Artificial intelligence (AI) is rapidly changing the way financial services institutions attract and retain their customers, and will need new models of collaboration among competitors, according to a new report by the World Economic Forum and Deloitte.
The report, The New Physics of Financial Services, explores how AI will transform financial institutions by radically changing front- and back-office operations, creating major shifts in the structure and regulation of financial markets, and raising critical challenges for society to resolve.
The report also notes that investment in talent is a critical enabler of AI.
“AI is giving rise to a new discipline on how financial institutions plan for their future talent and technology needs.”
The report says talent transformation will be the most challenging road block on institutions’ implementation of AI.
It will put at risk the competitive positioning of firms and regions that fail to effectively transition talent alongside technology, it points out.
“While AI is often seen as a substitute for human talent, establishing a workforce that views the implementation of AI as an opportunity will be critical for anything but the most marginal business transformations. Achieving this will require an honest and collaborative relationship between an institution’s workforce and leadership.”
The report lists some questions that need to be answered around preparing the workforce for the AI-enabled environment.
What are specific talent profiles that financial services will need to evolve and perform within new business models?
How can institutions balance the domain expertise they need today with the quintessentially human capabilities they will need over the longer term?
How can finance institutions accelerate transformations when training, learning and adapting takes place at human speed?
What should the role of government be during this period of uncertainty and as new talent economies unfold?
The report, meanwhile, lists four core areas where AI is radically transforming the front- and back-office operations of financial institutions:
Cost centres to profit centres: AI enabled back-office functions will allow financial institutions to turn their centres of excellence into services, while pushing them to outsource most other capabilities. As financial institutions move towards a back-office as-a-service model, these processes will continuously learn and improve using data from its collective users. This both accelerates the rate at which capabilities improve while necessitating competitors to become consumers of that capability to avoid falling behind.
A new battlefield for customer loyalty: Past methods of differentiation for financial institutions—such as cost, speed and access—are eroding. AI is giving rise to a new set of competitive factors on which financial institutions can distinguish themselves to customers.
For example, the ability of institutions to optimise financial outcomes by tailoring, recommending and advising customers will allow them to compete on value offered. The ability to engage users and access data through ongoing and integrated interactions beyond financial services will allow them to better retain customers. And curating ecosystems by bringing together data from multi-dimensional networks that include consumers, corporate clients and third parties will allow financial institutions to offer differentiated advice and improve performance.
Self-driving finance: Financial advice, part of every product, is often generic and impersonal. It also tends to be overly reliant on subjective advice from different customer service agents. A self-driving vision of finance could transform the delivery of financial advice, centreing customer experiences around AI. In this vision, individuals will increasingly interact primarily with a single platform or agent who will provide recommendations about the types of products they should engage with and advisory services around those products.
AI enables this vision in three key ways: empowered platforms which can compare and switch between products and providers; increasingly personalised advice based on data; and continuous optimisation through algorithms which will automate most routine customer decisions.
Collective solutions for shared problems: While AI presents increased opportunities for competition, it also presents a strong mechanism to collaborate as the value of shared datasets is tremendous. There is great potential for cross-institutional collaboration on issues such as fraud prevention and anti-money laundering controls, which are often run inefficiently and ineffectively today.
In the future, financial institutions will be built on scale of data and the ability to leverage that data
Collaborative solutions built on shared data sets will radically increase the accuracy, timelines, and performance of non-competitive functions, creating mutual efficiencies in operations and improving the safety of the financial system.
“AI is rapidly reshaping what’s necessary to build a successful business in financial services. In the future, financial institutions will be built on scale of data and the ability to leverage that data,” says Deloitte New Zealand partner and banking sector lead Marco Ciobo.
Fulfilling the promise of AI will require an honest and collaborative relationship between an institution’s workforce and leaders, and the transformative impacts of AI will necessitate more public-private commitment, he adds.
“While emerging questions about consumer protections and systemic risks remain the role of regulators, effectively responding to these challenges will require collaboration between public and private stakeholders to resolve regulatory uncertainties and manage the risks and opportunities of AI in financial services.”
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