Financial data quality assurance

As financial services firms turn to technology to improve efficiency and cut costs, business-critical tasks have become increasingly software dependent, and Quality Assurance has never been more important. A single error or oversight in a complex financial ecosystem can cause significant financial damages or inflict substantial regulatory fines.

However, Data Quality Assurance is often neglected, not least because standard data sourced from leading global data providers, is perceived to be, if not flawless, then without any true alternatives. But buying standard or “off-the-shelf” financial data, even from a world-class data provider, does not necessarily mean, that your data is of high quality.

Many financial services firms, when observed from the outside, can appear to have similar needs and challenges. However, when you really delve into their processes, almost every medium to large organisation is unique, and have very different needs for financial data.

Data Quality is crucial to your organisations ability to make informed decisions. When you are combining data from different sources to provide a unified view of the collected data, you open yourselves to errors and kickouts, duplicate data, and mismatched records. Of course, other data quality issues are that the data are being entered, edited, maintained, manipulated and reported on by people.

On the surface, it is obvious that data quality is about cleaning up bad data – data that are missing, incorrect or invalid in some way. But in order to ensure data are trustworthy, it is important to understand the key dimensions of data quality to assess how the data are “bad” in the first place.

7 key dimensions of data quality

There are many definitions of data quality, but data is generally considered high quality if it is “fit for purpose” – fit for its intended uses in operations, decision making, planning and reporting.

At Financial Data Solutions we operate with 7 key dimensions of data quality:

  • Accuracy
  • Completeness
  • Consistency
  • Timeliness
  • Validity
  • Uniqueness
  • Relevance

Improving data quality is much more than clearing out bad data. It is a dedicated and ongoing process to maintain the accuracy and value of the business-critical operational information.

Financial Data Solutions will assist clients in designing and implementing a Data Quality Solution that embeds data quality techniques into their processes and into their enterprise applications and data integration.

Financial Data Solutions will work with clients towards a tailored solution that enhances the data quality, saves time, eliminates errors, and adds value immediately.

Financial Data Solutions is the only financial data company of its kind – specialist advisors and one-stop facilitator of high-quality customised financial data.

Either working alongside your current/future data providers or as a single point of contact for sourcing all your financial data.

For more than 20 years, we have provided financial data solutions and services tailored to our clients’ needs – at the right time, in the right way.

In an ever-changing world, we ensure a seamless and automated import of customised, validated, cross-referenced, and accurate data – to be used throughout the organisation.