Insights: Financial Modelling – May 2016

We begin this issue with an article that focuses on the exciting new features of RiskAgility Financial Modeller version 2.2. This is then followed by a case study on industrialising assumptions management as part of actuarial processes. We finish with a tutorial exploring the debugging tool in RiskAgility Financial Modeller, including how it can be used in understanding unexpected model results. Read more


Insights: Financial Modelling – December 2015

In our fourth and final edition of Financial modelling Insights for 2015, we begin by introducing our new virtual grid solution vGrid which provides RiskAgility FM users with fast cost efficient on-demand access to secure and scalable cloud-based grid resource. We also introduce DataValidator, a tool that enables insurers to validate, cleanse and transform data, efficiently preparing it for use in financial modelling and reporting and highlight the benefits of this product through a case study featuring Guardian Financial Services. We close this edition with a tutorial on RiskAgility FM Input Manager, a tool which helps manage assumptions when modelling in RiskAgility FM. Read more


Insights: Financial Modelling – September 2015

In this issue, we announce the launch of Unify a powerful new software solution which enables you to integrate your financial modelling and reporting applications into an automated and governed process for greater efficiency and control. In our second article, we present an implementation case study of RiskAgility FM, which gives the insurer greater integration of their financial modelling processes using our leading-edge financial modelling platform.The newsletter continues with articles on Least Squares Monte Carlo, STAR ESG RN, our risk-neutral economic scenario generator and news from the world of financial modelling. Read more


Insights: Financial Modelling – May 2015

We discuss how we implemented RiskAgility FM at Samsung Fire & Marine Insurance in Korea and describe some of the challenges faced by SFMI and how they were overcome using RiskAgility FM’s modelling capabilities. The second article considers implications for liability models in MoSes or RiskAgility FM when adopting a Least Squares Monte Carlo (LSMC) approach to proxy modelling. Our closing article introduces our readers to Star ESG RN, which is an addition to the STAR ESG product suite for the generation of risk-neutral economic scenarios. Read more


Insights: Financial Modelling – December 2014

This month we introduce RiskAgility FM Team edition, showcasing the benefits of the Team edition and how they translate into a real-world environment. Team edition builds on the flexibility available in the Standard edition of RiskAgility FM to provide security and source control to a multi-user model development environment. We also present a case study of a cluster approach to model pointing, based on our experience working with MoSes at Hannover Re. We share some of the differences between this new approach and the classical approach and highlight the reasons why the cluster approach benefited Hannover Re’s processes. Read more


Insights: Financial Modelling – August 2014

We open this issue with an article on the use of predictive modelling in relation to life insurance business. Having developed and refined these techniques over many years in the P&C space, we are now seeing increasing demand for assistance in implementing these techniques with life insurance companies. Continuing the previous edition’s feature on RiskAgility FM (Financial Modelling) we provide tips to help modellers migratie models from MoSes. Our final article outlines some of the new software support services that we are rolling out to clients with a view to becoming ever more efficient in solving any problems that you may encounter with our software suite. Read more


Insights: Financial Modelling – April 2014

We introduce our readers to our financial modelling solution, RiskAgility FM (Financial Modelling), identifying its different features, functions and the benefits of this market leading software. Read more


Insights: Financial Modelling – October 2013

We start this year’s final edition of Insights Financial Modelling with a case study on balance sheet projections. Following on from the previous edition’s case study on model optimisation, we continue with an article which introduces several model optimisation tips developed in-house and applied on a project we undertook for a large European insurer. We describe the various techniques used and the impact they had in reducing the model runtime. Read more


Insights: Financial Modelling – June 2013

We start this issue with a case study on a model optimisation project we undertook for a large Asia client. We describe various techniques used and the impact they had in reducing the model run time. The second article introduces replicated stratified sampling, a novel technique to reduce model run time without compromising the accuracy of results. We round off with a report back from two MoSes Azure roundtables held at the end of March in Paris and Milan and other news from the financial modelling world. Read more


Insights: Financial Modelling – March 2013

In this issue, we begin by looking at MoSes Azure and the potential benefits of using cloud computing without compromising on security. We then discuss a case study that we undertook with Pension Insurance Corporation that implemented a new end-to-end reporting process based around MoSes. The last article outlines how capital models, such as our RiskAgility EC, can be used beyond simply providing point estimates of capital requirements through the use of stress testing and simple projection metrics. Finally, we end with a round-up of news from the world of financial modelling. Read more


Insights: Financial Modelling – January 2013

In this issue, we look at ways of getting the most out of MoSes models using a combination of hardware and techniques. We begin with a case study on variable annuities, which shows how tools, such as MoSes HPC and MoSes Azure can reduce computing times, in combination with other run time reduction techniques. We then move on to a tutorial which looks at the ways to make use of non-rectangluar and ‘structured’ SmartArrays and how they can be used to optimise memory. We end with a round-up of news from the world of financial modelling. Read more