Insights ESG and Solvency II in the Cloud In this article we look at how the model of cloud computing can be applied to high performance computing (HPC) applications. In particular it looks at economic scenario generators with specific reference to Microsoft s Azure Cloud and outlines how this can help with Solvency II reporting. Matt Little Matt.Little@barrhibb.com Cloud computing why should I be interested? What is cloud computing? Cloud computing is a term used to describe a model of temporary access to computer resources. These resources can include access to computational power ( machines ), databases or other Software as a Service (SaaS). Typically charged for as access to a machine ; in reality the physical location, type, size and configuration of the machine will not be known....the optimal solution would be to host both the ESG and your ALM software on the cloud and get the systems to communicate and exchange data on the cloud. Companies offering cloud computing such as Microsoft, Amazon and Rackspace, provide organisations with access to an amount of computational resource, and although the provision of this access looks, to all intents and purposes, like a small computer or other service; in reality it is likely to be a slice of a large server (or slices of several servers) located at one, or more, global data centres operated by the cloud provider. Where that bigger machine is located is entirely at the discretion of your cloud supplier. Why is cloud computing attractive? The cost of maintaining physical servers is expensive costs for electricity, cooling, maintenance and monitoring are all being scrutinised and challenged; even more so when the full computing capacity of many in-house machines is only ever required at quarter or year ends. Many insurers are for that reason coming round to thinking about combining a permanent on-site capacity for their base loads with a flexible amount of cloud capacity for peak loads. In doing so, the hope is to maintain (and possibly improve) quality of service whilst reducing the operating overhead. Potential shortcomings of the cloud Data Throughput The time taken to upload or download large amounts of data can be prohibitive. For ESGs, assuming that scenario sets can be 1GB+, download times for scenario data from the cloud could be between 3 and 16 hours depending upon network speeds (assuming a 10GB data set with 50% network utilisation and network speeds of between 2 and 10 Mbps). The most effective approach to reduce this time is to minimise the volume and number of data uploads keep data on the cloud for as long as possible and only download the data that is essential. Additionally, data transfers between your own site and cloud resources should be kept to a minimum. Rather than move data onto the cloud for scenario generation and then off the cloud for asset and liability valuation, the optimal solution would be to host both the ESG and your ALM software on the cloud and get the systems to communicate and exchange data on the cloud, negating the need to transfer data off the cloud. As cloud data storage costs are low and the hardware highly resilient, this approach should not dramatically increase data storage costs or negatively affect availability of data.
Can you be sure that the same level of scrutiny has been applied to your internal storage? Security Probably the biggest perceived concern surrounding cloud computing is that data might be at greater risk on the cloud than would be the case if held internally. All the major cloud vendors have worked very hard to ensure that their platforms are secure and many man-hours of work have been expended ensuring that the storage and encrypted data upload and download systems are also highly secure. Can you be sure that the same level of scrutiny has been applied to your internal storage and communication systems by global experts in the data security field? Regardless of where you chose to hold your data, a rigorous review of security is an absolute requirement and you need to assess whether the security provided by any given cloud provider is sufficient. It is also sensible to scrutinise your data to assess whether it contains personal data, sensitive information, your intellectual property, or is affected by corporate confidentiality. Furthermore, when choosing a cloud provider, you should consider the following points: How sensitive is the data that you are hosting on the cloud? How will your data be segregated from that of other cloud providers? What provisions are made to provide physical security to the data centres hosting cloud resources? What level of access control is enforced? Do you have a requirement that data be hosted in a specific region rather than anywhere in the world? How many global data centres does your cloud provider have? Can they provide true global resilience to the failure of a data centre? What level of logging and audit does your cloud provider offer? What access does the cloud provider s staff have to your data? What is the long-term viability of your cloud provider? What level of encryption (data security) does your cloud provider offer? How do I access a cloud from a single application? Vendors provide rich and easy- to-use management consoles which allow you to access resources on their cloud. These allow you to set up the number and capacity of your cloud resources which can then be used by an application or service that interfaces with your cloud resources. Using Microsoft s Windows HPC Server 2008 R2 as an example, it is possible to have a single management console through which you can configure and manage local cluster machines and cloud machines. By defining job types, it is also possible to manage whether specific job types run on local machines only, cloud machines only or some combination of the two. In combining these approaches, it is possible to run jobs on local hardware until they reach a certain capacity and then burst out to the cloud for temporary additional capacity. If and when the time comes to migrate the entire application s processing requirements to the cloud, this is then a trivial exercise. What are the costs of cloud? Costs for access to cloud resources vary both by vendor and the scale of resources required. Several factors should be considered when costing cloud services: The size (power) of a cloud instance (machine) The data storage requirements The amount of data to be uploaded or downloaded to the cloud Again taking the Microsoft Azure cloud as an example, latest costs can be obtained here: http://www.microsoft.com/windowsazure/pricing/
Recommended cloud configuration For economic scenario generation, a typical cloud deployment would be approximately 20-30 large compute instances. Azure currently offers no-cost data upload and charges for download of data by the Gigabyte. In this example as you transfer data off the cloud after each scenario, you do not need to store data on the cloud and therefore there are no on-cloud data storage costs. Assuming that we use 25 compute instances, perform a scenario generation that takes one hour to run and generates scenario data of 1GB, the following costs will apply: Compute costs: $12 Data transfer costs: $0.15 Data storage costs: $0 Total cost for a scenario set generation: $12.15 At the end of the scenario generation, the cloud resources are switched off and there are no ongoing costs. It is apparent that the cost of running large-scale scenario generation on the cloud is both feasible and very cost effective especially when compared to the costs involved in maintaining your own cluster of machines, including: Electricity Air conditioning/cooling Physical security and surveillance Hardware depreciation and replacement cycles Managing and applying patching and system updates Maintaining redundant capacity for infrequent periods of peak demand Where are we going with the cloud? What solutions can it provide? The generation of economic scenarios is only a part of the Solvency II process. To recap, the guiding principle is to keep data transfers to a minimum in order to reduce costs and, more importantly, the time taken to transfer data onto and off the cloud. Additionally, the easiest way to successfully manage that is to co-locate applications on the cloud thereby maximising oncloud transfers whilst minimising off-cloud transfers. This approach can be applied to Solvency II reporting in the manner outlined on the next page:
Using the ESG to store scenario set data in on-cloud storage and provide an interface for ALM systems to access scenario data provides the capability to keep all scenario and ALM data on the cloud until the time comes to download only the asset liability value data thus minimising data transfer off-cloud. Cloud-based scenario generator Scenario Data available to ALM software directly on the cloud through Barrie & Hibbert cloud interface Asset Liability Modelling Software The cost of such a scenario generator in the cloud is as the example above, but with the additional costs of data storage. This example requires that scenario data be stored on the cloud for access by the ALM system; if we assume that scenario output is approximately 1GB in size, the total cost for a cloud ESG install would be: Compute costs: $12 Data transfer costs: $0.15 Data storage costs: $0.15 Total cost for a scenario set generation: $12.30 Summary Undoubtedly cloud computing will have real appeal for many insurers who wish to compliment an in-house scenario generation capability in a flexible and cost-effective manner. It can provide significant benefits to those using large amounts of computational power especially if that use is highly resource-intensive, cyclical and tends to peak for short periods at predictable times exactly the type of demands placed on you by Solvency II reporting. Building a Solvency II platform on the cloud is a realistic and cost-effective option, especially when scenario generation and Asset Liability Modelling are both performed on a cloud. Barrie and Hibbert s technology research team is currently prototyping cloud-based scenario generation and we are working with ALM providers to build a Solvency II platform on the cloud.
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