A common perception of risk is that it only pertains to the probability of an occurrence, or the severity of a loss. While some organizations view risk more holistically, the majority are missing an opportunity to make risk management not only a business driver, but also a competitive advantage and a tool to reduce business uncertainty.
If we only see risk as a combination of frequency, severity, probability and cost, that limited view does not offer a true picture of a business' potential for loss as well as growth or profit. A holistic perspective on risk encompasses not just the downside, but also the upside. Advances in technology, infused with business expertise, are enabling organizations to adopt this holistic viewpoint. While not all risk can be avoided, transferred or insured, such as strategic risk, technology-enabled risk management empowers risk owners to better identify risk and make informed decisions to avoid, retain or transfer the risk, or even profit from it by charging the customer for it.
In the past, risk professionals used qualitative methods or at best relied on manual sources of data, eventually shifting to spreadsheets, which were effectively the first risk management information systems. A fundamental problem with spreadsheets is that they don't show all the relevant data for making risk management decisions. Further advances that introduced commercial RMIS compiled data in one place from multiple sources, but the current generation of this technology has limitations: typical systems only use the organization's own risk data.
The future of risk technology is far broader in scope. It is about aggregating and integrating risk or claims data — not only the risk owner's, but also that of collaborators, peers and the broader market and industry. In addition, there are a myriad of external data sources; data such as weather, traffic, locations of hospitals or key landmarks and driving history, among several others. This leads to a treasure trove of data that unlocks the power of sophisticated analytics. Layering in more recent methodologies such as artificial intelligence, machine learning and neural networks, organizations can identify and analyze risks as never before. One result of this approach is the ability to accurately quantify the probability and severity of risks and claims.
Value in risk quantification
Imagine the risk equivalent of a credit score and how that could enable businesses to manage risk. Data-driven risk scoring applies to claims as well. These metrics increase decision accuracy and allow risk owners to make informed decisions about risk retention and transfer. For insurers, risk scores and claims scores could enhance underwriting and loss reserving. The technology to deliver accurate assessment and outcomes is here today, and it won't be long before the risk industry comes to rely on this approach and use predictive methods to predict risk, claims and reserves, among other things.
Property/casualty market conditions are harder than they have been in nearly two decades. The cost of risk transfer, through primary insurance and reinsurance, is high. When risk owners and insureds opt to retain more risk, they need to be very sure of the cost of that retained risk. In addition, insureds can make decisions selecting the best risk-retention point and have the data to have effective discussions with the insurers. These are some of the additional benefits of technology-enabled risk management.
Value in digital integration
Another trend is the adoption of digitally integrated systems, in which risk data can flow through the entire spectrum of retention, transfer and claims. Digital integration, augmented by Artificial Intelligence (AI) and analytics, can help simplify the understanding of complex risks in the business. It also enables better communication among risk managers, agents, brokers, and insurers. The coronavirus pandemic offers many lessons for risk professionals, but one of them is the value of online integrated data systems, accessible from anywhere. With so many organizations shifting to remote work, these systems are an important enabler of collaboration and informed decision-making.
The technology of risk analytics is now at the point that it is possible to derive insights from unstructured data — the kind that exists in an email, adjuster or margin notes and other sources not confined to data fields on electronic forms — by leveraging Natural Language processing, Sentiment Analysis and Word Trending. There is often more valuable and nuanced information in unstructured data, which often delivers insights from unknown perspectives (as opposed to structured data, which represent the bias or viewpoint of the originator of the structure). Risk professionals already know that relevant data exists throughout their organizations and a relative fraction of it finds its way into risk management systems. Silos and pockets of knowledge are present in every organization. Bringing risk and business data from disparate sources together improves the resolution of the risk picture. Integration of structured and unstructured data, with sophisticated analytics, will be a game-changer in the world of risk management. Technology today can automatically identify additional risks using AI techniques to scan data, compare benchmarks and even predict the severity and costs of risks.
The future of risk management offers exciting possibilities for innovation in risk assessment, risk financing and how insurance is transacted. In the next few years, integrators and connectors will merge the domains of data, analytics and business expertise and make risk management even more valuable in differentiating business offerings, and driving and sustaining profitable growth. Investing in automation of the entire risk management process including risk identification, pattern recognition and straight-through claims processing will further help businesses be competitive. Salil Donde is the chief executive officer of Ventiv Technology, a leading global provider of risk, insurance and underwriting technology.