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The confidence to compete in embedded finance

For banks, building data confidence is key to succeeding in embedded finance.

Simon Axon
Simon Axon
2023年11月30日 3 分で読める

Embedded finance was one of the hot topics at this year’s Money 20/20, garnering almost as much attention as generative AI. And for good reason: according to a June 2023 report available from Research and Markets, the industry is forecasted to grow steadily at a compound annual growth rate of 25.4% between 2023 and 2029 and to generate almost $135 billion in revenues by the end of the decade. Clearly, this represents a tremendous opportunity, and many banks are rushing to stake a claim in this dynamic market. However, many institutions are missing the critical piece needed to truly capitalize on the promise of embedded finance: data confidence.
 

The advantages and risks of an evolving market

Embedded finance involves integrating financial interactions seamlessly into existing customer journeys. It enables frictionless experiences so customers don’t have to leave one app, site, or outlet to pay, secure finance, or buy insurance related to that activity. The advantages are clear: customers get more streamlined, faster experiences that allow them to connect to their purchases or activities without distraction or delay. Merchants and service providers can create better brand experiences and stickiness, and financial service providers gain wider distribution and increased transaction flow.

But there are risks for banks, which are under threat from faster, more innovative, less regulated brands that are seeking to disintermediate them from direct customer relationships. Many of these businesses view the role of banks as limited to providing the financial service “rails” upon which flashier embedded finance applications can run. Banks that don’t challenge this notion are likely to become divorced from customers and relegated to providing the expensive, under-rewarded back-office functions.
 

Becoming “data confident”

Embedded finance is here to stay, and banks can’t afford to watch and wait. Institutional leaders who want to compete in this evolving market must build a data culture, and this means being data confident: knowing your data is reliable and accurate. A data-confident organization knows where their data comes from, understands how it is used, and has the assurance that regulatory, governance, and commercial requirements are met.  

To build this foundation of trusted data, a bank must use an enterprise data platform that harmonizes data across wide variety of sources. Second, they must use their wealth of data more effectively. This requires implementing AI and advanced analytics to quickly make sense of vast datasets at scale. The ability to develop precise customer profiles—segments of one—is key to better understanding and servicing customer needs. By combining real-time data on what customers are actually doing with longitudinal and life stage data, a bank can gain deeper insights into customers that can be leveraged to enable more relevant interactions or to create high-value products for delivery through embedded finance ecosystems.  

Empowered with trusted data and powerful AI/ML capabilities, a bank can have confidence in sharing its data with the wider ecosystem of partners while also maintaining a greater share of customer relationships—and even augmenting its position as a trusted financial services provider.  
Teradata has collaborated with customers across the financial services industry, helping traditional banks and new market entrants alike to utilize data and AI-driven innovation to create new value. For example, PayPal analyzes thousands of personalized data points within a couple of seconds to approve or deny a payment. Similar analyses of heuristics, transaction history, and behaviours underly the automated anti-fraud measures of our partners in banking.
 

Forging a path forward 

The embedded finance market offers the opportunity to partner with players in many sectors, from retailers to B2B service providers and buy-now-play-later (BNPL) specialists. And there are many roles a bank can play. One is that of an enabler, which enables a bank to capitalize on greater distribution for core products. A bank could also orchestrate its own ecosystem of products and services from third parties with the bank as the lead, or it could opt to license services as a new revenue stream. Many banks may opt for a combination of approaches.  

While there are many options, only the banks that successfully integrate and analyze data at scale will be empowered to determine which roles are best for growth and profitability—and will possess the agility to evolve as business needs and market conditions change.If you’re interested in learning how your organization can unlock its data to secure a place in the exciting space of embedded finance, reach out to the Teradata Financial Services Consulting team to schedule a meeting

Simon Axon について

Simon Axon leads the Financial Services Industry Consulting practice in EMEA. His role is to help our customers drive more commercial value from their data by understanding the impact of integrated data and advanced analytics. Prior to his current role, Simon led the Data Science, Business Analysis, and Industry Consultancy practices in the UK and Ireland, applying his diverse experience across multiple industries to understand customers' needs and identify opportunities to leverage data and analytics to achieve high-impact business outcomes. Before joining Teradata in 2015, Simon worked for Sainsbury's and CACI Limited.

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