Risk Finance Optimisation: Insurance and risk analytics tool for organisations

As risk events worldwide unfold quickly with increasing complexity, organisations in Asia are facing significant challenges in optimally balancing risk transfer and retention. To conduct the risk financing process with due diligence, organisations now need to deploy a risk analytics tool that not only pursues least-cost coverage for loss exposures and post-loss financial resource availability, but also identifies and quantifies ‘hidden’ risks that pose severe consequences if left unaddressed.

Is benchmarking sufficient in risk financing?

The first step most organisations take is benchmarking. The key issue is that relying on benchmarking alone to make important insurance program design decisions could result in unidentified risk exposures and exposure gaps.

Furthermore, benchmarking provides guidance only on common market or industry practices, is unable to be tailored to a business’s specific risk profile and tolerance levels, and provides only a historical view while being prone to confirmation bias.

As your organisation’s stakeholders increasingly scrutinise the performance of insurance programs, risk managers need to provide meaningful justification for their insurance and risk decision making (e.g. allocation of capital) in a way that is robust and accurately quantifiable. 

Risk Finance Optimisation: An enhanced risk analytics tool

To address the urgent need for an accurate, customisable, and forward-looking risk analytics tool, Marsh developed Risk Finance Optimisation (RFO), a data-driven exercise that provides meaningful and actionable real-time answers to program structure queries and identifies the most cost-efficient means to finance risk at both the portfolio and product line levels.

Case Study #1: Manufacturing

Amidst a hardening insurance market, a multinational electronics contract manufacturer faced sharply increasing property damage/business interruption (PDBI) renewal premiums. They engaged Marsh to determine the optimal renewal deductible structure under current market conditions. Through a Risk Finance Optimisation study, Marsh identified over 6% in expected savings to the Economic Cost of Risk (ECOR) through a 2.5x increase in deductible.

How does Risk Finance Optimisation work?

Leveraging Marsh’s proprietary financial model, extensive loss data lake, and actuarial model-building expertise, Risk Finance Optimisation represents a robust approach to designing and optimising your risk management strategy using a five-step process: 

Guided by Marsh’s risk financing directors, the Risk Finance Optimisation risk analytics process will help your organisation answer these four key questions:

• How much financial headroom is available for risk retention?
• Will a higher deductible breach our risk tolerance level?
• Are my policy limits sufficient? How volatile could my losses get?
• Are the quoted premiums value for money?

Organisations that undertake RFO will get the comprehensive answers they need with access to risk analytics tool and modelling in real time.

Benefits of Risk Finance Optimisation as a risk analytics tool

With Risk Finance Optimisation, organisations are able to view insurance as a source of capital that can be used to help manage and mitigate volatility alongside other sources available to you to finance insurance losses, for example debt and equity.

Organisations can expect the following benefits and outcomes upon the completion of the RFO process:

• Potential for significant cost savings to your Economic Cost of Risk. 
• Deeper understanding of your risk profile and risk financing trade-offs.
• Measurement of the economic value that insurance can deliver.
• Explore alternative risk retention and transfer options, e.g. deductibles, limits, captive solutions.

Powered by data intelligence, the RFO process empowers risk managers and organisations with scientific and actionable insights that enable confident risk management decision-making.

Case Study #2: Transportation Services

Anticipating a challenging auto liability renewal, a transportation services company specialising in logistics engaged Marsh for analytical support in determining the optimal insurance structures. Risk Finance Optimisation was used to create a baseline cost of risk and identify areas where the organisation could experience cost pressure. Leveraging the organisation’s captive balance sheet, RFO risk analytics identified layers of insurance that could be more efficiently retained versus transferred, and helped the organisation avoid material fixed premium increases without needing additional capital for the captive. Total cost of risk was also reduced.