Navigating Challenges in Finance with AI and Automation | GBAF

Navigating Challenges in Finance with AI and Automation | GBAF

Editorial & Advertiser disclosure

Global Banking and Finance Review is an online platform offering news, analysis, and opinion on the latest trends, developments, and innovations in the banking and finance industry worldwide. The platform covers a diverse range of topics, including banking, insurance, investment, wealth management, fintech, and regulatory issues. The website publishes news, press releases, opinion and advertorials on various financial organizations, products and services which are commissioned from various Companies, Organizations, PR agencies, Bloggers etc. These commissioned articles are commercial in nature. This is not to be considered as financial advice and should be considered only for information purposes. It does not reflect the views or opinion of our website and is not to be considered an endorsement or a recommendation. We cannot guarantee the accuracy or applicability of any information provided with respect to your individual or personal circumstances. Please seek Professional advice from a qualified professional before making any financial decisions. We link to various third-party websites, affiliate sales networks, and to our advertising partners websites. When you view or click on certain links available on our articles, our partners may compensate us for displaying the content to you or make a purchase or fill a form. This will not incur any additional charges to you. To make things simpler for you to identity or distinguish advertised or sponsored articles or links, you may consider all articles or links hosted on our site as a commercial article placement. We will not be responsible for any loss you may suffer as a result of any omission or inaccuracy on the website.

Home > Technology > AI-powered visibility key to mitigating IT systems risk in financial services

AI-powered visibility key to mitigating IT systems risk in financial services

Published by linker 5

Posted on March 2, 2021

4 min read

Last updated: January 21, 2026

AI technology enhancing IT systems risk management in financial services - Global Banking & Finance Review — An illustration depicting AI technology streamlining IT systems risk management in financial services, highlighting the importance of automation and cybersecurity in modern banking.

By Penelope Feros, Vice President, APAC, Cherwell Software

The world of finance changes by the minute. Financial businesses — from banks to insurance agencies and brokerages — are facing a myriad of macro challenges that come along with modernisation.

The rise of fintech and challenger banks make the landscape more competitive than ever, putting pressure on the ingenuity of offers, fees, and net interest margins (NIMs). Today’s mostly online banking means an increased need for cybersecurity and protection against data breaches and costly outages.

Automation is no longer a futuristic option for the workplace, but now, a reality that also impacts the customer experience. Disruptive technologies like AI to address the exponential rise in data and complexity in finserv organisations is primed to grow in significance across IT teams in the region.

According to IDC, financial services spending on AI in Asia Pacific will reach US$4.29 billion in 2024, with Australia making significant traction and advancements in AI spending, alongside key financial hub markets Singapore and Hong Kong.

Rising system vulnerabilities within complex IT environments

Digital transformation has resulted in IT infrastructure complexity growing at an astronomical rate. The resultant increases in infrastructure data and alarms at the service desk far exceed the capacity of any human to meaningfully read, analyse and respond to them. The infrastructure itself is also constantly morphing and changing, yet finance service desks are still expected to resolve requests, incidents, and performance issues in seconds – an impossible task, given the volume of data.

Penelope Feros

Penelope Feros

Financial brands are expected to maintain a pristine reputation while making sure all business-critical applications perform optimally, in order to stay competitive and deliver a better service experience.

Every application is supported by a complex fabric of servers, network devices and services – both physical and virtual – local and in the cloud. The impact of an outage or vulnerability for any one of those components can be extreme. IT teams need to monitor not just every device, but also the dependencies between them. Understanding all of the pieces that make an application available is about more than knowing the up or down status.

With security vulnerabilities putting customer data at risk, having awareness of the priority systems that need to be secured is also vital. As the architectures behind applications become even more complicated with the cloud, virtualisation and shared services, manual documentation of dependencies is no longer a feasible option.

AIOps implementation begins with discovery and analysis

The good news is that the solutions available to automatically discover the organisation’s systems and map dependencies are much more sophisticated today.

Discovery and dependency mapping (DDM) tools enable organisations to see how physical, virtual, and logical compute, network, and storage entities are connected. They can handle the complexity of distributed hybrid environments, giving finserv IT teams the opportunity to visualise and manage the components of their online retail, supply chain, ERP and other critical applications.

The discovery phase involves uncovering all of the compute, network and storage entities across the IT environment and ensuring the organisation’s configuration management database (CMDB) is always kept up to date.

DDM tools depict the interdependencies in a graphical format, so IT teams can readily see the connections between assets, and which services they support – critical to troubleshooting incidents or preventing impact of change.

Once the CMDB is kept up to date with automated discovery and dependency mapping, finserv organisations need to make sense of the data in order to make informed decisions. By applying machine learning algorithms to analyse this data, AIOps can identify patterns, spot anomalies and predict (and prevent) future outages. The resulting insights can trigger intelligent automations to effectively prevent outages, improve performance, and ease the burden of managing increasingly complex infrastructure. By automatically triggering actions based on insights, AIOps can quickly fix issues or prevent them from happening, whether it’s a network link that’s gone down, an over-utilised disk or a service that simply requires a restart.

With automatic discovery and dependency mapping, AIOps allow financial services organisations to, gain visibility over IT environments, rapidly evaluate changing needs, and the means to quickly meet them. Adoption of the right solutions leveraging AI can help IT operations in financial services organisations make sense of the growing volumes of data and get on top of increasing risks of outages.