AI can unlock $1tn a year in value for banks, McKinsey says

Rapid data analysis can also help lenders to make quicker decisions on credit applications

Traditional banks are under pressure to improve customer engagement amid a growing threat posed by digital-only lenders and technology companies looking to move into financial services. Getty
Traditional banks are under pressure to improve customer engagement amid a growing threat posed by digital-only lenders and technology companies looking to move into financial services. Getty

The adoption of artificial intelligence technology could potentially deliver up to $1 trillion in additional value each year for banks, according to global consultancy McKinsey.

AI technology is expected to boost revenue through the increased personalisation of customer services and lower costs due to the efficiency gains of higher automation, fewer errors and better resource use.

Lenders could also uncover new opportunities based on an improved ability to generate insights from vast troves of data, the consultancy’s Building the AI bank of the future report said.

“As customers conduct a growing share of their daily transactions through digital channels, they are becoming accustomed to the ease, speed and personalised service offered by digitally native [companies], and their expectations of banks are rising,” said senior partner Renny Thomas.

“To compete and thrive in this challenging environment, traditional banks will need to build a new value proposition founded upon leading-edge AI and analytics capabilities. They must become AI-first in their strategy and operations.”

There has been an improvement in operating conditions for lenders as businesses stabilise and economies around the world recover from the coronavirus-induced slowdown.

The International Monetary Fund last month upgraded its global economic growth forecast for this year to 6 per cent. The world economy shrunk by 3.3 per cent last year.

Many banks have struggled to scale up their adoption of AI technology because they lack a clear strategy and have fragmented data assets, an inflexible and investment-starved technology core or outmoded operating models, the report said.

To compete and thrive in this challenging environment, traditional banks will need to build a new value proposition founded upon leading-edge AI and analytics capabilities

Renny Thomas, senior partner at McKinsey

“Incumbent banks must become AI-first institutions,” said McKinsey, particularly as they face a growing threat from big technology companies looking to move into financial services.

Other challenges include greater competition from neo-banks, increased customer expectations and digital ecosystems looking to disrupt traditional financial services, according to the report.

However, the use of advanced AI technology by leading financial institutions is steadily increasing. About six in 10 respondents to McKinsey’s Global AI Survey report on financial services said their companies had embedded at least one AI capability.

“To craft and deliver intelligent propositions, banks need to free themselves from a product-centric view and instead adopt a customer-centric view, which starts with understanding customer needs,” the report said.

Lenders are already using AI for split-second loan approvals, biometric authentication and to power online assistants, helping to improve customer interaction and reduce costs.

Banks can also use AI to offer services such as fee-reduction recommendations, which are based on analysis of past transactions, and budgeting and planning tools than can help customers achieve their financial goals.

“Rapid analysis of transaction history enables banks to inform individual customers about their potential to reduce fees. Budgeting tools can help customers to improve financial discipline,” the report said.

“By integrating systems across the enterprise, banks can analyse relevant data to generate a comprehensive view of a customer’s total inflows and outflows and offer advice for balancing daily and annual spending with wealth-building goals.”

Lenders are also increasingly relying on AI and analytics capabilities to drive customer acquisition, make credit decisions and improve monitoring and debt collection.

The use of advanced analytics allows banks to deliver highly personalised offers directly on a landing page for new customers.

They can also better understand client needs by analysing their browsing history, how they arrive at a website and making use of their social media data to form an initial profile that includes a customer’s financial position and provisional credit scoring, McKinsey said.

AI-first banks can streamline lending processes by using the technology and “near-real-time analysis of customer data to generate prompt credit decisions for retailers, small and medium-sized enterprises and corporate clients”, it said.

Such banks can also qualify new customers for credit services, determine loan limits and pricing and reduce the risk of fraud, the report said.

By automating as much of the lending procedure as possible, banks can strengthen each customer’s experience through quick loan approvals and fund disbursements, fewer document requests and credit offers tailored to their needs, McKinsey said.

Updated: May 25, 2021 02:08 PM

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