Data monetization in the banking sector has become increasingly prevalent in recent years, driven by evolving customer expectations, new data sharing rules and opportunities for new revenue streams.

Twimbit, a Singaporean research and advisory firm, identifies data monetization as one of the biggest growth opportunities for banks in Asia-Pacific (APAC), which, alongside super-app platforms, financial marketplaces, banking-as-a-services and buy now, pay later (BNPL) arrangements, are projected to contribute over 40% of banking revenue by 2030.

Data monetization refers to the process of using data to obtain quantifiable economic benefit. Internal or indirect methods include using data to make measurable business performance improvements and inform decisions, while external or direct methods include data sharing to gain beneficial terms or conditions from business partners, information bartering, selling data outright, or offering information products and services.

In the banking sector, data monetization presents significant opportunities to drive growth, improve operational efficiency and deliver value-added services to customers. By leveraging their vast treasure trove of customer data, banks can unlock new sources of income, enhance customer experience and gain a competitive edge, experts say.

Personalized products and services

Muthukumar Krishnan, senior partner at Infosys Consulting, highlights in a blog post the significance of data analytics for personalization and customer experience. By analyzing transaction history, spending patterns, and other behavioral data, banks can understand how users interest with various service channels to tailor entire customer experiences and facilitate product adoption.

Krishnan illustrates these opportunities with various scenarios, such as a newly wed couple seeking a mortgage loan with attractive interest rates, a young family planning for their children’s college education, or an entrepreneur wanting all their personal and business banking needs to be met by one institution.

Providing a personalized experience is crucial for maintaining positive customer engagement and satisfaction, Krishnan says, noting that customers are most likely to become repeat customers with organizations that know their financial needs, goals, and level of risk. This enhances the overall customer experience.

Customer segmentation and personas

Banks are also utilizing data analytics to divide their customers into different groups based on factors like age, spending habits, and major life events.

Customer segmentation involves dividing the customer base into groups with similar characteristics and creating accurate customer personas. This segmentation helps financial institutions better understand the unique needs of each group, enabling them to customize their products, services, and marketing efforts accordingly. This ultimately helps boost customer satisfaction and loyalty, but also allows banks to allocate resources more effectively, Krishnan says.

Through data analysis, banks also gain insights into customer spending habits and how broader economic shifts impact saving and spending behaviors, an insight which allows them to offer more relevant services that truly meet individual needs.

Overall, Krishnan emphasizes that personalized customer experiences are key to enhancing satisfaction and loyalty. By leveraging data for customization, financial institutions can stand out from competitors and drive higher levels of customer satisfaction, loyalty, and retention, he says.

Cross-selling and upselling opportunities

Customer data analysis also helps banks identify cross-selling and upselling opportunities. A case study by Simon-Kucher showcases how banks can leverage data analytics to optimize sales interactions and empower their sales and relationship managers.

The strategy consulting firm worked with a leading global bank which had experienced declining performance in selling high-value financial products like funds and investments after the pandemic. This decline was due to the complexity and the effort required in the buying process.

To address this, Simon-Kucher introduced a systematic approach leveraging data, analytics and behavioral science to enhance sales interactions, improve client experience, and empower the bank’s sales and relationship managers.

This approach involved identifying psychological barriers to buying, auditing the sales process, and optimizing sales performance. First, Simon-Kucher conducted market tests to understand the cognitive barriers impacting the high-value financial products offered by the bank, and then ran a thorough assessment, audit, and analysis of the bank’s sales teams and sales processes. It then developed and implemented interactive scripts and digital tools to guide clients through the buying journey effectively and simplify complex concepts using examples and straightforward language. Finally, testing and validation protocols were deployed to ensure the effectiveness of these solutions.

According to Simon-Kucher, this approach allowed the bank to improve customer experience and increase its commercial effectiveness, resulting in a remarkable 50% increase in conversion rates.

An evolving regulatory landscape

The surge in data monetization within the banking sector coincides with governments worldwide implementing new data sharing rules and establishing open banking standards to promote innovation, enhance competition and drive financial inclusion.

India, for example, has invested heavily in infrastructure, including the Unified Payments Interface (UPI) and the Account Aggregator (AA) framework. UPI, launched in 2016, by the National Payments Corporation of India, enables instant real-time payments between bank accounts through mobile devices, while the AA framework, introduced in 2021, allows individuals and businesses to consent to sharing their financial data across multiple financial institutions securely.

In Australia, open banking is mandated under the Consumer Data Right (CDR) legislation. The legislation, enacted in 2019, aims to empower consumers by giving them the right to access and share their data held by businesses in various sectors, starting with banking. The rollout of the CDR legislation is being conducted in stages, starting first with the banking sector, followed by the energy sector, and then non-bank lending sector.

Most recently, the Philippine central bank launched the Open Finance PH Pilot. The central bank said in a press statement that the pilot is a voluntary undertaking of financial institutions to co-develop an open, interoperable and scalable ecosystem. This platform would focus on allowing consumers to have more control over their financial data and access a broader range of financial products and services provided by different companies.

The launch of the Open Finance PH Pilot in mid-2023 marked the next phase in the implementation of open finance in the Philippines, and followed the issuance of the Open Finance Circular Number 1122 in 2021, a framework that outlines guidelines for enabling data sharing and data portability in the Philippine financial sector.

Webinar: Monetizing Transactional Data in Banking

Join this upcoming webinar to hear from banking experts on effective monetization of transactional data and how this can unlock potential revenue streams for banks. Register at this link.

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