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NIGEL ALLENMay 05, 2020
A solution shared
A solution shared
A Solution Shared
May 05, 2020

The Risk Data Open Standard is now available, and active industry collaboration is essential for achieving wide-scale interoperability objectives On January 31, the first version of the Risk Data Open Standard™ (RDOS) was made available to the risk community and the public on the GitHub platform. The RDOS is an “open” standard because it is available with no fees or royalties and anyone can review, download, contribute to or leverage the RDOS for their own project. With the potential to transform the way risk data is expressed and exchanged across the (re)insurance industry and beyond, the RDOS represents a new data model (i.e., a data specification or schema) specifically designed for holding all types of risk data, from exposure through model settings to results analyses. The industry has longed recognized that a dramatic improvement in risk data container design is required to support current and future industry operations. The industry currently relies on data models for risk data exchange and storage that were originally designed to support property cat models over 20 years ago. These formats are incomplete. They do not capture critical information about contracts, business structures or model settings. This means that an analyst receiving data in these old formats has detective work to do – filling in the missing pieces of the risk puzzle. Because formats lack a complete picture linking exposures to results, highly skilled, well-paid people are wasting a huge amount of time, and efforts to automate are difficult, if not impossible, to achieve. Existing formats are also very property-centric. As models for new insurance lines have emerged over the years, such as energy, agriculture and cyber, the risk data for these lines of business have either been forced suboptimally into the property cat data model, or entirely new formats have been created to support single lines of business. The industry is faced with two poor choices: accept substandard data or deal with many data formats – potentially one for each line of business – possibly multiplied by the number of companies who offer models for a particular line of business. The industry is painfully aware of the problems we are trying to solve. The RDOS aims to provide a complete, flexible and interoperable data format ‘currency’ for exchange that will eliminate the time-consuming and costly data processes that are currently required  Paul Reed RMS “The industry is painfully aware of the problems we are trying to solve. The RDOS aims to provide a complete, flexible and interoperable data format ‘currency’ for exchange that will eliminate the time-consuming and costly data processes that are currently required,” explains Paul Reed, technical program manager for the RDOS at RMS. He adds, “Of course, adoption of a new standard can’t happen overnight, but because it is backward-compatible with the RMS EDM and RDM users have optionality through the transition period.” Taking on the Challenge The RDOS has great promise. An open standard specifically designed to represent and exchange risk data, it accommodates all categories of risk information across five critical information sets – exposure, contracts (coverage), business structures, model settings and results analyses. But can it really overcome the many intrinsic data hurdles currently constraining the industry? According to Ryan Ogaard, senior vice president of model product management at RMS, its ability to do just that lies in the RDOS’s conceptual entity model. “The design is simple, yet complete, consisting of these five linked categories of information that provide an unambiguous, auditable view of risk analysis,” he explains. “Each data category is segregated – creating flexibility by isolating changes to any given part of the RDOS – but also linked in a single container to enable clear navigation through and understanding of any risk analysis, from the exposure and contracts through to the results.” By adding critical information about the business structure and models used, the standard creates a complete data picture – a fully traceable description of any analysis. This unique capability is a result of the superior technical data model design that the RDOS brings to the data struggle, believes Reed. “The RDOS delivers multiple technical advantages,” he says. “Firstly, it stores results data along with contracts, business structure and settings data, which combine to enable a clear and comprehensive understanding of analyses. Secondly, the contract definition language (CDL) and structure definition language (SDL) provide a powerful tool for unambiguously determining contract payouts from a set of claims. In addition, the data model design supports advanced database technology and can be implanted in several popular DB formats including object-relational and SQL. Flexibility has been designed into virtually every facet of the RDOS, with design for extensibility built into each of the five information entities.” “New information sets can be introduced to the RDOS without impacting existing information,” Ogaard says. “This overcomes the challenges of model rigidity and provides the flexibility to capture multivendor modeling data, as well as the user’s own view of risk. This makes the standard future-proof and usable by a broad cross section of the (re)insurance industry and other