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Against a backdrop of financial and macroeconomic uncertainty, constant regulatory change, and ever increasing scrutiny of the most efficient use of capital, insurers are under pressure to improve the accuracy and usefulness of economic capital models, and to embed capital measures into strategic business management and decision making.

We take a retrospective look at one life insurer’s implementation of an economic capital model, where Willis Towers Watson’s RiskAgility Economic Capital Aggregator (EC) model has been in place for a number of years. In particular we consider key drivers and requirements of the project, early stage learnings, and how these have impacted the business, including what the model has enabled them to do to respond to the changes in its wider business environment.

Background

Our client is a multinational insurer operating in life, general and health insurance markets across the Americas, Europe, and Asia. Prior to RiskAgility EC, they had a capital model which provided relevant information to management but required a lot of time and resource to setup and run. This created significant time pressure around analysing results and maintaining a robust model governance framework.

At the same time, the insurer’s business requirements for the economic capital model were evolving and expanding in line with internal and external pressures.

In response, in 2012 the insurer undertook a review of its economic capital modelling capabilities and options, leading to the deployment of RiskAgility EC as the primary economic capital calculation engine. The implementation commenced in the first quarter of 2013, and an initial model was completed within six months, which was then moved into a production environment.

Implementation goals

The initial goal was to deliver an end-to-end economic capital modelling process which would satisfy the requirements of internal and external stakeholders, primarily:

  • Regulators: The insurer wanted a model which would be fit for use in Own Risk and Solvency Assessment (ORSA) reporting, and which would meet regulatory requirements.
  • Ratings agencies and investors: The model needed to produce measures of capital requirements that would usefully and reliably educate credit ratings agencies and existing and potential investors about the scale and nature of risks faced by the business.
  • Board and other management functions: The model had to enable the board and other management functions to make risk management and strategic decisions about the deployment of capital, the use of reinsurance and hedges, the allocation of assets, and the structure of products. An implication of this requirement was that the model needed to calculate both economic capital and earnings at risk metrics.

Building the foundations

A joint team consisting of the insurer’s employees and Willis Towers Watson’s experts in economic capital modelling worked on the implementation, with the structure of the team designed in a way which would enable the insurer’s personnel to gradually become expert in the use of RiskAgility EC and the associated methodology. This involved the following key steps:

  • Establish the initial model framework and high level methodology
  • Design workflow processes for project governance, reporting, and model updates
  • Receive and prepare data
  • Build the initial model in RiskAgility EC
  • Perform testing and model sign-off
  • Train business users on the model methodology and software interface
  • Develop a roadmap for potential future enhancements

Issues resolved by the joint project team during the implementation phase included:

  • Technical calculation components: The correlation matrix originally constructed between risk factors was determined not to be positive semi-definite (PSD), a necessary pre-condition for the calculation. The team was able to use RiskAgility EC’s built-in algorithm to find a solution.
  • Management actions: A number of questions needed to be answered around how to account for the modelling of management actions and specific product features which could be used to manage risk during a stress scenario. The project team developed techniques to incorporate these in line with the client’s business strategy.
  • Process efficiencies: The project team identified a number of components of the end to end modelling process as sub-optimal and altered them to improve overall speed and efficiency. For example, it developed guidelines around scenario selection for the model fitting process and established consistent templates for managing inputs and outputs.

Reaping the benefits

The implementation of RiskAgility EC has created significant benefits for the client, including:

Regulatory reporting

The outputs from the economic capital model now form a key component of ORSA reporting and support the business in discussions with the regulators. In addition, the collaborative nature of the project team, the accompanying training and the documentation developed give the client’s users of the model confidence to have conversations on model process and methodology.

Ratings agencies

Rating agencies have responded positively to the economic capital allocation methodology embedded in RiskAgility EC, even resulting in a ratings upgrade for one of the insurer’s entities after the methodology was discussed with the agency.

Internal decision making

Perhaps less tangibly, results from the RiskAgility EC model are now being used within the company at multiple levels to support decision making, including but not limited to:

  • Scenario analysis tools allow them to understand the events to which they are most vulnerable, and therefore which risks to manage most actively.
  • Asset mix studies allow the asset management teams to assess the most capital efficient allocation of assets.
  • Business mix studies allow the board to understand which groupings of products offset each other’s risk profiles, and therefore how to grow the business while minimising capital requirements.
  • Hedge studies allow hedging teams to understand how hedges can be used most efficiently to reduce the company’s risk.
  • Forward looking projections allow them to understand where the business is likely to need additional capital in the future, and therefore how to head off potential unwanted risks.

Model management and controls

RiskAgility EC provides a full governance and control framework for modelling inputs, outputs and calculations. Within this framework, each version of each input going into the model is tracked and version controlled and is fully auditable at each step of the modelling process – so that all calculations can be traced back to specific inputs.

The insurer took advantage of these features throughout the model development process, and the control mechanism gave management and other stakeholders the confidence to trust the results which were being produced. In particular, they found:

  • The in-built and automated audit report generation functionality saved weeks of time from the team’s business as usual processes, which would otherwise have been spent collecting, reviewing and documenting all inputs.
  • The access control framework embedded within the model allowed the model owners to split up the model and control access to specific components.
  • The modelling environment stored inputs and outputs centrally, but allowed inputs to be specified and outputs to be viewed in a distributed way, by multiple team members in parallel. This avoided much of the traditional practical inefficiencies around model development and allowed the team to focus on adding to the model rather than passing components of it around.

The multiple demands now being placed on economic capital models can mean rethinking a modelling approach from the ground up. Daunting as this may seem, this case study is an example of what can be done and the lasting benefits being realised.