Enterprise Risk Management Technology Guide 2023/24

RNA Analytics - R³S Software Suite

Type of System

  • Analytics
  • Asset/liability management
  • Capital modelling
  • Economic / risk scenario generator
  • End-to-end ERM
  • IFRS 17 solution
  • Internal/external reporting
  • LDTI solution
  • Portfolio analysis/hedging
  • Reserving solution
  • Solvency II solution
  • Stress and scenario testing
  • Stress testing

Type of platform

  • Cloud
  • Desktop-based
  • Grid
  • Server-based
  • Web-based

Other features - does your offering facilitate

  • Curve-fitting
  • IFRS 17
  • LDTI
  • Least-squares Monte Carlo
  • NAIC Principle-based reserving
  • Solvency II internal model
  • Solvency II standard formula

What are the typical implementation costs?

The size of the investment depends on the size of the product portfolio, the complexity of the company structure and the type of models to be reproduced in the new tool, but also on the overall company infrastructure upon implementation.

The key element is to plan adequately the project, considering external impacts to ensure the different milestones are delivered under the agreed timeframe and budget, and answering the company’s business case.

Depending on the type of project, returns and cost saving would be measured based on different dimensions like time, flexibility, and robustness. Flexibility and transparency of the tool allow the end user to learn and work faster resulting in cost savings. A robust end-to-end process will allow future projects to be implemented more rapidly using the same IT infrastructure thus saving costs in the future.

How long does your software take to implement on site?

The duration of an implementation will depend on the size of the portfolio, the scope of project and the degree to which the client is involved. A medium-sized insurer, for example, looking for a fairly straight-forward implementation carried out by dedicated actuarial and technical consultants alone, may take up to six months.

In this time, teams will work to develop a full cash flow model, some stochastic modelling and decision management rules. In that standard implementation, users then need to be trained so they understand the full range of functionalities, so they are confident in using the tool and understand how to carry out testing and reporting.

No-one is going to be an expert after just a couple of months, so this needs to be considered part of the overall implementation. Over time, however, we typically find that clients become fully proficient with the tool and able to carry out all of their maintenance and future coding developments.

Most recent significant update:

RNA Analytics has recently released R³S version 4.0, focusing on improving performance and functionality of the software suite. The enhancements in this release, which build on the software’s existing strengths, are based on market requirements, client feedback and input from our R³S users worldwide.

The major enhancement in this release is the completion of a new distribution mechanism that allows the majority of production models to be executed across multiple machines rather than being executed by a single machine. This avoids manually splitting models, where possible, to allow them to run in parallel on multiple machines. Also, by utilising multiple machines this provides access to significantly more memory than on a single machine allowing larger models to be run.

Other enhancements include, enhancements to Azure Batch distribution, code check-in approvals. New system functions have been added and existing system functions enhanced to enable more array-based operations, including on array indices.

As well as the R³S software, there has been enhancements to the R³S model packages, including, but not limited to, our expansion into the non-life segment with new R³S Non-life Standard Code, the development of our unique IFRS 17 end-to-end offering, and LDTI for US customers.

Planned future enhancements:

The recent releases will be followed by additional new features, enhancements, and tools throughout 2023/4. We are also responding to the demands of smaller insurers that do not have an established actuarial modelling department. Such companies are often using Excel calculations, which they are finding increasingly ill-suited to the highly complex processes and calculations required under new regulations.

We will continue to release additional enhancements and new features to the R³S software suite in order to meet our clients’ constantly evolving requirements. With enhancements around reporting, and Azure Batch, plus new features around profiling, and execution on Linux.

How does your solution integrate with third-party systems or in-house systems?

With the R³S Toolkit, organisations can integrate the running of R³S models in an existing infrastructure allowing full automation. It allows the seamless integration of the modelling within existing governance infrastructure, so clients do not need to purchase a specific workflow engine or change existing processes. 

One of R³S strengths is its flexibility to integrate directly with input in multiple formats. This is achieved by the use of common standards to connect to third party databases, removing the need for pre-processing or specific formatting of inputs. R³S output can also be written directly into third party databases, this removes the need for manual or slow additional integration process steps which reduces operational risks and improves efficiency.

What is the key attribute of your product(s) that differentiates it from your competitors?

The R³S Modeler tool offers enormous flexibility with an open, and visual architecture rather than operating as a black box. The system’s modular approach has the overriding concept of only needing to code something once, then the ability to drag-and-drop that component to reuse it in other parts of the model. 

This provides a very efficient and linear glide-path for model development from creating a single cash flow liability model, to a dual basis EV type calculation, to ALM modelling and then to stochastic or even nested stochastic modelling.  At each stage of this process users only need to code the extra complexities involved and simply reuse all the other areas previously created.

This model development approach, together with the constantly evolving system architecture to make effective use of the latest hardware and computing availabilities, with little or no changes by the customer, makes R³S Modeler a very efficient tool capable of modelling and projecting the most complex products and dynamic ALM decision rules.

As well as providing model packages for regulatory needs such as Solvency II and IFRS 17, the standard code library has been expanded to cover non-life modelling. Allowing companies to have a single tool for all life and non-life requirements, accelerates any implementation project.

What trends are you seeing in terms of customer demand?

The pace of change we have seen in the last decade is not abating, and forward-looking insurers are turning to technology to keep them multiple steps ahead. However, to do that, insurers must first recognise the major force of technological change - which pervades all other trends.

With investment in advanced actuarial analytics expected to continue to grow, insurers can expect to be able to offer more tailored recommendations, enjoy a constantly improving understanding of customer behavior, gain greater market knowledge, and therefore improved profit through better managed portfolios.


The R³S Software Suite simplifies the complexity of actuarial, regulatory and risk-based requirements.


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