Optimizing Data Utilization in Banking
Data has become crucial for managing financial portfolios effectively, with a focus on ensuring operational efficiency. However, the bank’s ability to transform raw transaction data into actionable insights quickly is essential. This is the premise of Visa’s Data Strategy, particularly their Data Manager platform, which aims to provide reliable card and account information that can be instantly utilized by those running the issuing business.
According to Nick Roberts, Senior Director of Visa DPS Product Management in Data and Analytics, publishers are eager to access data encompassing various profitability metrics and fraud indicators. This information enables issuers to pinpoint high-value cardholders and optimize spending more effectively.
Roberts mentioned that obtaining data has become more streamlined. Publishers dislike having to navigate a separate dashboard outside their regular workflow. The Data Manager integrates a comprehensive dataset and various DPS tools into a single application, allowing clients to access information tailored to their needs: whether through web interfaces for business users or APIs and cloud integrations for developers.
This flexibility extends to how and when different users engage with the data. Executives can log in to view aggregated KPIs and portfolio data, while data teams can pull detailed extraction files into their own analytics warehouses. In contrast, business analysts focus closely on transaction details, working within the same environment to access executive-level reports. The design is intentionally developed to bridge analysis with actionable insights.
Innovative Data Delivery
Roberts described a user role-oriented delivery model instead of a one-size-fits-all reporting system. Though availability may fluctuate due to various factors, data managers provide timely access to transaction-level data for investigative purposes, executive dashboards for leadership, and large data extracts for data science teams that prefer their own tools. The goal is to ensure that each group can obtain what they need without going through lengthy processes.
Roberts emphasized that operational efficiency often comes from the frequency of use. Many users check in to the data manager multiple times a week, if not daily, to find answers that require manual queries or customized reports. This helps to minimize delays when conditions shift.
An example he provided was when an issuer needed to identify cardholders in specific areas affected by natural disasters. Since the relevant data is already organized and searchable in the Data Manager, clients can quickly compile targeted contact lists and provide essential information about nearby ATMs without waiting for batch-processing delays.
This principle also applies to revenue protection. If a cardholder’s monthly transaction count drops significantly, issuers can detect these declines early and take steps to intervene before losing valuable customers.
The Role of AI
Roberts noted that artificial intelligence (AI) is set to play a critical role in data analysis. Instead of spending hours compiling data, analysts can rely on AI tools to gather the necessary datasets and present findings in straightforward language.
The shift in timing is also noteworthy. Rather than solely relying on historical reviews to make future decisions, Visa DPS is developing systems that can send alerts within hours or even minutes of meaningful changes. In some situations, AI will automatically identify trends, flag anomalies, and suggest next steps. This evolution enables portfolios to transition from reacting to indicators to responding to initial signals and from retrospective reporting to continuous adjustments.
Roberts connects this agility directly to profitability. The Data Manager incorporates essential metrics like profitability and fraud indicators, as well as merchant-level reporting that highlights where the returns are strongest and spending may be at risk. The Visa DPS also features a goal tracker app, allowing users to set performance benchmarks and monitor progress efficiently. Future AI enhancements may even provide automated goal recommendations based on current performance relative to peers.
The risk and marketing teams are also involved in this process. The Data Manager incorporates fraud performance metrics and transactional contexts, allowing issuers to refine their controls based on actual data rather than assumptions. In terms of growth, segmentation by cardholder demographics and integrated connections to Visa Campaign Solutions help teams launch targeted campaigns and evaluate results seamlessly without needing to export sensitive data to multiple systems.
Roberts envisions deeper integrations across Visa tools and increased automation to ensure trustworthy data. “Our aim is to make data more accessible and predictable,” he explained, emphasizing the need for systems that facilitate quick responses to market changes.
Ultimately, the objective is clear: enabling decisions to be made as quickly as the transactions that drive them, resulting in less effort and better outcomes.
