Bank IT capacity planning is becoming increasingly important as financial institutions manage more complex technology environments and growing customer expectations for reliable services. System outages and performance failures can create significant operational costs while further damaging customer confidence in banks already facing reputational challenges.
Traditional approaches that simply add infrastructure when problems arise may provide short-term relief but do little to anticipate future demands. Predictive analytics can give banks greater visibility into capacity requirements, allowing potential bottlenecks and performance issues to be addressed before they disrupt customer services.
The global financial crisis devastated the reputation of the UK banking industry and it is not hard to understand why public trust in banks is at a low ebb. Since 2008, there have been at least five major scandals involving one or more banks operating in the UK, writes Peter Duffy
Along with the reputational damage and massive fines imposed by regulators to fall out of the financial crisis, the banks also face huge reputational and financial costs as a result of their IT failures.
To restore trust, UK banks need to demonstrate to the Financial Conduct Authority and their customers that they are paying more care, ensuring robust risk and service management practices and assuring end user performance. Having a strong capacity planning capability is key to this.
There are a wider range of platforms to be considered by banks when it comes to capacity planning, compared to companies in other sectors, where environments are typically more standardized with a smaller set of platforms.
In such complex operating environments, where demand for different services can be volatile and high levels of change are a way of life, maintaining an accurate handle on capacity headroom and potential issues is a real challenge.
If a disk fills up on a database server and can no longer process transactions, the repercussions can be substantial. The common reaction is to throw money at the issue, adding resources, and turning to things like additional storage and virtualization to solve the problem.
This can offer a quick fix, but using new technologies like predictive capacity analytics can help banks make smarter decisions, and address any potential IT issues well before they impact service performance and customer perception.
Analytics Help Banks Anticipate IT Performance Issues
With today’s banking customers demanding a wider variety of products and services, financial institutions must find ways to manage the added complexity in their operational requirements and IT environments. This is one of the reasons why many FIs are looking toward improved data management, integration, and the use of analytics to better understand and customer service needs, and forecast and address possible system bottlenecks and performance issues before they become a problem.
As financial institutions expand their products, channels, and digital services, managing the underlying technology infrastructure becomes increasingly complicated. Effective bank IT capacity planning can help institutions understand how systems are being used, anticipate changing requirements, and identify potential performance problems before customers are affected.
Combining improved data management and system integration with predictive capacity analytics can also help banks make more informed technology investments rather than continually adding resources in response to problems. For institutions seeking to improve reliability and rebuild customer trust, proactively managing IT capacity and service performance can become an important part of delivering a more dependable banking experience.
Overview by Ed O’Brien, Director, Banking Channels Advisory Service at Mercator Advisory Group
