Predictive Risk Analytics - Technology Landscape

Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. Predictive Risk Analytics (PRA) uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.” However, our RuleSphere research over the course of 2013 and 2014 has indicated that the current PRA vendors do not address the areas of enterprise resiliency and complexity management. For this reason, RuleSphere has entered this market with the help of our partner Ontonix S.r.l.

Current vendors in the Predictive Risk Analytics software application marketplace include the following vendors. But once you explore them, you will quickly find out that none of the vendors, except Ontonix / RuleSphere address enterprise resiliency, complexity management, critical infrastructure and our other application-focused solution areas:

• Angoss

• IBM Predictive Analytics


• Ontonix / RuleSphere International, Inc. < Leadership in Quantive Complexity Management, critical infrastructure oversight, internal audit programs for complexity management

• Oracle Data Mining

• Palantir


• Revolution Analytics

• Salford Systems

• SAP Predictive Analytics

• SAS Analytics

• Statistica

• Tibco Analytics Software

Ontonix provides a new Predictive Risk Analytics approach with a highly differentiated SaaS-based multi-tenant application. Ontonix and RuleSphere focus on helping companies to assess the mission-critical areas of enterprise infrastructure and resilience. Ontonix solutions are now available to customers in North America through RuleSphere.


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