Predictive Analytics as a platform for maintenance services
Predictive analytics can also help drive efficiency enabling predictive maintenance operations. By leveraging on real-time condition monitoring and predictive maintenance to maintain equipment, organisations can avoid costly corrective or preventative maintenance. This approach can be described as the first line of defence against unplanned downtime, which not only results in ensuring higher service quality, but also direct cost savings.
Customers expect banks to operate 24/7, so the downtime of a bank's infrastructure needs to be minimised. A legacy IT infrastructure can result in disadvantages for a financial services provider in terms of reduced productivity, customer satisfaction, and regulatory scrutiny on maintenance costs, and downtime.
The ATM is a good example of a significant tool of a bank's infrastructure. According to a study by Accenture, the ATM channel still retains its central role as a core banking touchpoint with the consumer despite the shift towards internet and mobile banking. By leveraging the benefits of predictive analytics, banks can ensure that consumers remain satisfied with a higher quality of service and reliability rendered as banks can predict equipment failures and dispatch maintenance services as and when needed.
The future of analytics
Data analytics is redefining itself. Businesses should also take note of the proliferation of advanced analytics and data science, which allows for more streamlined movement of data across business functions and the emergence of machine-learning algorithms.
Banks will be able to process data faster and cheaper, significantly improve projection capabilities and imbue their analytics ecosystem with flexibility and reliability. However, the starting point remains access to big and potentially streaming data. Banks that treat the potential of advanced analytics as an afterthought will themselves become an afterthought in the minds of their competitors and consumers.
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