Mid-size and small banks and credit unions could soon find themselves at a serious competitive disadvantage. Ongoing developments in artificial intelligence have the potential to significantly change the way back offices operate and the experiences consumers receive from financial institutions. More importantly, these new technologies could disrupt how banks and credit unions attract and retain their customers, create new business models and present regulatory issues, according to the report, “The New Physics of Financial Services” from the World Economic Forum and Deloitte.
There is little doubt that AI can provide significant benefits for the banking industry, as has been documented often in The Financial Brand. However, the 166-page analysis finds that the significant efficiencies that AI provides through the use of data could provide the largest financial services organizations and tech companies with unmatched competitive advantages at the expense of mid-sized and small banks and credit unions. A bigger concern could be that the industry is not prepared to respond, concludes the report.
“Markets are already emerging where data sharing is critical to competitive success and first movers are positioned to distinguish themselves by delivering better advice, constant presence, and curated ecosystems. Firms that lag behind are finding that their old strengths may not keep them as competitive as they once were.” – Rob Galaski, Deloitte
Nine Ways AI Will Disrupt Traditional Banking
The World Economic Forum report identifies nine ways that AI is changing the traditional structure of financial services industry, creating new competition as well as the need for modified governance. Each of these findings will impact banks and credit unions of all sizes, requiring new strategies that will impact the future of how organizations are structured and consumers are served.
1. Cost Centers Become Profit Centers: Artificial intelligence will allow the the most efficient institutions to turn back-office operations into external services, which will be purchased by financial institutions not wanting to fall behind. As institutions consolidate back-office capabilities, the data collected will allow for insight development to be leveraged as a competitive advantage.
There will be an interesting balance needed to be addressed by financial institutions as they determine what data services to offer to outside “competitors.” In addition, how will regulators respond to these new third-party agreements?
2. Personalization as a Competitive Weapon: With the past benefits of cost, speed and accessibility eroding as competitive weapons, a new battlefield for customer loyalty is emerging around the ability to create value from using data and insights to create real-time custom solutions and recommendations. By bringing together data from consumers, commercial organizations and third parties, financial institutions will be able to impact consumer’s financial well-being.
Will traditional financial institutions be able to compete in a highly personalized marketplace? And how will consumer privacy be maintained?
“The ability of institutions to optimize financial outcomes by tailoring, recommending, and better advising customers will allow them to compete on value offered.”
3. Emergence of Self-Driving Agents: Rather than relying on multiple financial services organizations for products, services and advice, AI-driven financial intermediaries will emerge that will provide recommendations on the best products, services and advice to use, regardless of provider. This agent will recommend switches in providers and optimization of solution based on personalized algorithms.
The question is whether the provider will be a traditional financial firm, a new entrant, a tech company, or another player? Also, how can we ensure that agents work on behalf of consumers?
“An emerging risk is that ‘self-driving finance’ will upend existing competitive dynamics, pushing returns to the customer experience owner, while commoditizing all other providers.”
4. Collaborative Solutions: With the impact and value of data and advanced analytics becoming increasingly important, the value of collaboration between organizations inside and outside financial services becomes stronger. This is especially true in areas such as fraud prevention, know your customer (KYC) capabilities and improved consumer experiences.
In a shared data marketplace, how will liability for errors be handled? Also, can regulations be created for cross-border solutions?
5. Disruption of Market Structure: As AI-driven solutions continue to emerge, scale players with the lowest cost products and smaller niche innovators that can serve unmet needs will prevail, negatively impacting regional and mid-sized organizations the most. This will create significant disruption of the marketplace, with providers at the extremes of size and offerings. Will the ‘too big to fail’ discussions become front and center again?
“Polar forces are pulling the middle apart and the risks to mid-tier firms are ramping up in this new market”
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6. New Data Alliances: To benefit from expanded data and AI opportunities, banks and credit unions will be pushed into alliances that may not be as comfortable as in the past. Balancing short-term benefits and longer-term risk ramifications will challenge institutions that want to be at the center of the new banking ecosystem as opposed to being at the periphery.
The question becomes, who will retain control of the customer experience and how will smaller banks and credit unions get access to the insight large firms will have?
7. Data Regulations Gain Power: Data regulations will potentially become more important than traditional financial regulations in determining market structure. Today, regulations of technology companies are more relaxed with regulations regarding cloud use differing across markets. At the same time, consumers increasingly want control over the use of their data.
