Data-driven Operational Risk Management

Operational risk losses have famously led to the complete demise of financial institutions, with more than 100 reported losses exceeding US$100 million in recent years. This executive report demonstrates how to avoid such severe losses through improved operational risk data collection. Most organisations currently rely on soft subjective op risk data such as self assessments. But objective measurements reflect a truer picture of risk. Using primary research, this practical report demonstrates how you can use hard data to improve your operational risk measurement. Robert Scott Levine tackles this data challenge based on in-depth knowledge gained as an experienced auditor, fraud examiner, data security manager and risk systems implementer. The core focus of the report is on how you can plan, implement and manage the available data sources for improved operational risk management. It also shows you how to maximise the rich internal and external data sources that are often overlooked. The practical examples given throughout the report clearly demonstrate the business benefits of operational risk management, beyond just the need for regulatory compliance. It also looks at the techniques that you can automate to produce early warning operational risk indicators. Highly recommended for operational risk practitioners, auditors, examiners and compliance staff who will benefit from learning how to pull in the right operational data and how to automate the collection, cleansing, aggregation, correlation and analysis processes to do your job more effectively.