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    The Emergence of a New Banking Model

    Banks should prepare for a new business ecosystem driven by the financial technology (FinTech) revolution. Learn how the industry can adapt to disruptions by optimizing resources, revamping technology, analytics and data platforms, improving efficiency, rebuilding their capital base, changing the risk culture, reducing payout ratios, and searching for new business models.

    The banking sector has changed dramatically since the 2007 financial crisis, which severely affected the traditional growth engines of investment and corporate banking. Stricter global regulations and financial legislation have increased the level of capital, shrinking the profitability of the investment and lending activities, lowering leverage and revenues (Figure 1).

    At the same time, a long period of ultra-low (Figure 2) and, in some areas, negative interest rates have left banks struggling to accelerate their deposit base growth given the increasing competition, lower margins, and new customer behaviors. In addition, the wide-spread adoption of social media, mobile technology, and the web by many customer segments is radically changing the way they interact with banks and other financial institutions. It is also transforming how these institutions manage and interact with their customers. As a consequence, banks face increasing challenges in acquiring and retaining customers, along with low interest rates and maintaining and growing margins.

    These external factors are exacerbated by outdated banking infrastructure and legacy systems that limit timely responses to new regulatory and business requirements. Manual processes in the front, middle, and back offices, lack of automation, and use of traditional analytics are dragging down efficiency and represent a huge cost for a business. Applications for loans can usually take weeks, individuals without credit history cannot access basic banking services, and a lack of credit information from small and medium enterprises make their access to financing extremely difficult and expensive.

    Preparing for the FinTech revolution

    Technology is reducing information asymmetry in the financial and consumer sectors. Borrowing Daniel Goldin’s quote, information is being shared and distributed “faster, better, and cheaper.” As a consequence, emerging new business models are more customer focused, have a lower cost, and are more efficient than traditional banking models (e.g., peer-to-peer lending and alternative payment systems).

    Banks should prepare for a new ecosystem driven by the financial technology (FinTech) revolution, as it represents one of the biggest threats to the banking industry. After all, global FinTech investment tripled to $12 billion from 2013 to 2014 1 (Figure 3). Investors around the world are starting to price innovation in banks’ valuations and are considering the effect of non-bank competitors. FinTech companies are also putting additional pressure on banks’ margins and revenues by providing traditional banking services and fee-based solutions (e.g., lending, payments, wealth management, etc.) with lower costs. Therefore, financial institutions should not underestimate new incumbents in the financial space and the potential impact on future revenues. For example, Apple was not even considered a competitor by Nokia during its 2008 investors presentation.2

    From a strategic perspective, Moody’s Analytics views how banks and financial institutions respond to the following themes as key to the success or failure of these institutions in the coming years:

    1. Digital banking: Firms must adjust to digital replacing brick-and-mortar as the primary banking channel.
    2. Operational efficiency: How can firms best operate in a low interest rate, low margin environment?
    3. Non-traditional competitors: For example, peer-to-peer and online marketplace lenders
    4. Payments systems: Cryptocurrencies, smart contracts, and new settlement processes
    5. Distributed data architectures: Technologies based on Hadoop, Apache, Spark, open APIs, etc.
    6. Cyber risk and cyber security: How will banks address security concerns?
    7. Leveraging data and analytics: Gain new insight, open up new business opportunities, and develop new products.

    As these themes evolve, the investment in analytics development and enterprise software will increase, reshaping the banking and finance industry. This will affect how a customer views banking and the speed, cost, user experience, transparency, and openness of transactional and consumer banking in a way never they have never seen before. Non-traditional competitors will also erode banks’ already low margins, requiring non-traditional responses:

    • Customizing their offerings to clients’ needs; analyzing sentiment scores to maximize retention rates
    • Enhancing risk and underwriting analytics
    • Designing new financial products using new technologies, such as the Internet of Things and data from wearable technology (i.e., based on location, business activity, environmental factors, shopping, or weather patterns
    Figures 1 and 2
    Figure 1. Net interest margin for US Banks, %
    Figure 2. Effective Federal Reserve funds rate, %
    Net interest margin for US Banks
    Source: Moody's Analytics

    The FinTech revolution is also transforming banks into big data factories (Figure 4), driven by customer interactions with their websites, third-party vendors, or mobile applications. Nowadays, banks generate and record terabytes of daily information – from geographical pinpointing and transactional data to life events (e.g., deposits, paychecks, mortgages, rent, shopping habits). Consumers and small and medium enterprises also express interest for financial products through search engines and social media; thus generating a wealth of information that can substantially improve the underwriting and credit scoring process of those individuals.

