Proper data management is the cornerstone of planning effective business strategies in the financial industry. However, before the digital revolution, many financial institutions had not been efficient in managing data and leveraging information to improve their services.
For a long time, banks have stored a large volume of data in siloed systems that are not capable of connecting with other platforms for data transfers. This leads to the slow and inefficient process of moving inbound and outbound data across different systems. Such poor data management is a red flag from a regulatory standpoint and ultimately results in lower customer satisfaction.
To address data management issues, banks must build a unified data foundation system that effectively reduces the time and labor required to move data from different sources. Establishing a centralized system also results in consistent and accurate data which can be accessed by bank officers instantly. In the long run, efficient inbound and outbound data services enable financial institutions to streamline their operations and maintain financial integrity for improved regulatory compliance.
To learn more about efficient data management, here are several ways banks can build solid inbound and outbound data services:
Modernize Outdated Legacy Systems
Though many banks were built on legacy IT systems, these now lack the capability and extensibility required to support analytics for large volumes of data. These systems are not equipped to perform advanced analytics to extract valuable insights that can improve banking strategies. Furthermore, outdated legacy systems are largely incompatible with innovative platforms that can instantly connect with other systems. IT departments must therefore manually extract data and transfer them into another platform, which leaves more room for data errors.
Over time, legacy systems become expensive to maintain and update. Thus, it makes better sense to invest in integrated data system solutions that easily connect and engage with other current-gen platforms. This also frees up the IT department’s time so they can focus on more important tasks. Finally, most hardware manufacturers no longer offer support for legacy products, making it imperative for banks to upgrade to the latest data systems.
Simplify Data Acquisition
Each branch in a financial institution, such as the accounting department, front office, and risk management department, all have unique data requirements. As such, IT professionals are trained to use various types of systems to perform different tasks. And for many traditional banks, most data is stored and managed in bespoke systems that often produce inconsistent analytic outputs. These systems are also designed in architectural silos that cannot connect with other systems or interpret different coding languages.
To address this issue, banks must strive to simplify their data acquisition. This can be done by investing in an integrated data system that automatically streamlines data gathered from different storage platforms. They must also have a reliable system that communicates in the same data language that maintains the analytical source for consistency. Using an effective system that integrates data also saves financial institutions a great deal of time in organizing information.
Use Systems with Pre-Built Product Integrations
Since each bank department has specific data requirements, financial institutions generally use specific software to support different tasks. And to manage smooth inbound and outbound data movement, it’s important to use compatible systems that connect and integrate with other platforms easily. This integrated data system must also support a vast majority of source types, such as XML, ASCII files, Hive, and HDFS. This kind of flexibility enables banks to combine data from different sources and blend them together to produce new insights.
Investing in new systems with pre-built product integrations helps minimize maintenance requirements. Many hardware providers also offer automatic updates for their systems as the product evolves. As a result, it reduces maintenance tasks for IT departments and allows them to focus on managing mapping extensions for the data to be used in analytical applications.
Prioritize Data Quality Management
Besides modernizing systems, financial institutions must focus on checking their data for accuracy. Before widespread digital technology, most banks encoded data manually, leaving plenty of room for human error. Once banks upgrade to a centralized integrated platform, they must enter existing data into the new system. But before doing so, they must carefully review, verify, and update the existing data for accuracy. While this process takes time, it is necessary to ensure the quality and consistency of the data. Otherwise, inconsistent and incomplete data can compromise analytic outputs and fail to deliver accurate insights.
Streamline Data Systems for Improved Regulatory Compliance
Banks face pressure from regulatory agencies to remain compliant with numerous data-related laws. Since part of compliance is improving systems for efficiency, upgrading to the latest software and hardware tools will help keep their systems updated with regulatory requirements. This will save banks from having to pay fines for noncompliance and reinforce their public image as institutions that can be relied upon.
Data is a key factor that can significantly improve financial services. Thus, it’s crucial to employ smooth inbound and outbound data services for efficient data management. Hopefully, the items mentioned above will help your bank build better inbound and outbound services. Improved data management enables financial institutions to obtain relevant insights that can enhance their strategies and further propel growth.