Banking is a fast evolving, dynamic sector that tries to use the latest technology available to achieve growth and success. And with the growth of AI machine learning tech, all the major banks are not only familiarising their operations with it, but already actively refining and optimising their processes for machine learning.
This is not surprising when you consider the banking and finance industries are one of the biggest adopters of machine learning, with Precedence Research forecasting the sector to reach $12,337.87 million by 2032. McKinsey, meanwhile estimates throughout the cross-section of Banking, Wholesale, and Retail, generative AI could add between $200 billion and $340 billion in value for businesses across the globe.
The rewards are already being felt, with all three of the leading companies in the financial rankings of the most recent Customer Effort Index all adopting machine learning in one form or another.
Take Chase Bank, number one in the US rankings, for example. The company is investing $12 billion per year in technology, which then aids a team of more than 50,000 technologists. A key example is Chase using machine learning to personalise the digital experience of its research platform, J.P. Morgan Markets.
Meanwhile, over in Australia, Bendigo Bank recently celebrated a 20% improvement rate in its customer service efficiency and the uplift of key performance, productivity and service standard metrics. This all came one year after migrating its contact centre operations to the cloud and included a 90% reduction in call waiting time complaints, which was reflected in its position in first place in the Customer Effort Index rankings.
Over in the UK, Nationwide, the leader in its country’s rankings, is working with London-based AI machine learning provider Jumio to streamline the digital onboarding process for new members. Nationwide claims that Jumio’s software is using a proprietary mix of AI, machine learning, and other advanced technologies to determine if an identity document is authentic and belongs to the user.
These three banks are each benefitting from machine leaning not just from a financial perspective, but from a customer retention point of view as well. By using AI for customer service, fraud detection solutions, onboarding, process automation tools for risk management, and regulatory compliance, banks across the world are harnessing the power of machine learning and the ones that have yet to adopt it are falling behind.
