Risk managers are facing many risk management challenges, not least in the international programme space where there are increasing regulatory pressures and complex networks to deal with. But ultimately, the biggest challenge is the sheer amount of information available and the complexity of the risk management requirements, from multiple jurisdictions, each with their own unique compliance and regulatory challenges, to servicing issues and carrier setups. It is an extremely complex landscape and in the end, it is the job of the insurance industry to try and simplify that complexity.
The risk management community is currently looking for clarity of information, quality of data and, above all, an overview of that data. In addition, they are looking for analytics and insights from the data to support the decision-making process. And it is here that technology can provide the support and the means to make this happen.
The challenge of managing all this information is being met through an end-to-end digital risk management approach and through the technological delivery and integration of a variety of data sources. It is taking a traditional business model and transforming it into an aligned, interconnected digital business model.
Corporations no longer simply want the data – they now want to be able to use it to help them make better decisions, and not necessarily just in the realm of insurance, but also to support the business goals of their companies in a much wider risk management sense. Risk managers have moved on from simply taking a financial view on risk, and instead are taking a much more holistic risk management approach.
The difficulty for risk managers is that, in common with others, they have less resources and smaller budgets nowadays, but the complexity of the risk landscape that they are dealing with is increasing. They are in desperate need of investment in technology, as this is the only way for them to solve this conundrum. There is a fundamental change in mindset required as a result of this, and there will be different skillsets needed by risk managers and indeed the insurance industry as a result. It is always important to consider the impact of new technologies on the human element of risk management.
Supporting risk managers
The insurance industry has access to a very broad range of information, from portfolio- to industry-level data points. This wealth of information can be of great help for risk management to become a more strategic area for companies rather than simply about insurance placements. There is data around climate change, or political and social unrest, which can be useful when companies are looking to invest in new countries or open a new factory, and the data from the insurance industry can be used to help support such strategic decisions, giving the risk manager greater visibility and a more strategic role in their company. From a loss prevention point of view, it might be about new ways of building or managing plants, or fire technologies that prevent a loss in the first place. And it will involve tracking, monitoring and updating risk improvement actions at all locations globally.
In terms of international programmes, new technologies are enablers for risk managers to take a more holistic view, to optimise their insurance portfolio and ensure that the programme aligns with local regulations around the world. This kind of overview and control is especially important where a captive is involved.
Emergent technologies are transforming the insurance industry and the global insurance programme space, and have the potential to bring huge benefits and support to risk managers facing today’s many challenges. From application programming interface (API) and distributed ledger/blockchain technology (DLT), through to intelligent augmentation using robotic process automation (RPA) and artificial intelligence (AI), these new technologies are playing a crucial part in the digital transformation of risk management.
API for instance is taking connectivity to the next level, cutting out the inefficiencies of manual exchange of spreadsheet reports and cumbersome, non-value-add reconciliations. It offers externally facing system-to-system interfacing and enables seamless real-time integration with customer or broker risk management information systems or market platforms.
Large international commercial insurance is based on complex and tailor-made propositions with a high level of non-standard and unstructured information that needs to be processed. Recent advancements in AI and natural language programming (NLP – understanding how people organise their thinking, feeling, language and behaviour to produce results) have proven their great potential to increase the level of automation and augmented quality assurance.
Looking ahead, technology such as the Internet of Things is allowing live information to be collected from those insurable exposures – whether it be machines, containers or factories – on their wellbeing, how they are working, their location, or the risk of an incident. But while machines are becoming able to talk to us, the next challenge, of course, is to make sense of this data and turn it into business-relevant events or triggers. It is a huge technological challenge but there is a great opportunity to support loss prevention and risk mitigation.
The crucial elements are that risk managers need the data and the associated insights to be consistent, of high quality, and to be timely. And this is all about being connected with partners in the insurance industry so as to be able to efficiently process, manage and consolidate the various data streams. Ultimately, the right analytical capabilities, delivered through new technologies such as AI, can help risk managers make the right decisions for their businesses.
Contributed by Jonathan Newbery, global head of broker strategy & execution, commercial insurance, Zurich Insurance Company, and Armin Schaefer, head of digital & new technology, commercial insurance international programmes, Zurich Insurance Company.