industries.” Opening Up the Standard To achieve the ambitious objective of risk data interoperability, it was critical that the RDOS was founded on an open-source platform. Establishing the RDOS on the GitHub platform was a game-changing decision, according to Cihan Biyikoglu, executive vice president of product at RMS. You have to recognize the immense scale of the data challenge that exists within the risk analysis field. To address it effectively will require a great deal of collaboration across a broad range of stakeholders. Having the RDOS as an open standard enables that scale of collaboration to occur. “I’ve worked on a number of open-source projects,” he says, “and in my opinion an open-source standard is the most effective way of energizing an active community of contributors around a particular project. “You have to recognize the immense scale of the data challenge that exists within the risk analysis field. To address it effectively will require a great deal of collaboration across a broad range of stakeholders. Having the RDOS as an open standard enables that scale of collaboration to occur.” Concerns have been raised about whether, given its open-source status and the ambition to become a truly industrywide standard, RMS should continue to play a leading role in the ongoing development of the RDOS now that it is open to all. Biyikoglu believes it should. “Many open-source projects start with a good initial offering but are not maintained over time and quickly become irrelevant. If you look at the successful projects, a common theme is that they emanate from an industry participant suffering greatly from the particular issue. In the early phase, they contribute the majority of the improvements, but as the project evolves and the active community expands, the responsibility for moving it forward is shared by all. And that is exactly what we expect to see with the RDOS.” For Paul Reed, the open-source model provides a fair and open environment in which all parties can freely contribute. “By adopting proven open-source best practices and supported by the industry-driven RDOS Steering Committee, we are creating a level playing field in which all participants have an equal opportunity to contribute.” Assessing The Potential Following the initial release of the RDOS, much of the activity on the GitHub platform has involved downloading and reviewing the RDOS data model and tools, as users look to understand what it can offer and how it will function. However, as the open RDOS community builds and contributions are received, combined with guidance from industry experts on the steering committee, Ogaard is confident it will quickly start generating clear value on multiple fronts. “The flexibility, adaptability and completeness of the RDOS structure create the potential to add tremendous industry value,” he believes, “by addressing the shortcomings of current data models in many areas. There is obvious value in standardized data for lines of business beyond property and in facilitating efficiency and automation. The RDOS could also help solve model interoperability problems. It’s really up to the industry to set the priorities for which problem to tackle first. The flexibility, adaptability and completeness of the RDOS structure create the potential to add tremendous industry value “Existing data formats were designed to handle property data,” Ogaard continues, “and do not accommodate new categories of exposure information. The RDOS Risk Item entity describes an exposure and enables new Risk Items to be created to represent any line of business or type of risk, without impacting any existing Risk Item. That means a user could add marine as a new type of Risk Item, with attributes specific to marine, and define contracts that cover marine exposure or its own loss type, without interfering with any existing Risk Item.” The RDOS is only in its infancy, and how it evolves – and how quickly it evolves – lies firmly in the hands of the industry. RMS has laid out the new standard in the GitHub open-source environment and, while it remains committed to the open standard’s ongoing development, the direction that the RDOS takes is firmly in the hands of the (re)insurance community.   Access the Risk Data Open Standard here

Helen YatesSeptember 06, 2019
Background-RDO
Background-RDO
A Data Step Change
September 06, 2019

With the introduction of the Risk Data Open Standard, the potential now exists to change the way the (re)insurance industry interacts with risk modeling data In May 2019, RMS introduced the (re)insurance industry to a new open data standard. Set to redefine how the market structures data, the Risk Data Open Standard (RDOS) offers a flexible, fully transparent and highly efficient framework — spanning all risks, models and contracts and information sets — that can be implemented using a wide range of data technology. “The RDOS has been constructed to hold the entire set of information that supports the analysis of any risk” Ryan Ogaard RMS That this new standard has the potential to alter fundamentally how the market interacts with exposure data is not hyperbole. Consider the formats that it is replacing. The RMS Exposure and Results Data Modules (EDM and RDM) have been the data cornerstones of the property catastrophe market for over 20 years. Other vendors use similar data formats, and some catastrophe modeling firms have their own versions. These information workhorses have served the sector well, transforming the way property catastrophe