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Boosting Financial Institutions data resilience with AI

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Vusi Melane
Vusi Melane
Staff Writer

Data centers play a vital role for banks and financial institutions by providing dependable and swift connectivity and processing power, thus mitigating the risks of errors or delays in real-time transactions.

For these organizations, the reliability and efficiency of their private data centers are paramount. They frequently opt to own and operate their data centers in-house, primarily due to the sensitive data they store. This is according to Vice President for Anglophone Africa at Schneider Electric, Ben Selier.


“Therefore, the need to ensure critical power backup capabilities for uninterrupted operations is paramount, yet traditional uninterruptible power -apply (UPS) and power backup solutions and approaches often struggle to optimise efficiency and minimise downtime, particularly in distributed branch networks across the country.” he says

“UPS system failure is one of the leading causes of unplanned data centre outages. For banks and financial institutions, this can be catastrophic as they rely on this backup power to prevent critical data loss. UPS failure happens when the system malfunctions or the power outage exceeds the UPS battery’s capacity. Such failures can lead to severe data loss, which has the potential to negatively impact an organisation’s revenue. It is, therefore, crucial to take measures to prevent UPS failures and safeguard against losses that could adversely affect the organisation’s financial performance.” he adds

Reasons for failure

UPS system failures in data centers, often caused by aging infrastructure or efforts to prolong equipment life, result from various factors. Common culprits include batteries, capacitors, fans, filters, connections, and power supplies. Unfortunately, many organizations only uncover the root causes of these failures post-event, risking significant data loss.

AI Intervention

Selier says that this is where AI comes in. “This is where Artificial Intelligence (AI), a transformative force in predictive analytics, can make a significant difference. It can help to make in-house data centre operations more resilient by providing robust backup power systems through AI-driven solutions. These backup solutions can enable branch managers and IT specialists to proactively anticipate and address potential issues before they become major problems.”

“AI can predict changes in power consumption or equipment performance, enabling dynamic resource allocation and significant cost savings. Additionally, AI-driven insights enable IT teams to adjust power and cooling settings in real-time, optimising performance while minimising energy consumption. AI-enabled predictive maintenance can also facilitate proactive intervention to prevent downtime, as real-time monitoring of environmental factors like humidity allows for pre-emptive measures, ensuring uninterrupted operations.” he adds

Reducing risk of unplanned downtime

AI-driven predictive maintenance has transformed data centers by leveraging sophisticated machine learning algorithms to analyze extensive data from sensors, monitoring systems, and past performance. This analysis predicts equipment failures, allowing for proactive maintenance scheduling. This proactive approach minimizes unplanned downtime, ensuring high availability and meeting service-level agreements effectively.

Selier insists on routine maintenance using AI. He says “Proactive maintenance of UPS and power backup systems using AI technology can be more cost-effective in comparison to reacting to outages. It reduces the requirement for expensive emergency repairs and minimises the impact of downtime on revenue. In addition, routine and timely maintenance increases the life span of power backup systems, which translates to fewer replacements and a reduction in capital expenditure. Predictive maintenance helps optimise the utilisation of resources, as repairs and replacements can be planned for times when they have the least impact on operations.”

“Financial institutions can benefit greatly from utilising predictive analytics for power backups and UPS systems. By doing so, they can optimise the performance of their data centres and enhance their resilience against power loss disruptions. With the help of AI, banks and other financial institutions, AI-driven predictive power backup solutions can achieve new levels of efficiency, cost-effectiveness, and operational excellence in managing their data centres. This will ensure that critical financial services run seamlessly without any interruptions.” he concludes

Ben Selier
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