Ben Selier, Vice President, Secure Power, Anglophone Africa at Schneider Electric.

Data centres play a crucial role for banks and financial institutions as they offer reliable and fast connectivity and processing power, reducing the risk of errors or delays in real-time transactions.

For these organisations, the reliability and efficiency of their private data centres are paramount, as they often own and operate their data centres in-house, largely due to the sensitive data that they store.

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

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.

Reasons for failure

There are several reasons why UPS systems and other power backup solutions can fail, especially when a data centre is operating an ageing infrastructure or trying to optimise the lifespan of newer equipment. The most common UPS components that are susceptible to failure are batteries, capacitors, fans, filters, connections and power supplies. Unfortunately, many organisations only find out why their power backups have failed after the event and resultant data loss.

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.

Reducing risk of unplanned downtime

Predictive maintenance, powered by AI, has revolutionised the data centre industry. It utilises advanced machine learning algorithms to analyse massive amounts of data obtained from sensors, monitoring systems, and historical performance records. This data is then used to predict when equipment is likely to fail, allowing maintenance to be scheduled proactively. This significantly reduces the risk of unplanned downtime, which can be costly and disruptive, and is critical for maintaining high availability and meeting service-level agreements.

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.