Data Virtualization: A Game-Changer for Banks

Data virtualization is a technology that allows organizations to access and integrate data from multiple sources without having to physically move or copy the data. This technology is increasingly being adopted by banks to help them manage their data more effectively and efficiently. In this article, we will explore the benefits of using data virtualization from a bank's perspective, with examples from different types of banks.

The challenges faced by banks in managing data

Banks are among the organizations that generate the most data. This data comes from various sources such as transactions, customer interactions, and external sources such as market data. The challenge for banks is to manage this data effectively and efficiently, ensuring that it is accurate, complete, and timely. This is not an easy task, as the data is often stored in different formats and in different locations, making it difficult to access and integrate.

The benefits of data virtualization for banks

Data virtualization offers a number of benefits for banks. Here are some of the key benefits:

• Faster response to market: Data virtualization allows banks to access and integrate data from multiple sources much faster than traditional methods. This means that banks can respond more quickly to changing business requirements and market conditions.

• Reduced costs: By using data virtualization, banks can avoid the costs of physically moving or copying data. This can result in significant cost savings, as it eliminates the need for expensive hardware and software.

• Improved data quality: Data virtualization allows banks to access and integrate data in real-time. This means that the data is always up-to-date and accurate, which can help to improve decision-making and reduce the risk of errors. The transparency in how the data are combined also provide users with clear data lineage and any calculations that happens during the data combine stage. This is aligned to the global BCBS239’s data quality expectations that most banks adhere to.

• Better customer experience: By using data virtualization, banks can access and integrate customer data from multiple sources. This can help to provide a more complete view of the customer, which can help to improve the customer experience. For example, a customer service agent can have a complete view of the customers and recent transactions and interactions all in one view to serve the customers better.

• Enhanced security: Data virtualization allows banks to control access to sensitive data and apply the control uniformly across the bank. This can help to improve security and reduce the risk of data breaches. Any changes to the access control can also be implemented quickly through the data virtualization platform.

• Data can be consumed through many channels: Banks typically has many channels for consuming data be it a data visualizer, chatbot, bank app, product channel partners etc. Data visualization can ensure the different views of data are channeled through the various outputs efficiently.

How data virtualization can be used in banks?

There are many ways in which data virtualization can be used in banks. Here are some examples from different types of banks:

Retail Bank:

A retail bank could use data virtualization to integrate customer data from different systems, such as a CRM system, a loan origination system, and a credit card system. By accessing and integrating this data in real-time, the bank could provide a more complete view of the customer, which could help to improve customer experience and enable better decision-making. For example, if a customer has a mortgage and a credit card with the bank, the bank could use data virtualization to view both accounts simultaneously, which could help the bank to identify opportunities to cross-sell additional products or services to the customer.

Wholesale Bank:

A wholesale bank could use data virtualization to integrate market data from external sources, such as market data, with internal data such as trading data or transaction data. By accessing and integrating this data in real-time, the bank could get a more complete view of market conditions, which could help traders to make more informed decisions. For example, a wholesale bank could use data virtualization to view real-time market data alongside its own trading data, which could help traders to identify trends or anomalies that could impact their trading strategies.

Investment Bank:

An investment bank could use data virtualization to integrate data from different systems, such as a research management system, a trading system, and an analytics system. By accessing and integrating this data in real-time, the bank could get a more complete view of its research and analytics capabilities, which could help to improve decision-making and enable better insights into market trends.

For example, an investment bank could use data virtualization to view real-time market data alongside its research and analytics data, which could help analysts to identify trends or anomalies that could impact their research findings. This could help to improve the accuracy of research and enable more informed investment decisions.

Asset Management:

An asset management could use data virtualization to integrate data from different systems, such as a portfolio management system, a risk management system, and a compliance system. By accessing and integrating this data in real-time, the company could get a more complete view of its portfolio and risk exposure, which could help to improve decision-making and reduce the risk of errors. For example, an asset management company could use data virtualization to view real-time portfolio data alongside its risk management data, which could help portfolio managers to identify risks and opportunities and adjust their investment strategies accordingly.

Conclusion

Data virtualization is an increasingly popular technology that offers a number of benefits for banks. By using data virtualization, banks can access and integrate data from multiple sources more efficiently, which can help to improve decision-making, reduce costs, and enhance the customer experience. There are many ways in which data virtualization can be used in banks, and solutions such as Denodo provide a powerful platform for implementing this technology. As data continues to play an increasingly important role in banking, data virtualization solutions like Denodo are likely to become even more essential for banks seeking to stay competitive and innovative in the digital age.