What is Financial Modelling?

Financial modelling involves the use of High Performance and High Throughput Computing clusters, working in parallel, to predict possible future outcomes typically using Monte Carlo techniques. Example applications include credit modelling, risk modelling and predictive analytics.

Typical on-premises technology:

• Bespoke clusters
• Tibco
• Symphony
• Hadoop/ Spark

Typical on-premises challenges:

• Long execution times
• Capex and capacity planning
• High total cost of ownership (TCO)
• Maintenance burden
• Low agility and innovation

Why now?

The growth in compute capacity and services on AWS means that financial modelling workloads, traditionally running on on-premises grids, can now run more effectively and at a lower cost on the cloud.

Who is it for?

Financial services industry customers such as:

• Insurance
• Banking
• Investments
• Capital Markets
• Wealth Management

How it works:

1. Discovery: The lab begins with an initial discovery workshop, which typically takes one day. Following the workshop, we assess the suitability of the proposed workload and determine the scope of work, technical architecture, data security requirements and Key Performance Indicators. In total, this phase takes approximately one week.
2. Evaluation: During this phase, we migrate and modernize key elements of the workload, ensuring that the required KPIs, cost and scalability metrics are measured. This process typically takes between 6 to 12 weeks depending on the nature of the workload and is iterative and transparent.
3. Analysis: Finally, we produce an analysis report that details the results of the lab, measured KPIs and a go-forward plan to move the workload fully to production.
4. Post-Lab Engagement: We provide full support for the build and scale-out to production. A dedicated team is assigned full-time for the lab's duration.

Benefits:

• Reduced Code and Infrastructure: Fewer bugs, less maintenance, and reduced TCO.
• Compliance: Simplify security and regulatory compliance by leveraging the AWS Shared Responsibility Model.
• Future-Proof Technology: The technology evolves with your needs, making obsolescence a thing of the past.
• Sustainability: Reduce your carbon footprint by moving from always-on grids to compute-on-demand.