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The new physics of financial services: adopters of AI in Belgium are compounding competitive advantages.

But are the long term consequences properly addressed? Mid size players will struggle to remain competitive.

Brussels, 6 November 2018

Artificial intelligence (AI) is rapidly changing the way financial services institutions attract and retain their customers, and it will necessitate new models of collaboration amongst competitors. A new report from World Economic Forum and Deloitte, The New Physics of Financial Services,” explores how AI will transform the realities of 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. Jean-Marc Boxus, Senior Director at Deloitte Belgium: “The duality of the competitive landscape between players going for lower costs commoditized products, leveraging scale on the one hand, or looking for niches, building on agility on the other hand, will increase. This will leave mid-size players struggling to invest to remain competitive.”

As AI drives operational efficiency, economies of scale alone will not sustain cost advantages. In the future, financial institutions will be built on scale of data and the ability to leverage that data. This is an opportunity for competitors to join forces and jointly reap benefits from the technology. Firms that lag behind are finding that their old strengths such as low cost standardized products, physical distribution networks or high switching costs, may not keep them as competitive as they once were. Jean-Marc Boxus continues: “Earlier adopters of AI in Financial Services are compounding short term competitive advantages by improving their operations, offering differentiate customer experiences and improving customer’s financial lives. However, unlocking the long term benefits of AI will require nothing less than a collaborative effort, forming strategic collaborations and working with regulators and policymakers to address the ethical grey areas around the safety of financial markets, customers and workforce.”

Core findings specifically explore how AI is radically transforming the front- and back-office operations of financial institutions:

Cost centers to profit centers

AI enabled back-office functions, built on a hyper-agile micro-services architecture, will allow financial institutions to turn their centers of excellence into services. 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 virtuous cycle both accelerates the rate at which capabilities improve and leave competition struggling to catch up.

A new battlefield for customer loyalty

Past methods of differentiation for financial institutions—such as price, speed and access—are eroding profit margin. The ability to customize services, engage users and access data through ongoing and integrated interactions beyond financial services will allow them to better retain customers.

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, centering 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 personalized advice based on data; and continuous optimization 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.

Additional findings from the report explore major shifts in the structure and regulation of financial markets and critical challenges for society to resolve:

  • Bifurcation of market structure: As AI reduces search and comparison costs for customers, firm structures will be pushed to market extremes, amplifying the returns for large-scale players and creating new opportunities for niche and agile innovators. This will leave mid-size players struggling to invest to remain competitive
  • Uneasy data alliances: In an ecosystem where every institution is vying for diversity of data, managing partnerships with competitors and potential competitors will be critical, but fraught with strategic and operational risks.
  • The power of data regulators: Regulations governing the privacy and portability of data will shape the relative ability of financial and non-financial institutions to deploy AI, thus becoming as important as traditional regulations to the competitive positioning of firms.
  • Adapting talent strategies: Talent transformation will be the most challenging roadblock on institutions’ implementation of AI, putting at risk the competitive positioning of firms and regions that fail to effectively transition talent alongside technology. 
    Boxus explains: “AI will require new skills while traditional jobs will be reduced. This will have to  be anticipated properly for example in different master programs at Belgian Universities. Data scientists, algorithm development and AI training are typically new roles that will gain in importance.”
  • New ethical dilemmas: AI will necessitate a collaborative reexamination of principles and supervisory techniques to address the ethical concerns and regulatory uncertainty that are hindering institutions’ willingness to adopt more transformative AI capabilities. “It is possible that AI platforms put the safety of the financial system at risk like for example the 2010 flash crash. In that way regulators and market authorities have to ensure that the AI platforms protect the best interest of the consumers and employees” said Jean-Marc Boxus.
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