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Bank user data analytics: The tricky balance between innovation and regulation

Banks are increasingly personalizing services through user information but face challenges in data privacy regulation.

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Quantumrun Foresight
January 26, 2024

Insight highlights

Data generation is expected to double from 2018 to 2022. This surge has led to increased data utilization by businesses, including financial institutions, but also raised concerns about proper data usage and security. Companies face potential risks of data misuse, resulting in financial and reputational damage. Despite regulatory challenges, bank user data analytics advancements have far-reaching implications, including tailored financial products, new tools and applications, increased demand for skilled workers, and targeted lending.

Bank user data analytics context

According to a white paper by research firm Oliver Wyman, data generation has experienced a massive surge, as the worldwide data quantity is expected to double between 2018 and 2022. Both established companies that predate the digital era and financial technology (fintech), as well as major tech firms, are swiftly expanding their capacity to gather and utilize data on their customers. Internet-of-things (IoT) technologies enable businesses to gather a broader range of customer information, such as location and behavior. Moreover, advanced computing facilitates better storage, management, and data transfer, while sophisticated analytics allow for a deeper understanding of customer behavior and preferences.

These advancements have paved the way for business innovation, but they have also generated concerns about the proper use of customer data. Governments worldwide are contemplating incorporating aspects of the European Union's General Data Protection Regulation (GDPR). Business executives are evaluating their response to potential third-party misuse of customer data. Meanwhile, customers are questioning the methods companies employ to collect, utilize, and share their data, as well as the advantages they receive in exchange.

Safeguarding customer data presents difficulties, as it can be exploited by malicious individuals within an organization, taken by cybercriminals, or shared improperly with external parties. Data misuse may result in direct financial losses stemming from increased fraud claims or regulatory penalties. Companies that do not pass the "newspaper test" (i.e., the consequences of their data misuse becoming public knowledge) may also suffer considerable damage to their reputation.

Disruptive impact

The rapid increase in digital adoption serves as a post-COVID-19 pandemic silver lining for various industries, including financial services, emphasizing the importance of providing smooth, smart customer experiences. Financial institutions are expected to not only flawlessly execute basic servicing tasks but also build upon them. Banks are starting to leverage user data analytics for more personalized services by adopting a "data mesh" approach instead of a centralized data repository.

This strategy allows their employees to access data from various sources. The information can be arranged into logical domains based on the bank's business requirements rather than technical classifications. With a well-defined governance and access control framework established, banks can "democratize" their data by granting each business unit access to the data mesh, thereby enabling them to take increased responsibility for the quality and value of the database.

However, the growth of data-driven innovation can be hampered by increasing demand for regulation. While most governments are keen on promoting fintech, they also worry about potential risks that could undermine confidence in the financial system. As regulators worldwide experiment with novel tools and strategies, they may grapple with the challenge of dealing with products and services that don't fit within current regulatory frameworks. Rapid technological progress can render existing laws and regulations outdated, causing frustration for both customers and businesses trying to utilize innovations. At the same time, customers may feel uneasy if they believe governments are not adequately shielding them from emerging risks.

Implications of bank user data analytics

Wider implications of bank user data analytics may include:

User data analytics enabling financial institutions to better understand the needs and preferences of different demographic groups. This technique could lead to more tailored financial products and services but could also perpetuate stereotypes or exclusion of certain groups.

Advances in data analysis and artificial intelligence, which may have far-reaching technological implications, including the development of new tools, applications, and platforms.

Increased demand for workers with skills in data analysis, artificial intelligence, and machine learning.

Enabling more targeted lending and investment, which could facilitate the growth of green industries and renewable energy.

Financial institutions using social media data to better understand their customers and develop more effective marketing strategies.

Governments becoming concerned about privacy and security and may seek to regulate or limit data collection. At the same time, financial institutions may use their data and influence to shape public policy and political agendas.