Why The Financial Sector Requires Automated Data Quality Tools

Data privacy governs how organizations collect, share, store, and delete personal data. In another word, data privacy safeguards user's rights to private preferences. There are laws established to ensure compliance with data privacy - General Data Protection Regulation (GDPR) and Calfornia Consumer Privacy Act (CCPA).

Data Privacy in Banking

Today, data is fundamental to the success of almost every sector, including banking. It is needed for innovation and advancement. However, it is also keen to note that misuse, can lead to devastating losses and destabilization of systems.

Banks now have a lot of sensitive data on their customers. After the 2008 global financial crisis, regulators focused on improving transparency in financial institutions. To ensure compliance with data privacy, banks need to have a proper understanding of the data they need from the customer, especially personal data.

Benefits of automated data quality tools:

Banks are known to have an extensive collection of their customer’s personal data.  We cannot mention data privacy without having to talk about data quality. Data qualities refer to the state of being accurate, complete, consistent as well as reliable, and up to date for use in planning and influencing decision making. Here are the benefits of automated data quality tools:

  • Improve customer experience: With an automated data quality tool, banks are able to have a complete 360-degree customer view. In this way, they can profile the customers and create customized products for them based on their needs. This saves the customer time and improves their experience leading to long-term customer retention.
  • Curb Fraud: Biggest challenges faced by the banking sector are money laundering and identity thefts. The Federal Trade Commission reported 1.7 million fraud complaints in the year 2019. Automated data quality tool is monitoring this function, through these banks can monitor and single out unusual patterns that can help prevent fraud.
  • Compliance: Regulators have put in place laws and regulations on data. These encompass data quality. Failure to be compliant can result in revocation of trading licenses, punitive penalties, and court cases. The automated data quality tool can handle data ensures compliance with the said laws preventing adverse effects on the flow of business.
  • Informed decision making: With new products and innovations arising every day, banks need to have the ability to adapt to the changes easily. This means decision making should be very fast and well informed. Data is the key driver in making decisions.


This is all made possible through an automated data quality tool. Data requirements especially for banks and other financial institutions keep on evolving and becoming more stringent. 

Views: 182

Tags: dsc_enterprise_data


You need to be a member of Data Science Central to add comments!

Join Data Science Central

© 2021   TechTarget, Inc.   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service