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 and frameworks.

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 risk transmission pathways, including causal relationships, tipping points and networked cascade effects between risks along the full value chain. RISGRA® is built using a new, highly expressive hyper-graph language that includes 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 Generative 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.