Benchmax vs Mstarlib

Benchmax demonstrates your company’s compliance with operational standards 24/7. Does your company work to a set of operations standards and procedures where compliance is mandated by industry oversight or internally defined? If so, it’s essential to achieve them consistently. Benchmax provides the assurance that your teams are achieving those standards. The product provides your operations teams with insight into the performance of people, processes, and assets against standards across the organisation. MULTI-LEVEL ACCESS With access levels for workers, admin staff, verifiers, business decision makers and external auditors, Benchmax provides a range of views to demonstrate compliance. And you can view that compliance across all business locations globally, or drill down into regions, business functions, teams, and individuals. Scalable Benchmax is both scalable and customisable. The content management system allows you to import your own company best practices or to leverage relevant local or international standards. MULTILINGUAL Benchmax architecture is multilingual and can be deployed by organisations with locations across the globe and staff who speak different languages. HIGHLIGHT OPPORTUNITIES FOR IMPROVEMENT. With self-assessment and verifier grading, Benchmax provides comparative scores against specific tasks. This helps to focus improvement drives for focused training or best practice enhancement. Individual achievements are reflected in real time, so you can see who in your business has achieved the required level of compliance with requirements. It also shows how each team performs against standards, and against other teams. By seeing performance blockers/drivers on key issues, you can resolve such problems as consistency or scheduling. So, you can use this to drive overall performance improvement, reduce costs and enhance productivity.

Mstarlib is an application for operational risk managers in the banking industry. It provides news on recent events and recent studies. All information is put into perspective of operational risk scenarios. The scenarios are modeled with the XOI (Exposure, Occurrence, Impact) method based on Bayesian networks.