Jan 03 2020
Data Center

3 Tips for Managing Data in Financial Services

A solid data management strategy is key to optimizing revenue, driving down costs and delivering an excellent customer experience.

Creating a data management system at a financial institution is a bit like jumping onto a moving train. Few industries produce and store as much data as the financial sector does — from bank ledgers and customer transaction histories to channel traffic and credit scores. That’s why it’s important for financial institutions to structure their data as early as possible: Industrywide digitization will only make data management more important (and more complex) as time goes on.

Of course, it’s not enough to merely store data. Ideally, a financial institution will leverage insights from its data banks about how to better its serve customers. And a good data management strategy, paired with an appropriate platform, can drive profits for an institution while driving down existing costs.

In order to decipher patterns from data, IT and business leaders need it to be categorized it in a way that’s accessible. That means a three-pronged approach to data management: one that encompasses data storage, reporting and visualization and analytics.

Any data management strategy worth its salt must be able to keep up with rapid changes in the industry, offering financial analysts new information that can be applied to multiple use cases, Digitalist Magazine says. This means adopting adaptable methods that give organizations the ability to be agile in response to changing conditions on the ground.

Organizations should follow these three tips to create a data management strategy that serves their interests over time.

1. Firms Should Use a Unified Data Model

Once an organization standardizes its approach to collecting and sorting data across business functions, teams can start reaping the benefits. ITProPortal defines a unified data model as a system that “supports data consistency and simple access from analytics applications,” which means it connects to every tool in employees’ toolboxes, funneling actionable insights where organizations need them. A unified model will also cut down on repetition in data sets and break departments out of silos.

After an institution implements a singular strategy, stakeholders will find over time that it’s far simpler to dive into the company’s data records. For example, standardization will facilitate the process of presenting case histories, transactions and versioning. Looking back on data from past ventures will help to inform current and future business dealings as organizations refine their strategies.

2. Move All Analysis to a Single Data Platform

Even if a data management strategy looks identical across departments, team members will still need to access data in a central location. If leaders are having trouble regulating a data strategy, a platform can be a great help in defining what goes where. By making the right choice, organizations will facilitate the flexibility to deploy data on-premises, via the cloud and across hybrid environments.

When choosing a platform, it’s important to make security a top priority.

MORE FROM BIZTECH: Read how financial institutions can improve cybersecurity.

3. Build Workflows Around a Data Hub

A data hub, whether on-premises or in the cloud, will help teams fully understand their organizations’ data assets and will help them to discover new ways to manage data across the IT environment. By building the platform around a data hub, organizations can increase transparency, helping teams to become more agile and efficient.

A functional hub will govern an institution’s data, orchestrating opportunities for teams to use information as an enrichment tool for in-progress programs. When catalogs of customer behavior patterns and use cases are organized in a central hub, it will become immediately clear where teams can glean the insights they need to help them achieve the business goals of the organization.

Jirapong Manustrong/Getty Images

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