Regulatory Compliance
Improve the efficiency and precision of your Regulatory Compliance system to meet your regulatory obligations and save millions in fines. Enhance your existing KYC, AML, Trade Surveillance, Sanctions or Financial Crime monitoring processes with a knowledge graph based solution. Improve the alert review process to provide better monitoring, review, analysis and prediction of potential risks.
How You’ll Benefit
Unambiguously identify the parties, transactions, markets and instruments involved in the activity.
Enrich the existing data with additional information from third party sources.
Provide rich analytical context by grouping the information by different hierarchies and logical models.
Interpret the existing data and infer new facts by using the formal semantics of knowledge graphs.
Provide additional suggestions on the basis of semantic or graph similarities.
Interpret each alert not only against the latest version of the organizational structure, but against its state at the time when it happened.
Complement the structured data with risk or opportunity signals from unstructured sources.
Create task specific dashboards and analytics UIs for the SME to consume and act on the information.
How it Works
Knowledge graph development
- Integrate with existing compliance systems and/or ingest data from third party sources.
- Create a model to map your data where you define:
- Parties, Events, Market and Jurisdictions;
- Event Classification and Severity;
- Parties roles, hierarchies and relationships;
- Exceptions based on white/black lists and markets/jurisdictions.
- Ingest the information in the knowledge graph, where you can:
- normalize data to compliance/industry models such as the Financial Industry Business Ontology (FIBO), SEC or FCA glossaries;
- employ proper semantic alignment to guarantee high quality data;
- infer new facts and relations by applying reasoning at scale.
Quality and outcome improvement
- Iteratively improve the quality of the events and alerts processing by involving SMEs, historical events and regulatory mandated patterns.
- Measure and maintain the quality by running benchmarks against Gold Standards and continuously improve the grouping, classification and filtering capabilities.
- Automate the repetitive tasks for process monitoring and measurement data updates, software operation, etc.
- Meet the KPIs for operation and process efficiency, data and information quality, software resiliency and productivity.
Visualization and analytics
- Benefit from an evolving knowledge graph loaded with high-quality data from multiple sources.
- Integrate with the other members of the enterprise ecosystem, including well established tooling for ML and data science, business analysis, message busses, databases, document stores, etc.
- Enable several search and information retrieval paradigms for different types of queries and stakeholders.
- Provide analytical dashboards for data points monitoring, related to the key data element. Identify patterns and correlations between multiple alert events. Suggest specific information or subsets of information about suspicious activities.
- Visual information consumption and investigative interfaces, replicating and enhancing the SMEs workflow.
Case Studies
-
Better Trade Surveillance by Using Ontotext’s GraphDB to Tackle Market Manipulation
A global bank uses Ontotext’s knowledge graph based solution to improve the trade surveillance system that provided alerts for potential market manipulation
-
Smart Adverse Media Monitoring Solution for Accelerating Negative News Disambiguation
Ontotext’s smart KYC Adverse Media Monitoring solution can ensure that multinational investment banks comply with regulatory requirements and are protected from reputational risk.
Products, Solutions and Services Involved
GraphDB
Semantic Data Modeling
