Financial institutions operate in multiple highly regulated business domains and work with various international, national, regional and industry regulatory organizations, agencies and governments. Many of them comprise formerly independent businesses with distinct organizational and technology cultures and histories. The successful operation of these institutions requires efficient operational integration, which in turn requires smooth knowledge integration across the enterprise and across different domains.
The Goal
A global bank needed to integrate its various information resources, which were managed by a variety of tools with limited integration capabilities (employees, hardware, software, networks, customers, locations, etc.). The Bank wanted to create a hub for the federated management of this disparate information sources and be able to respond in real time to issues such as:
- When the server of a financial unit was offline, what business processes were impacted and who was responsible for these systems?
- When employees left the Bank, who had to take over their responsibilities?
- If an open source library was identified as a security threat, what systems were impacted and who was responsible for these systems, what business operations were impacted and who was responsible for these business operations, etc.?
The Challenge
The main cause for information hurdles in the Bank was the existence of data islands as well as the structure of incentives empowering the creation and maintenance of such islands. Therefore, the required solution had to be able to integrate all this siloed data from the various information sources to leverage:
- near real time incident management of human assets (amicable and hostile exits, etc.), physical assets (changes in software, hardware, etc.), etc.
- quick response to errors in publishing data (identifying the proximate and distal causes of the error, notifying all affected parties, publishing corrections, etc.).
- ability to quickly adapt to changes in regulations that would otherwise disrupt the Bank’s operations (new sanctioned business entities, new classes of prohibited activities, etc.).
- ability to quickly adapt to changes in policies (identifying business processes that were counter to these new policies, reallocating or terminating personnel and hardware resources, etc.).
The Solution: A Knowledge Graph-based Connected Inventory
The Connected Inventory knowledge graph built by Ontotext enabled the Bank to integrate meaningful, correct, current, trusted and accessible information and turn it into useful knowledge. It created a highly connected inventory powered by GraphDB – Ontotext’s leading RDF database for knowledge graphs.
Using this flexible graph data model, the solution unified and standardized meaning across the Bank’s information assets, enabling sophisticated expression of the classes of the assets and their relationships as they appeared in real-life. The addition of rich meta-data allowed clear identification of the assets and the ability to fill up the gaps within the evolving Connected Inventory knowledge graph.
As the data loaded in the graph was of high-quality and up-to-date, the inventory consistently provided the Bank’s team with relevant quantitative and qualitative information about the asset inventory. Consequently, they had a solid foundation for identifying patterns and correlations between the assets as well as for analyzing insights.
Business Benefits
Using the 4Cs methodology, which discusses capability, cost, control and capacity, here are the main business benefits of implementing a Connected Inventory knowledge graph for the Bank:
Improved capability:
- Discovering and identifying the key assets of the business;
- Structuring, unifying and standardizing meaning;
- Measuring quantitative and qualitative information;
- Analyzing insights based on the holistic view of the enterprise;
- Predicting risk and opportunity scenarios.
Reduced cost:
- Achieving cost optimization of risk, controls, time, repeatable manual efforts, physical and IT infrastructure expenses, etc.;
- Enjoying new revenue streams by adding new and improved monetization of existing information and data assets, resulting in new products, services and ways of doing business.
Enhanced control:
- Looking at the big-picture in real-time and drilling down insights;
- Viewing and analyzing key success/failure factors;
- Analyzing financial performance and ROI with a cross-joined 360-degree view;
- Auditing and demonstrating ongoing compliance with standards and regulations;
- Enabling risk identification, measurement and management;
- Assessing company capabilities and competitive advantages.
Increased capacity:
- Enabling a consistent view of the enterprise assets;
- Standardizing to comply with standards and regulations as well as to reduce risk errors;
- Automating and repeating the best practices of the enterprise;
- Performing on-demand at speed and scale;
- Iteratively improving and extending in parallel;
- Avoiding vendor lock-in and comply with technical W3C standards.
Why Choose Ontotext?
The implementation of an enterprise knowledge graph powered Connected Inventory solution equipped the Bank with business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of its enterprise assets.
This provided a common language for the disparate systems that performed similar roles using different technologies. It also allowed the individual systems and their resources to be efficiently expressed while maintaining their operations in their traditional languages.
By automatically identifying and managing human, software and hardware related outages and exposures, Ontotext’s smart Connected Inventory solution allowed the Bank to save much time and expenses, and avoid reputational risks.
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