About the Customer
One of the largest holding companies in the middle-east region with several billion in assets under management, its investment portfolio covers a diversified range of industries, ranging from financial services to hospitality.
The challenge
Given the nature of customer’s business, they needed a strong probabilistic solution to manage risk-adjusted modeling and planning to consolidate their large portfolio of assets and investments.
The solution had to be:
- Easily adaptable to each business characteristic and peculiarities
- Compatible with a hierarchical company structure
- A full probabilistic solution easily accessible as a web application
- Powerful in terms of graphical reporting for financial communication
- Best-in-class in quantitative risk analysis
- Field-proven for ERM and Financial modeling
- With a flexible licensing plan to fit the large number of users with different profiles
The solution
Techedge has in its portfolio Riskturn, a solution that allows users to define their financial models and input data and perform simulations based on Montecarlo methods, a broad class of computational algorithms that rely on a repeated random sampling of input data to obtain a distribution of numerical outcomes.
Riskturn was fitting with the majority of customer’s requirements but the original on-premise architecture was not the best one to provide the scalability and cost-effectiveness for this specific use case, with the key need to perform simultaneous simulations on hundreds of different financial cases, reflecting the multi-industry business of our customer.
We decided that the solution needed to be redesigned to leverage the full extent of a cloud-native architecture based on Microsoft Azure with the introduction of the following logical components:
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Web Application: Asp .Net Core web application for data configuration and simulation management. Hosted on an Azure App Service.
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Simulation Engine: Azure Batch application for simulation execution.
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Database: Sql Server database containing the application data and simulation outputs.
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Cache: to boost simulation performance storing intermediate results of each run we selected Azure Radis Cache.
This technological upgrade allowed to provide the customer with a fully satisfactory solution, because:
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The introduction of Azure Batch for high-performance computing brings in several advantages in probabilistic simulation performance, thanks to pools of dedicated resources for calculation, automatic horizontal scaling and out-of-the queue system for concurrent executions.
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With the help of Azure Redis Cache, each simulation output is stored in memory, quick access and temporary storage support the execution of full-scale Montecarlo methods.
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Azure App service is cheaper than a virtual machine and Azure Batch can provide better performance at a fraction of the cost, with an extremely positive impact on ROI.
How the solution helps
Moving to Azure avoided the management and maintenance of on-premise servers, saving time and furtherly reducing costs by delegating these activities directly to Microsoft services.
In this specific use case, the running costs for the infrastructure were decreased by 1/3, thanks to the pay-as-you-go pricing model of Microsoft Azure and a proper choice of the involved services.
Moreover, the use of cloud-native services highly increased the application performance and stability: the time to perform tens of thousands of cycles of Montecarlo simulation decreased from 10 to 2 minutes for each run, enabling the customer to easily manage all the company assets and perform quantitative analysis even for the whole portfolio in a reasonable amount of time, increasing analytical capabilities and providing a better decision making support to business users.