Payment Data: The Textbook of Many Payment Journeys

Data as a Textbook for Artificial Intelligence

In the realm of artificial intelligence (AI), data serves as the “textbook” from which models learn and make decisions. Just as students rely on the quality of their textbooks to learn accurately, AI systems rely on high-quality data to function effectively. Poor data, like a bad textbook, produces biased, unreliable, and inaccurate results. This issue becomes even more critical with Generative AI (GenAI), which creates new content based on patterns in its training data or prompts. If the data textbook is poorly written, even the most powerful GenAI will produce low-quality results, underscoring the need for clean, accurate information.

This blog highlights the critical role of quality data, with a particular focus on payment data and its importance. Accurate payment data is essential for effective AI applications, which are critical for delivering tailored experiences, from recommendations to predictions. Conversely, incomplete or ambiguous data leads to poor customer outcomes and poor decisions. Ultimately, high-quality payment data improves transparency, which leads to better customer experiences and higher satisfaction.

Quality Payment Data: The Key to Better Services

Have you ever been puzzled by a strange charge on your credit card statement or a cryptic transaction in your transaction history? You’re not alone. Not too long ago, I received my credit card statement and had to Google the description to figure out where I spent the money and for what.

And, as we move toward new AI-powered user experiences, they will increasingly rely on accurate, comprehensive payment data.

Processing of raw transaction data with SIX Payment Enrichment Services

With Payment Enrichment Services, we address these needs and make payment data self-explanatory.

How does it work?

Under the hood, we mine data from external sources and apply various techniques, such as pattern recognition, to “understand” the semantics of the transaction and generate new content such as the category (e.g., transportation, grocery), unique merchant names, logos, and geographic information about the merchant, i.e., store location.

This enriched data not only enhances the customer experience, but also makes AI applications more effective and optimizes key processes such as chargebacks.

High-quality payment data is more important than ever to enable the effective use of AI, among other things.

Imagine having a bank account that curates your payment data and analyzes your spending habits. The bank can identify patterns in your spending, such as frequent purchases at certain stores, regular subscription payments, or recurring invoices. With this information, the bank can help you make better financial decisions. For instance, if the bank notices that you frequently shop at a particular grocery store, it can offer you a credit card with cash back rewards.

Optimize savings potential thanks to high-quality payment data

Alternatively, the bank can provide intuitive services to help you better understand your personal finances. For example, providing answers to a wide range of questions, from simple ones like “How much did I save last month?” to more complex ones like detecting unusual transactions, predicting future grocery spending, or offering personalized recommendations to optimize savings. All of this is possible by combining high-quality payment data with the appropriate AI techniques to answer specific questions.

With the advent of multibanking for retail customers in Switzerland, the need for high-quality and consistent payment data – regardless of the originating bank – will become critical. The consistent consolidation of underlying payment data from multiple sources serves as the foundation for a wide range of innovative services and apps that offer personalized financial products.

Payment Enrichment Services: Free test version

Transform raw data into valuable insights with Payment Enrichment Services from SIX. Drive data-driven product development and enhance transparency in your customers’ personal and corporate finances.

Our Sandbox is free to use and available via API in a risk-free environment.

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Ensuring Payment Data Quality: A Continuous Effort

Payment data quality management is not a one-time effort. It is an ongoing process that involves ensuring that payment data is accurate, consistent, and complete. Tools such as payment data enrichment are essential to maintaining high payment data quality, paving the way to better financial products.

Continuous quality management ensures correct, consistent and complete payment data.

Conclusion: Building Sustainable AI Solutions with High-Quality Payment Data

As a reflection of the information in the training data, AI systems excel when fed with high-quality data. The metaphor of data as AI’s textbook illustrates the importance of ensuring that our AI “students” are learning from the best sources. As AI becomes more integrated into our daily lives – predicting spending trends, spotting anomalies, or helping to make better investment decisions – the quality and bank-agnostic consistency of payments data will become increasingly important. This will become even more important as we approach the final implementation phase of multibanking in Switzerland, which will pave the way for novel financial products. By paying attention to the integrity and quality of payment data, we can ensure that we not only improve our current user experience, but also contribute to a better overall offering.