, risk management and compliance framework. Even if the systemic problems were known, there was no reliable means to communicate the issues in a timely manner so that those issues could be addressed.

Manage Regulation, Manage Risk

The companies in the financial sector have to operate in one of the most regulated business domains. They must harmonise an ecosystem of regulation that is constantly changing across international, national, regional and industry-specific jurisdictions. Many of these organisations have grown through acquisitions. The integration of which leads to an operational and technological Rube Goldberg machine, making vital knowledge integration across the enterprise and across different domains a seemingly impossible task. It was exactly this problem that was cited as the source of the problem for the bank’s billion dollar mistake.

Knowledge Graphs Make the Impossible, Simple

Knowledge graphs, like Ontotext’s GraphDB, represent an organisation’s data at a higher level of abstraction. In other words, data is stored by how the data is used and understood rather than where it is stored and what file format has been used. Ontotext has a proven methodology for taking the messing low-level information assets and transforming them through a unified and standardized meaning, accessible and understandable to both human and machine.

Through rich metadata and automated reasoning, it is possible to express the complexity of assets and their relationships. The knowledge graph has the flexibility to change with business needs but can also provide multiple views and perspectives on the data without the waste of replicating data across business units. By consistently providing teams with relevant quantitative and qualitative information about the asset inventory, it is possible to automate the identification of patterns, correlations between the assets and real-time actionable analysis.

Policies, Procedures and Standards

One of the problems identified was the inability to ensure adherence to its own data policies, procedures and standards. This is literally a case of the left hand not knowing what the right hand was doing. If a policy can be understood, it can be modelled in RDF, the language used by Ontotext GraphDB. RDF is the recognized standard for semantics and is used by EDM’s FIBO. FIBO is a formal model of the legal structures, rights and obligations that form the foundation of the financial industry.


One of the biggest, and costly failures, was the inability to produce reports for management and regulatory agencies. By not being able to produce accurate and up-to-date reports for the bank’s boards, the organisation was unaware of data quality issues, identifying problems and implementing remediation plans. A knowledge graph can ensure consistency of data policies across the entire company as well as adherence, which provides real-time identification of risks and the ability to model escalation and remediation processes.

Traceability and Accountability

With the adoption of an enterprise-wide knowledge graph approach it becomes possible to understand the source of errors without the reliance on slow and error-prone input and adjustment processes. It is possible to to simplify and consolidate applications with common functionalities, eliminate disparate systems, and strengthen data quality controls. Business units become more transparent and it is possible to establish inventory control over authoritative data sources and reference data while maintaining consistency across the enterprise. The identification, inventory, and evaluation of limitations of all systems and data sources required for report generation as well as the provenance of any data or actions is fully traceable. It ensures the development and implementation of the corrective action necessary is valid and reproducible.


Ontotext is already delivering value to the financial sector. With rich, meaningful metadata, our clients are benefiting from improved capabilities, enhanced control and increased capacity while also reducing operational costs. You can read our case study of how Ontotext implemented an enterprise knowledge graph to provide a connected inventory solution. Our business insights about the current status and trends, risk and opportunities are based on a holistic interrelated view of enterprise assets. The semantics defined in knowledge graphs provide a common language for the disparate systems irrespective of the underlying technology they are using. Individual systems and their resources can be utilised for a holistic view while maintaining their normal day-to-day operations without disturbance.

By automatically identifying and managing human, software and hardware related outages and exposures, Ontotext’s smart connected inventory solution allows banks to save much time and expenses, and avoid having to write checks that end in so many zeros that it gives you a hand cramp.

Want to deliver more value to your business with Ontotext’s Financial Services solutions?

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Technical Author at Freelancer

Jarred McGinnis is a managing consultant in Semantic Technologies. Previously he was the Head of Research, Semantic Technologies, at the Press Association, investigating the role of technologies such as natural language processing and Linked Data in the news industry. Dr. McGinnis received his PhD in Informatics from the University of Edinburgh in 2006.

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