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Enterprise risk management

Proactively identify and mitigate risk across your organization

In today’s continually changing business environment, the board, risk committees and senior management are challenged to:

  • Set the entity’s risk governance posture and tone
  • Establish specific strategic objectives and interrelated risk appetite
  • Implement and maintain a formal risk management system sufficient to identify and manage risks

The interaction of an organization's risks and potential impact on its earnings, capital and strategic plans necessitate risks to be assessed, evaluated and managed across the entire entity.

Wipfli’s experienced team assists boards and senior management to establish or enhance an appropriate risk management system to meet the organization’s strategic objectives. Through a tailored approach, Wipfli professionals use a combination of resources to create a program to:

  • Establish and reinforce the entity’s risk culture
  • Articulate and monitor adherence to the organization’s risk appetite
  • Develop and use an enterprise-wide risk management system to identify, measure, monitor and control risks

The Wipfli enterprise risk management team works closely with organizations to identify, develop and integrate key risk governance components and related reporting systems to facilitate the timely identification, measurement, monitoring and controlling of risks.

Model validation

In today’s business world, quantitative analysis models are widely used to improve business decision-making. Model use covers a wide range of focus areas such as credit underwriting, interest rate risk exposure, valuing assets and even general risk assessments. Unfortunately, the use of models introduces its own set of exposures related to the model. Model risks may occur at any time in the model validation process, starting with the design and development of the model through implementation and usage.

We use a systematic analytical model validation approach. The core elements of our validation activities include:

  • The evaluation of the model’s conceptual soundness, including developmental evidence.
  • Ongoing monitoring, including process verification and benchmarking.
  • An outcomes analysis, including back testing.