RISGRA® - in a Nutshell

What

RISGRA® is a powerful Entity-Relationship Knowledge Graph model (Ontology) that comprises a comprehensive, integrated set of Enterprise Risk Management (ERM) concepts & constructs.

Sitting at the functional interface between Risk, Finance, Compliance and Operations, RISGRA® is a holistic representation of (a) the Risk Universe (Taxonomy) and (b) the risk management capabilities (Ontology), of a complex large-corporate organisation (‘public interest entity’ - PIE), operating in a regulated sector, set in the context of its wider end-to-end value chain.

RISGRA® is a higher-level implementation of the Entity-Relationship graph model, making extensive use of nested and chained Relations (hyper-graph / hyper-edge), necessary to reflect the deeply inter-connected, dynamic and nuanced nature of risk, and risk management capabilities, in a regulated organisation.

RISGRA® models the complex, non-linear decision processes, including causal links, tipping points and networked cascade effects between risks along the full value chain, and integrates rules, weights and temporal analysis to enable powerful inference.

So what?

RISGRA® is a foundational (symbolic) graph model, with commercial applications that include:

  • Neuro-Symbolic AI in which Symbolic foundational hyper-graph models such as RISGRA® bring real-world “Judgement” as guard-rails to counter-balance and complement the “Predictive” power of Neural AI and Agentic AI models (LLM + ML). This is a critical requirement, underpinning regulatory compliance as organisations integrate Agentic AI capability in to their operating models and supply chains;

  • Data Mesh: RISGRA® schema enables traversal and powerful querying across disparate and often inconsistent data sets that span the risk, finance, operations & compliance domains;

  • Augmentation of pan-organisation and pan-value-chain Decision Intelligence capabilities and projects;

  • Digital Twin: design, build and compliant operation.

Sector-specific applications - a mix of verticals & horizontals - varying stages of development, for example:

  • Financial services: corporate & commercial banking; general insurance; asset management;

  • External audit: traversal of granular corporate reporting disclosures to discern the (IFRS & ISSB-prescribed) connecting narrative between sustainability related financial disclosures, and general purpose financial disclosures;

  • Aviation: commercial airline operation and compliance; aviation insurance underwriting;

  • Restructuring & Insolvency [ pipeline ]: traversal and querying over large, heterogeneous, incomplete data sets, using rules and inference to surface otherwise hidden connections, for example in support of complex cross-border asset tracing; and drive resource / time efficiencies in insolvency & recovery professional appointments;

  • Agricultural lending [ pipeline ]: agricultural credit risk - assessment, underwriting and portfolio management;

Now what?

We’d welcome an informal discussion to explore how RISGRA® foundational hyper-graph ERM models could support compliant adoption of Agentic AI in your organisation.

Contact us here.