risk is transacted, priced and managed. Out With the Old But after over two decades of dedicated service, it is past time these formats were put out to pasture. Built to handle a narrow range of modeling approaches, limited in their ability to handle multiple information formats, property-centric by design and powered by outdated technology, the EDM/RDM and other formats represent “old-gen” standards crumbling under current data demands. “EDM and RDM have earned their status as the de facto standards for property catastrophe data exchange,” explains Ryan Ogaard, senior vice president at RMS. “Clearly documented, easy to implement, SQL-based, they were groundbreaking and have been used extensively in systems and processes for over 20 years. But the industry has evolved well beyond the capabilities of all the existing formats, and a new data model must be introduced to facilitate innovation and efficiency across our industry.” The RDOS is not the only attempt to solve the data formatting challenge. Multiple other initiatives have been attempted, or are underway, to improve data efficiency within the insurance industry. However, Ogaard believes all of these share one fatal flaw — they do not go far enough. “I have been involved in various industry groups exploring ways to overcome data challenges,” he explains, “and have examined the potential of different options. But in every instance, what is clear is that they would not advance the industry far enough to make them worth switching to.” The switching costs are a major issue with any new data standard. Transitioning to a new format from one so firmly embedded within your data hierarchy is a considerable move. To shift to a new standard that offers only marginal relief from the data pains of the current system would not be enough. “The industry needs a data container that can be extended to new coverages, risk types or contracts,” he states. “If we require a different format for every line of business or type of model, we end up with a multiplicative world of data inefficiency. Look at cyber risk. We’ve already created a separate new standard for that information. If our industry is truly going to move forward, the switch must solve our challenges in the short, medium and long term. That means a future-proof design to handle new models, risks and contracts — ideally all in one container.” Setting the Standard Several years in the making, the RDOS is designed to address every deficiency in the current formatting framework, providing a data container that can be easily modified as needs change and can deliver information in a single, auditable format that supports a wide range of analytics. It is already used within the framework of the recently launched risk management platform RMS Risk Intelligence™ “The RDOS is designed to be extended across several dimensions,” Ogaard continues. “It can handle the data and output to support any modeling algorithm — so RMS, or anyone else, can use it as a basis for new or existing models. It was originally built to support our high-definition (HD) modeling, which requires a domain-specific language to represent policy or treaty terms and structures — that was not possible with the old format. During that process, we realized that we should design a container that would not have to be replaced in the future when we inevitably build other types of models.” The RDOS can also span all business lines. It is designed to accommodate the description of any risk item or subject at risk. The standard has inherent flexibility — new tables can be introduced to the framework without disrupting existing sets, while current tables can be extended to handle information for multiple model types or additional proprietary data. “EDM and RDM were fundamental to creating a much more stable, resilient and dynamic marketplace,” says Ogaard. “That level of modeling simply isn’t available across other lines — but with the RDOS it can be. Right off the bat, that has huge implications for issues such as clash risk. By taking the data that exists across your policy and treaty systems and converting it into a single data format, you can then apply an accumulation engine to evaluate all clash scenarios. So, essentially, you can tackle accumulation risk across all business lines.” It is also built to encompass the full “risk story.” Current data formats essentially provide exposure and modeling results, but lack critical information on how the exposure was used to create the results. This means that anyone receiving these data sets must rely on an explanation of how an analysis was done — or figure it out themselves. “The RDOS has been constructed to hold the entire set of information that supports the analysis of any risk,” he explains. “This includes exposures, (re)insurance coverage information, the business structure used to create the results, complete model settings and adjustments, the results, and the linkage between the information.  