How artificial intelligence is transforming the financial ecosystem has been saved
How artificial intelligence is transforming the financial ecosystem
The new physics of financial services
As artificial intelligence (AI) significantly changes the traditional operating models of financial institutions—shifting strategic priorities and upending the competitive dynamics of the financial ecosystem—how can financial institutions better embrace AI and prepare themselves for the future?
The World Economic Forum (WEF) and Deloitte Global’s latest report studies the strategic, operational, regulatory, and societal implications of AI on the financial services industry to elucidate previously sensationalized debates and help the industry look forward.
The report finds that artificial intelligence is changing the physics of financial services, weakening the bonds that have held together the component parts of incumbent financial institutions and opening the door to entirely new operating models.
The report highlights nine key findings that describe the impact.
- From cost center to profit center: Institutions will turn AI-enabled back-office operations into external services, both accelerating the rate at which these capabilities improve and necessitating others to become consumers of those capabilities to avoid falling behind
- A new battlefield for customer loyalty: As past methods of differentiation erode, AI presents an opportunity for institutions to escape a "race to the bottom" in price competition by introducing new ways to distinguish themselves to customers
- Self-driving finance: Future customer experiences will be centered around AI, which automates much of customers’ financial lives and improves their financial outcomes
- Collective solutions for shared problems: Collaborative solutions built on shared datasets will radically increase the accuracy, timeliness, and performance of non-competitive functions, creating mutual efficiencies in operations and improving the safety of the financial system
- 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
- 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
- Finding a balanced approach to talent: Talent transformation will be the most challenging speed limit on institutions’ implementations of AI, putting at risk the competitive positioning of firms and geographies that fail to effectively transition talent alongside technology
- New ethical dilemmas: AI will necessitate a collaborative re-examination of principles and supervisory techniques to address the ethical gray areas and regulatory uncertainties that reduce institutions’ willingness to adopt more transformative AI capabilities
The report describes key AI-enabled strategies that are substantiated with real world examples, as well as identifies core institutional and broader ecosystem challenges and uncertainties that need to be addressed.
Read the report to learn how AI can transform your business.
The report also explores the impacts of AI on a variety of different financial services sectors, which are summarised below.
Deposits and lending
AI can improve banks’ profitability through the delivery of personalised advice at scale and the transformation of lending operations. It is allowing institutions to deliver advice at scale and at the moment of need, redefining the value proposition of the retail banking experience. AI can deliver smarter and more nimble workflows that improve the productivity and reach of lending operations. It is launching a commercial banking renaissance through improved data integration and analytics tools that unlock a vast underserved market. Read more in our deposits and lending summary card.
AI will help insurers predict risk with greater accuracy, customise products and use enhanced foresight to rapidly deploy new products. It is driving efficiencies in underwriting and risk monitoring to give insurers a competitive edge, particularly in commoditised markets. AI is being used to evaluate claims, creating workflows that are more accurate and responsive to customer needs. It is augmenting the capabilities of new and existing distribution channels, allowing insurers to expand their reach and scale. AI allows institutions to be more agile, enabling them to deploy new products in response to emerging risk. It allows insurers to make use of their internal data and provide unique service offerings that complement their product shelves. Read more in our insurance summary card.
AI presents new tools to fight fraud, respond to the shifting form of payments and draw valuable insights from data. It is increasing customers’ confidence when making payments by enabling real-time interventions and responses to criminal activities. AI enables payments providers to generate new revenue streams by using their datasets to provide unique insights. It provides valuable tools for payment providers to preserve relevance of the moment of payment disappears. Read more in our payments summary card.
AI is enabling investment managers to adapt their business models by altering or replacing core differentiating capabilities. AI is allowing wealth advisors to provide a personal and targeted investment advice to mass-market customers in a cost-effective manner. It is taking on a growing portion of investment management responsibility, delivering high-quality service at a lower cost. AI-driven personalised portfolio management enables more tailored customer experiences and better investment outcomes. AI enables institutions to serve low-income markets in a cost-effective manner. It can be used to generate products with new return profiles that are uncorrelated with established strategies. Read more in our investment management summary card.
AI has the potential to democratise access to capital across the global economy by unlocking greater efficiency, safety and performance in capital markets. AI can perform administrative tasks faster and better than humans, enabling the latter to focus on higher-value activities. It can help discover promising investment opportunities by tracking down patterns that are not detectable through conventional research methods. AI allows institutions to track their risk exposure more accurately and optimise capital reserves in real time. Read more in our capital markets summary card.
AI can bolster the resilience and efficiency of market infrastructure while allowing providers to augment their value proposition through new services. It allows institutions to automate reporting and better integrate workflows, reducing manual labour and improving straight-through processing. AI is creating new opportunities to develop software ‘as a service’ solutions that address the regulatory and compliance pressures faced by clients. AI is allowing infrastructure providers to introduce new insights by experimenting with their unique access to trade data. It allows institutions to deploy new order types and settlement methods that protect long-term and risk-averse investors. Read more in our market infrastructure summary card.
AI and automation in financial services: What does the future hold?
Uncover findings from this report, and learn more about the potential implications of artificial intelligence across the global financial services environment with our webinar recording.