    The ability to leverage this data across different functions, coupled with the analytic layer to exploit it, can give banks a competitive advantage over their competitors – from generating better predictive insights about customers to customizing the risk management, pricing, and underwriting process.

    Figure 3. FinTech investment, USD billion
    FinTech investment
    Source: Moody's Analytics
    Figure 4. Non-traditional credit and financial metrics – Creating value through data aggregation and benchmarking
    Non-traditional credit and financial metrics
    Source: Moody's Analytics

    Digital banking transformation

    Digital banking is growing rapidly across customer segments and is poised to replace traditional brick-and-mortar branches as the core channel for banking. Traditional relationship management, which most banks rely on as a vehicle for maintaining a low cost of funds and a high lending margin, cannot be easily adapted to the new digital banking landscape and electronic distribution channels.

    The digital banking transformation, while reducing operating costs and facilitating market penetration, is coming at a cost to banks. Tasks like account comparison shopping are becoming increasingly simple, forcing banks to erode margins to maintain a competitive advantage and retain customers. Therefore, to enhance digital relationships and provide highvalue, one-to-one services to digital customers, banks will have to develop a new generation of analytics to evaluate customer behavior data and make inferences about customer needs and risk profiles.

    The impact of technology: Industry response

    The industry (Figure 5) is adapting to these disruptions by optimizing resources, revamping technology, analytics, and data platforms, improving efficiency, rebuilding their capital base, changing their risk culture, reducing payout ratios, and searching for new business models.

    Figure 5. Adopting the FinTech revolution – Benefits for financial institutions
    Adopting the FinTech revolution
    Source: Moody's Analytics

    Regulators also view technology as the key element for improving the transparency of the financial system and facilitating the supervisory and data evaluation processes of both banking and non-banking institutions. However, there is still a lack of clarity about operational and regulatory requirements as well as lack of cross-border coordination about how regulators will approach a new generation of analytics and technology being used by banks.3 There is also an important shift in the attitude of business leaders and senior management, who recognize the incredible value in bringing new technologies and analytics to the banking business and sharing data across the organization:

    • On the organizational front, banks have started adopting a less siloed approach to their business. The conditions are also significantly different in terms of how technology and regulatory requirements can facilitate this change in organizational dynamics.
    • The exponential advances in technology and the adoption of enterprise-wide risk architectures and cloud-based computing approaches present a unique opportunity for banks to advance their traditional analytics and scoring processes, which extends services to a wider segment of the population. In addition, data processing and real-time analysis capabilities are also significantly different than those available decades ago. They have provided banks with the technology and infrastructure to exploit and monetize multiple sources of data in a cost effective and timely manner.
    • Security and data privacy will be key for financial innovation success. Privacy laws and banks’ concerns about security have been a major issue in the financial space. However, a new generation of remote data processing capabilities (e.g., cloud computing) and improvements in security are addressing these concerns.
    • Modern data-mining applications represent the next frontier in banking analytics, from risk management to fraud detection, digital authentication, and security. In Moody’s Analytics view, the next generation of predictive risk management analytics and business intelligence platforms will use large-scale customer and enterprise behavior data, analyzed by cutting-edge machine-learning algorithms to arrive at predictive inferences. This, in turn, will facilitate the discovery of trends and quantification of risk profiles while driving business actions.
    • Banks are launching their own FinTech funds and innovation labs to accelerate the adoption of new technologies and analytics. FinTech funds allow banks to tap into innovation outside of their own technology ecosystems to capture new trends such as data-mining-driven scoring systems, cash management, and predictive analytics focused on maximizing and monetizing client relationships across the full spectrum of banking services (e.g., small and medium enterprises, corporate clients, wealth management, and retail banking).

    Banks should prepare for a new ecosystem driven by the financial technology (FinTech) revolution, as it represents one of the biggest threats to the banking industry. After all, global FinTech investment tripled to $12bn from 2013 to 2014.

    Effectively implementing these technologies will enable banks to make better informed underwriting and credit decisions, automate processes and services, develop new products, minimize fraudulent behavior, improve efficiency, reduce risks, and help understand the evolving nature of the banking business, and quantification of clients’ risk profiles and behaviors. This should lead to a more sound, lower-risk financial system comprised of more efficient banks with extended services and financing opportunities for a wider segment of the population.


    1 The Future of FinTech and Banking, Accenture 2015.

    2 Extending the leading device market position, Lehman Brothers Wireless Conference, May 2008.

    3 The Australian Prudential Regulation Authority (APRA) is one of a few that has released an information paper about its expectations when using cloud computing and sharing data: Outsourcing involving shared computing services, July 2015.

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