Banks are overwhelmed by payments data. Does unified processing offer a lifeline?

Digitization and compliance have been facts of life for banks for decades. But part of the reason for they why might feel overwhelmed by data right now is the sprawling diversification of sources available to them.

Digitization has enabled banks to collect data from multiple new sources beyond traditional transaction records. To enhance their understanding of customer preferences and behavior, they have access to a wealth of information from across their various online and mobile channels. The devices consumers use are also a mine of information that can be used to authenticate customers and understand fraud risks, such as geolocation data and device usage patterns. Digital wallets, peer-to-peer payment apps, and other alternative payment methods – all have also further expanded the types of data banks must manage and analyze to process and protect payments.

Banks themselves, alert to data’s potential, have contributed to the issue by undertaking various advanced analytics and big data initiatives. They’ve amassed mountains of data in their efforts to gain insights into customer behavior, identify fraud, automate processes, and develop personalized products. More recently, these initiatives have pivoted towards machine learning and generative AI applications, which require large amounts of historical and real-time data to train models, further contributing to the data deluge.

The challenges facing banks when it comes to effectively, efficiently and consistently capitalizing on their high volumes of payments data have their roots in legacy payments infrastructure and skill shortages.

Skilled data scientists, data engineers, and analysts are in short supply. And without them, it is difficult to consistently leverage the advanced analytics, machine learning, and AI tools that turn raw data into actionable insights.

But legacy payments infrastructure arguably presents the bigger challenge of the two. Many of the systems in place today were not designed to handle the volume, variety, and velocity of modern data. They rarely integrate well with one another, or more modern data and analytics solutions, and so they lack the flexibility needed to process and analyze large datasets efficiently. Consolidating that data from across multiple platforms to, for example, create a unified view of customer behavior or risk profiles, requires significant effort in data cleaning, transformation, and integration, which can delay insights and decision-making.

By phasing out legacy payment systems in favor of unified payment platforms, banks can pave the way to solving their data difficulties.

By centralizing today’s diverse data streams into a single system, banks could reduce the complexity and effort required for data integration, cleaning, and transformation. A modern, open data management architecture along the lines of a data lakehouse concept would make them better able to respond to change and to adopt the latest solutions. This, ultimately, would help them to access a more coherent and unified view of customer behavior and risk profiles, reducing the delays in insights, innovation, and decision-making that are caused by fragmented systems. A unified payments system could also facilitate better compliance and easier reporting by providing a centralized repository of all transaction data and other information needed for AML and KYC requirements.

Importantly, this kind of payment modernization is likely to be a prerequisite for any meaningful innovations with AI. A single, integrated source of payments data would enable banks to more easily apply machine learning models and advanced analytics to derive actionable insights, automate processes, and personalize services, thereby unlocking more value from their data. There would also be opportunities to reduce the operational complexity and costs associated with managing multiple payment processing systems and to provide customers with more personalized and consistent experiences.

A unified payments infrastructure is not just a solution to the data overload facing banks. It is an enabler of efficiency and innovation – both of which are long-standing business imperatives.

By unifying payments processing and all associated data, and simplifying compliance, banks can shift their focus from merely managing data to actively leveraging it for strategic insights, enhancing customer experiences, and driving operational efficiency. This modernization effort will enable banks to fully capitalize on emerging technologies like AI and machine learning, positioning them to stay competitive in a digital, data-driven and real-time world.