Optial delivers systems for insurers to assess and manage risk more effectively enabling superior loss control activities through more accurate pricing of risk, operational efficiencies and enhanced data analysis.
The operational risks that insurers now face have become more complex, more potentially devastating and more difficult to anticipate. Although operational risk is possibly the largest threat to the solvency of insurers, it is a relatively new risk category. Operational risk is defined as the capital charge for “the risk of loss arising from inadequate or failed internal processes, people, systems or external events”. This definition is based on the underlying causes of such risks and seeks to identify why an operational risk loss occurred. It also indicates that operational risk losses result from complex and disconnected interactions between risk and business processes.
Unbundling Operational Risks
Unbundling operational risk from other risk types in risk management and risk measurement can help prevent failures. This holds equally true for smaller and larger losses. Often larger losses are the cumulative effect of a number of smaller losses which often occur when the main focus is on managing the business rather than operational risk.
Optial and the Challenges in Insurers’ Operational Risk Management
Insurers have not historically gathered operational risk data across their range of activities. Today the major difficulties and challenges that insurers face are closely related to the identification of and estimation of the level of exposure to operational risk. A distinction can be made between internal and external loss data, risk self-assessment, supporting techniques, tools and governance.
Loss data provides a means of measuring operational risk. Although internal loss data is considered to be the most important source of information, insufficient and poor quality internal loss data are typical. While insurers can supplement their internal loss data with external data from consortia such as ORIC and ORX, external data raises a number of issues such as reliability, relevancy, aggregation and consistency. Therefore it is important for insurers to improve the quality of their internal loss data and data-gathering techniques.
Risk self-assessment and scenario analysis can be an extremely useful way to overcome the problems of internal and external loss data. They can be used in situations where it is impossible to construct a probability distribution and also enable the capture of risks that relate to areas for which there is unlikely to be historic loss data, for example new technology and products.
Optial is a web-based management system that incorporates the full spectrum of operational risk, governance, risk and compliance as well as audit and business continuity activities to support insurers in the effective management of operational risk.
Optial provides support for:
It therefore provides the infrastructure for creating and implementing the broad range of control, risk management and compliance processes that are crucial for insurers generally and for compliance with the Solvency II directive.
Added to this, Optial's highly configurable nature means that organisations can be up and running very quickly.
Solvency II Directive for (Re)Insurers
Operational Risk has been identified as a separate risk category in Solvency II which is now on track to put greater emphasis on the link between risk management and risk measurements of operational risk.
In terms of the Solvency II framework, pillars 2 and 3 particularly apply to operational risk management for insurers, while Pillar 1 is largely the requirement for insurers to understand the nature of their risk exposure and hold regulatory capital to a confidence interval of 99.:5%.
The second pillar of the Solvency II framework deals with the qualitative elements and sets out requirements for the governance and risk management of insurers. While the third pillar focuses on disclosure and transparency of requirements by seeking to harmonise reporting and provide insight into insurers’ risk and return profiles.