Multiple analyses can also be included in a single container. That means more time can be spent on accurate risk decision-making.” The RDOS is also independent of any specific technology and can be implemented in modern object relational technology, making it highly flexible. It can also be implemented in SQL Server if the limitations of a relational representation are adequate for the intended usage. The insurance industry, and cat analytics software, has been slow to adopt the power of tools such as Parquet, Spark, Athena and other new and powerful (and often open-source) data tools that can drive more data insights. Opening the Box For the RDOS to achieve its full potential, however, it cannot be constrained by ownership. By its very nature, it must be an open standard operated in a neutral environment if it is to be adopted by all and serve a larger market purpose. RMS recognized this and donated the RDOS to the industry (and beyond) as an open standard, harnessing open-source principles common in the software industry. Taking this route is perhaps not surprising given the executive leadership now in place at the company, with both CEO Karen White and Executive Vice President of Product Cihan Biyikoglu having strong open-source credentials. “When they saw the RDOS,” Ogaard explains, “it clearly had all of the hallmarks of an open-source candidate. It was being built by a leading market player with an industrywide purpose that required a collaborative approach.” What RMS has created with the RDOS represents a viable standard — but rather than a finished product, it is a series of building blocks designed to create a vast range of new applications from across the market. And to do that it must be a completely open standard that can evolve with the industry. “Some companies claim to have open standards,” he continues, “but by that they mean that you can look inside the box. Truly open standards are set up to be overseen and actually modified by the industry. With the RDOS, companies can not only open the box, but take the standard out, use it and modify it to create something better. They can build additions and submit them for inclusion and use by the entire industry. The RDOS will not be driven by RMS needs and priorities — it will exist as a separate entity. RMS cannot build every potential solution or model. We hope that by making this an open standard, new synergy is created that will benefit everyone — including us, of course.” Under Scrutiny To create a standard fit for all, RMS accepted that the RDOS could not be built in isolation and pushed out into the market — it had to be tested, the underlying premise reviewed, the format scrutinized. To ensure this, the company set up a steering committee from across the (re)insurance market. Charged with putting the RDOS through its paces, the committee members are given a central role in virtually every development stage.  The committee is currently sixteen companies strong and growing.  It will be dynamic and membership will change over time as issues and company focuses evolve. The membership list can be seen at www.riskdataos.org. “You cannot sit in an ivory tower and decide what might work for the industry as a whole,” Ogaard explains. “You need a robust vetting process and by creating this group of leading (re)insurance practitioners, each committed not simply to the success of the project but to the development of the best possible data solution, the RDOS will be guided by the industry, not just one company.” The role of the committee is twofold. First, it reviewed the existing specification, documentation and tooling to determine if it was ready for market consumption. RDOS saw its industry launch at the end of January 2020, and now the RDOS is published, the committee’s role will be to advise on the priorities and scope of future developments based on market-led requests for change and improvement. “Almost every open standard in any industry is based on a real, working product — not a theoretical construct,” he states. “Because the RDOS was built for a practical purpose and is in real-world use, it is much more likely to hold up to wider use and scrutiny.” So, while the RDOS may be growing its awareness in the wider market, it has already established its data credentials within the RMS model framework. Of course, there remains the fundamental challenge of shifting from one data format to another — but measures are already in place to make this as painless as possible. “The RDOS is essentially a superset of the original EDM and RDM formats,” he explains, “offering an environment in which the new and old standards are interchangeable. So, a company can translate an EDM into an RDOS and vice versa. The open standard tooling will include translators to make this translation. The user will therefore be able to operate both formats simultaneously and, as they recognize the RDOS data benefits, transition to that environment at their own pace. The RDOS could be extended to include other modelers’ data fields as well — so could solve model interoperability issues — if the industry decides to use it this way.” The standard has launched on the global development platform GitHub, which supports open-source standards, offering a series of downloadable assets including the RDOS specification, documentation, tools and data so that companies can create their own implementation and translate to and from old data formats. The potential that it creates is considerable and to a degree only limited by the willingness of users to push boundaries. “Success could come in several forms,” Ogaard concludes. “The RDOS becomes the single universal container for data exchange, creating huge efficiencies. Or it creates a robust ecosystem of developers opening up new opportunities and promoting greater industry choice. Or it supports new products that could not be foreseen today and creates synergies that drive more value — perhaps even outside the traditional market. Ideally, all of these things.”

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