How does data quality underpin success in a changing and disrupted banking environment?

The banking industry is currently in a state of flux. Traditional banks have to contend with new competitors unburdened by legacy technology or business models, making them far more agile and responsive. These advantages enable new entrants to offer low cost banking, new product offerings and services tailored toward changing customer needs.

To remain competitive, traditional banks must be able to make intelligent decisions on how best to serve their customers – and the crux of intelligent decision-making is quality data.

Banks are looking for new ways of doing business, and this requires an in-depth understanding of their market and customers. Adding to this pressure, there are many regulations that the banking industry must comply with. All of these challenges require data, but simply having data is not enough. To be competitive and comply, banks need quality data that is accessible and can be trusted.

Poor data quality leads to errors in decision making, which can be costly.

Incorrectly marketed products, for instance, will see poor uptake at best, and at worst can actually cause customer attrition. Accurate customer segmentation can also improve customer satisfaction, since risk profiling can be completed more accurately, and therefore customers can be offered lower interest rates and better service offerings.

Increasingly, experts agree that the accuracy of advanced analytics capabilities such as machine learning, artificial intelligence and big data are heavily dependent on the quality of the raw material – data. As traditional banks make choices that will allow them to compete with newer entrants their ability to leverage quality information could be their game changer.

The quality of data is also critical for compliance reasons.

For anti-money laundering (AML) purposes, for example, you need to be able to verify information, trace transactions and so on, which requires accurate and accessible information. The accuracy of risk calculations, as regulated by the Basel Committee on Banking Supervision’s standard number 239 (BCBS 239) must also be verifiable and impacts the amount of capital a bank must hold in reserve.