Adaptive Mesh Analytics for Enterprise Risk Compliance
Keywords:
Correlated enterprise risk; Event-driven architecture; Data-driven risk signals; Decision fabric; Enterprise risk coordination; Enterprise risk management; Regulatory compliance; External insurance-scoring data.Abstract
Enterprise risk coordination consumes significant resources as organizations rely on intensive effort shifts for risk assessments. These coordinations activities often lack a continuous knowledge of enterprise-wide operational conditions and the associated risk changes. Data-driven risk signals enable a more scalable, adaptive, near-real-time risk coordination operated under a decision fabric. Together with a strategic enterprise risk coordination activity, these signals support the analysis of risk and product compliance status and forecasts. The data-driven signals improve usage of data and reporting capabilities, promoting organizational learning for governmental oversight of a real-time enterprise risk landscape. The data signals are composed of risk tables and operational dashboards accounting for a variety of risk conditions and scenarios in the organization.
Enterprise risk management and compliance represent burdensome operations in many organizations. The composition and transmission of risk assessments consume considerable effort, especially around risk coordination activities dealing with accumulated and aggregated risks. A risk signal, based on consolidated external and internal data, could facilitate a more continuous coordination trend and even trigger alerts once tolerance limits are reached. Various triggers would support continuous usage, possible reporting, and update-resilient decision support serving oversight and coordination.
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