Driven by rapid innovation in the tech sector, financial services have embraced cloud computing, aiming to redeploy this towards their specific needs. It affords them greater flexibility, resiliency and computing power than an inhouse infrastructure would allow for.
Cloud computing allows for financial institutions to secure computing power, on demand, allowing them to optimise their spending based on their changing needs. This allows for cost-savings compared to maintaining servers inhouse –- a feature that is especially relevant for rapidly growing firms. This allows companies to be far more scalable and responsive to growth than with traditional IT infrastructure.
Financial services firms tend to have an extremely segmented business, especially with larger institutions offering multiple services under one brand – such as divisions between retail banking, investment banking, wealth management, etc. This often means that the firm’s data also remains segmented and distinct, preventing its central collection and its use as an asset for the firm. A centralised repository of data also presents opportunities in analytics, whereby machine learning techniques can identify trends and patterns in the firm’s business; this can be used to identify opportunities for growth and risks to continued performance.
Beyond this, cloud computing gives financial institutions access to more computing power than before and at a lower cost. This is especially pertinent in areas such as fraud prevention, which requires the analysis of vast quantities of transaction data and existing due diligence.
The ever-growing regulatory environment and need for rapid analytics is also increasing demand from financial institutions for computing power. On the risk management side, internal calculations for stress testing, capital requirements and VaR often rely on Monte Carlo simulations, whereby repeated random sampling allows for an estimation of the distribution of future PnL; this places a significant computational burden on banks due to requirements necessitating their daily calculation. The growth in the use of various valuation adjustment to derivatives trading, such as CVA, is case in point of this computing need. These simulations estimate the future path of derivative positions, at multiple time intervals, with the aim of computing the expected exposure at any given time.
Migration to cloud computing enables these tasks to be performed far quicker and at a lower cost. Furthermore, banks will not have to continue adjusting their IT infrastructure as the regulatory landscape evolves, providing greater certainty over their future spending on computing.