Tag Archives: actuarial modeling

New modeling and allocation capabilities in Milliman’s Arius solutions provide richer analysis and reporting

Milliman announced today that it has released version 2020b of its Arius® solutions, a family of state-of-the-art reserve analysis systems for property and casualty insurers. This update provides significant enhancements to the systems’ analytical capabilities, together with key additions to the reporting and data management tools.

This release adds new generalized linear modeling (GLM) capabilities to help actuaries better model and understand their claim costs. GLM tools can be especially valuable when analyzing periods of inflationary pressure on the claim process or significant changes in claim handling within a company or throughout the industry.

In addition, the new release of Arius Enterprise®—Milliman’s reserving solution designed specifically for larger insurers and self-insureds—helps actuaries analyze results at one level of detail and then report on them at different levels. The system’s new allocation tools more reliably and efficiently perform the summary and reporting work that is typically accomplished using riskier spreadsheets.

Our Arius solutions are specifically designed to help our clients better understand and account for the complexities in their business. This release provides a number of new tools to help actuaries with sophisticated calculations, as well as data and report management, so they can focus on the areas where their substantial expertise can provide the most value to their organizations.

Modeling the future of COVID-19

There is still much uncertainty about the current COVID-19 outbreak. Modelers are trying to anticipate the future of this pandemic based on relevant parameters driving its evolution. To this aim, the current scientific literature is a core source of information. However, in a context of exponentially increasing numbers of publications, an exhaustive manual analysis remains out of reach.

In this paper, Milliman consultants illustrate the potential and the challenges of using Bidirectional Encoder Representations from Transformers (BERT), a Natural Language Processing (NLP) framework, to automate the task of gathering input information and assisting experts for COVID-19 studies.

Interpreting actual models for enhanced results

Insurers use models to predict the future, whether it is for future reported claims, ultimate claim costs or policy sales. Businesses are sometimes reluctant to move to more sophisticated models because models can be difficult to interpret and trust.

Predictions from models are not always intuitive. Validation exercises can be undertaken to prove that they are reliable, but additional work is needed to ensure that they are doing what is expected of them.

There have been some public examples where models have not performed as expected. Gender bias or racial bias, for example, can occur unintentionally where input data is not representative. Changes in data collection over time can also invalidate results. Unlike human beings, a well-coded and well-explained algorithm may be able to clearly display its own biases.

Model interpretation is understanding how models work and why they are accurate. If a model is interpretable, the predictions from that model should be intuitive to the modeller. Model validation and interpretation are key and distinct steps in the data science workflow and are essential before deployment.

In this briefing note, Milliman’s Eoin O’Baoighill and Eamonn Phelan discuss key steps in model interpretation, requirements from model interpreters and model validation methods.

Chief modeling officers provide value in a new actuarial modeling world

Understanding the business versus the operational skills and activities related to modeling holds the key to the new actuarial operating model. When these differences are recognized and each function is empowered to focus on what it does best, the resulting sum of the two parallel functions is greater than the original comingled model. Milliman consultant Van Beach provides more perspective in The Actuary article “Undeniable Synergy: A case for the chief modeling officer.”

Cloud computing reading list

Cloud-based computing systems provide insurance companies several advantages over traditional systems. The following reading list highlights the benefits that cloud computing solutions such as Milliman’s Integrate offer insurers.

• Milliman Integrate™
This video showcases how Integrate is reinventing the way the world’s life insurers model risk.

• Reuters: Amazon’s cloud business a harder sell in post-Snowden era
This article discusses the pros and cons of public, private, and hybrid cloud models.

• Rewrite.ca.com (Wired): The biggest risk facing insurers today? Old-guard IT
Some insurance companies have moved their actuarial modeling systems into the cloud. This article highlights how UK-based insurance firm The Phoenix Group increased productivity by implementing Integrate. In the article, Milliman principal Pat Renzi discusses the value that cloud-based actuarial modeling can have for insurance companies.

• TechTarget.com: What to consider before running HPC in the cloud
Information technology (IT) administrators should follow best practices when running high-performance computing in the cloud. Milliman’s Paul Maher and other IT professionals offer eight tips that can help administrators manage testing, networking performance, and more in this article.

• Contingencies: Fast forward: Emerging technology and actuarial practice
Cloud-based solutions such as Integrate are transforming the actuarial profession, offering clients the speed and scalability needed to process advanced analyses in real time. Pat Renzi discusses the advantages of conducting complex calculations using an actuarial modeling system in the cloud.

• The Digital Insurer: Actuarial models meet the cloud: A perfect marriage?
The costs associated with actuarial modeling have increased. This article, authored by Milliman consultant Dennis Stanley, demonstrates how migrating an actuarial model to the cloud is cost-effective and increases flexibility for large-scale, time-intensive projects.

• MG-ALFA® Compute for Windows Azure
This video shows how MG-ALFA Compute for Azure can help insurers meet their growing needs for high-capacity computing as the industry’s modeling requirements expand. This solution reduces run-times, increases capacity for analyses, and lowers costs relative to an in-house grid.