How effective country risk analysis can support corporate strategy

Multinational companies often operate in highly volatile risk environments across the globe and one of their biggest challenges is to understand and manage the various risks they face across countries and regions. Hence, sourcing relevant and reliable data on country risks, analysing this data and then utilising it as part of corporate risk management and strategy-setting processes is of utmost importance to enable better strategic decisions.

Country risk management is a very complex subject matter, covering a whole spectrum of risk categories, including business, economic and political, public finance and regulatory, as well as human capital, infrastructure, technology and innovation, climate change, and natural resources risks, to name only a few. Companies require reliable country risk data to support key business decisions and strategies, for example when conducting an M&A transaction or when considering new business developments such as entering a new market or choosing where they are going to establish a new facility. They are looking to use data to assess the relative strengths and weaknesses of various alternative business and strategy options and allow for better-informed decision making.

Country risk management tools can help risk managers and other decision-makers up to the c-suite to better understand whether risks for a particular country are increasing or decreasing over time, to determine the key underlying risk drivers and trends, and to visualise otherwise complex risk data. The data and the analysis can be used not only to validate a prevailing perception or hypothesis about a risk, but also to identify new risks which might previously have been unrecognised.

Quality data
It is often challenging to find the kind of data that is required for sophisticated and comprehensive country risk analysis, because there is a multitude of potential data sources. The completeness, reputation and quality of the underlying data source is key. We at Zurich, for example, rely on data sources such as the World Bank, the IMF and the World Economic Forum – public data sources of the highest possible data quality – when collating country risk data.

But it is also about the quality of the data management of the platform or tool that is provided to the risk manager. If there is quality data from good sources, but it is collated in an inefficient or inadequate manner, this can have a negative impact on the reputation and credibility of the analysis and ultimately lead to significant biases in corporate decision-making processes.

We believe in providing ‘storm-proof data’, which means both collating data from the best possible data sources, and a platform using comprehensive data quality management processes that allow for making the data points comparable and adjustable, as well as being very transparent about what is being measured, and what kind of information is being used.

Analytical functionalities
Risk managers and other decision-makers are not just looking for country risk data, but also benchmarking information to understand best practice in the industry and the corporate sector overall about how to manage country risks. They are also looking for forecasts in order to better understand how certain country risks might evolve in the future. This could be over a short-term horizon, for example up to a month, but also over long-term horizon of up to a couple of decades. While conducting purely model-based, quantitative country risk forecasts is often very difficult – mainly due to the frequency and heterogeneity of much of the underlying data – it is key to enable risk managers to formulate and implement their own assumptions about potential future risk developments as part of a holistic country risk management framework.

The interconnectivity between risks is another important aspect for country risk management. For example, the impact of storms or other natural catastrophe events on the likelihood of business interruptions in a certain country or region. Country risk management is about getting a better picture of not only how risks materialise in one situation or region, but also how they are potentially interconnected. Much more attention is being paid to interconnected risks and modelling particular scenarios to assess the impact.

Companies are also starting to focus more strongly on the potential interactions of risks – for example, not just considering the risks to their properties, but the risks to the community that may be employed around their facility. This implies a careful consideration of both the ‘micro’ risks at company level and relevant ‘macro’ risks associated with the environment in which the company operates.

But data alone cannot make a decision for you; it can only make you more risk aware to enable better decision-making. A risk should not necessarily be discounted simply because there isn’t the data to prove it, and different scenarios should also be considered even if there isn’t a lot of supporting data.

Ultimately, companies require tools with comprehensive analytical functionalities to be able to use the data as creatively and flexibly as they need to support their overall corporate strategy. Multinational companies and those with global supply chains need to address country risks across many layers of their organisation, such as strategy, risk management, finance and treasury.

The right platform
Risk managers and other decision-makers expect to have a platform or tool that allows country risks to be comparable and put in a broader perspective, ideally being aligned with their own in-house data, as well as the ability to ‘slice and dice’ the data to create their own risk scenarios and categories based on the risk information available. They are looking for a platform with a pre-selection of country risks, enabling them to choose the risks that are relevant to their own company and create risk scenarios that are relevant to their organisation.

They also want capabilities and functionalities enabling them to manage the data and use it practically, for example time-series analysis, stress testing, and the ability to compare and benchmark their own data with the data in the risk management tool. It is also important in the context of a reporting framework to have the ability to showcase the value of the data for consideration by the c-suite, for M&A strategies or investment decisions, for example. Risk managers need the data to be credible when presenting to decision-makers and it undoubtedly helps if the data can be visualised to show, for example, cross-country and risk comparisons over time.

When it comes to country risks, it is about providing as much quantitative information through data as possible, and as much qualitative insight through expert analysis, to help organisations make better informed strategic and risk management decisions, and bring country risk up to where it belongs, in the c-suite.

Contributed by Christian Amon, senior proposition manager, Zurich Risk Room, Zurich Insurance, and Eugenie Molyneux, chief risk officer, commercial insurance, Zurich Insurance