It will be interesting to see how regulations can be developed for cross-border data flows. Also, as privacy laws differ regionally, how will universal regulations be developed and applied?
“In a market 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.”
8. Redefinition of the ‘Future of Work’: Current roles and responsibilities are changing the needs for talent in financial institutions, with a significant shortage of talent emerging. In fact, many believe that talent transformation will be the most challenging hurdle to the implementations of AI at financial institutions. This challenge is compounded because many organizations are not culturally ready for the digitization of banking or aligned on the timing and impact of AI.
Banks and credit unions must ask themselves, “What specific talent is required to move forward in the near term and in the future?” A bigger question is: How will the use of AI and robotics impact the “future of work” as a whole?
9. New Ethical Issues Emerge: The speed and scope of impact of AI on society and economic well-being can’t be ignored states the WEF/Deloitte report. The safety and security of financial systems and consumer interests are at stake, including regional growth potential and income equality.
It is clear when we discuss AI and cross-industry sharing of data, we don’t know what we don’t know. Much of this change is happening faster than regulations can respond, with the risks multiplied accordingly.
Data and Analytic Opportunities in the Future
The WEF/Deloitte report references many opportunities that can result from the use of data and advanced analytics. These range from increased efficiency, more personalized services and engagements, increased availability of solutions, smarter decisioning and new value propositions.
With greater insights into consumer behavior and needs, solutions will be able to be delivered in real-time, potentially expanding beyond financial services. This capability will favor larger institutions as well as those serving niche and underserved markets.
The reach of banks and credit unions can be expanded as virtual agents work on behalf of the consumer to find the best mix of solutions for each individual. This transformation may also result in the elimination of specific traditional products (checking, loans, payments) with the emergence of universal cash management solutions that address all needs in an integrated service.
Future Challenges of AI
Not surprisingly, the challenges presented by the emergence of AI revolve around the access to and efficient processing of data, the ability (and willingness) to change back-office operations, the availability of talent and the speed of regulatory changes that will most likely impact all of the aforementioned challenges.
“The operating models of financial institutions are being fundamentally reshaped, making financial institutions more specialized, leaner, more highly networked – and more dependent on the capabilities of technology players.”
While financial institutions have historically possessed vast reservoirs of data, much of this data is stored in product-centric silos, making predictive 360 degree insights around individual consumers difficult to develop. Data quality is also questionable at many organizations, with much of the most important data still not in digital formats.
Legacy operating systems are also difficult to leverage in our digital age, with investment in modernization already behind the curve. Making matters worse is the reality that fintech firms and large tech organizations are far ahead in the digitalization of their enterprises.
How Should Financial Institutions Respond?
There is no argument that advanced technologies, access to data and competition is disrupting the financial services industry. But, what should banks and credit unions do in response to these changes? What do governments need to do to prepare for the changes that will most definitely occur in the future?
For banks and credit unions, there is a need to actually embrace change that is occurring faster than ever in the past, and realize that change will not slow down in the future. Organizational cultures need to adjust accordingly, with the realization that a strategic framework must be developed that will prepare each institution for the future.
Will your institution be able to partner or build affiliations with other organizations to be an insight leader and/or back office services “seller”? Or will your bank or credit union be a specialized provider serving a niche market. Continuing down the current path is most likely not a good option.
Financial institutions must take risks that are different than in the past. Ranging from the way that credit risk is evaluated to the way each institution works within compliance guidelines,, the future will be less black and white.
Is your bank or credit union willing to accept risks that will position it the best for the future needs of the consumer? How will you evaluate the risk associated with partnering with organizations inside and outside banking?
Finally, it is imperative that both financial institutions and their employees become willing to disrupt themselves. Not just from an organizational structure but also from a cultural perspective. In this process, there needs to be a realization that past success may be your worst enemy. Because, there is a good chance that while past successes will serve as a strong foundation, these same successes can be an anchor that holds people and organizations from progressing.
Can banks and credit unions and the people who work there rethink everything that has been the norm? Can they use data, analytics and AI as the stepping stone for future growth and prosperity?
The WEF/Deloitte report concludes that there is relatively little understanding of the impact (or even the definition) of AI within the financial services industry. In fact, most discussion around data, analytics and AI deals with the technology itself, as opposed to the associated strategic implications. They believe this gap in understanding and discussion of both risk and rewards is dangerous.