The demand for data-driven technology and innovation in the financial services market is surging, as data continues to take a more important role in the operations and management side of a business. From enhancing processes and retaining customers to improving security, data-driven technology has evolved into an essential technological solution for several challenges facing the finance industry. With proven success, more finance-focused businesses have been moving towards the data industry and implementing new data-focused services wherever possible.

Financial services businesses are keen to utilise the opportunities data can offer. The main challenge that needs to be addressed, however, is that the capabilities of data depend on the quality and availability of information.

Managing data as the first step

Data management is a critical step in leading to later stages of data innovation. Financial services businesses will tend to invest in several data-driven solutions to improve compliance, risk and security. To effectively deliver and utilise the information, businesses need to ensure their data is current, accurate and reliable.

One good example of this relates to tooling systems, such as reporting or another data-focused process. These processes need customer data, but often the existing flow is not complete or possibly not entirely accurate. Quite often, as a temporary measure businesses will have their team manually update and correct any data anomalies. This can become challenging when the information from new services do not provide the anticipated results. 

Small steps can make the difference

Fortunately for financial services businesses to rectify and ensure data management is correct does not necessarily mean high budgets. Beginning with goal definition has been a proven method on improving data governance and ensuring a business can leverage data management capabilities further down the line.

Delivering value can only happen when businesses can generate meaningful insights and high quality, accurate data. To achieve this, an organisation should begin by defining their data requirements by determining specific goals. A maturity assessment enables quick bottom-up analysis of the main challenges a business faces. The relevant data management and governance services can then be created and utilised, to structurally improve the data problems a business may be facing.

How to approach data management and governance

Industry analysts recommend that financial services organisations tend to implement several actions to ensure their data-driven technology begins correctly. This includes:

Defining clear goals – define the data challenges that you intend to solve and assess any inconsistencies between finance and risk reporting

Measure the impact of data management – identify data flows from source to report to measure specific areas of data problems. Data flow analysis will reveal details to determine what data gathered from finance and risk is inconsistent.

Create a custom data governance solution – Create data management solutions that fit your business, such as data quality assessment and selected mitigation measures.

Measuring and assessing data solutions – Measurement is vital to determine success. Measuring the improvements after implementing new technology services is critical. A business should maintain consistency between finance and risk data, enabling accurate risk and finance reporting.

In today’s market, the volume and importance of data continue to increase, meaning any data-focused asset requires management and protection. Now is the time for financial services businesses to ensure data management is a top priority in their business plans.