Data Analytics in the Financial Industry

Data Analytics in the Financial Industry

On June 9, House Republicans instituted a bill called the Financial Choice Act that moved to gut many of the regulations instituted under the Dodd-Frank Act of 2010. Dodd-Frank placed enormous regulatory pressure on banks in an attempt to prevent anything like the financial crisis of 2008 from happening again. In order to comply with those regulations, banks have been collecting enormous amounts of data to present to regulators and to meet regulatory standards.

Additionally, banks are collecting information on customer experience, product reception, and employee performance to ensure that the consumer facing side of their business continues to flourish. This creates an an enormous amount of information on both sides that must be cleaned, organized, processed, and analyzed. With that, 74% of financial institutions are planning or have implemented advanced, big data solutions.

Few industries collect as much data as financial institutions. Tracking transactions, investments, employee data, log data, emails, sensor data, social media feedback, and a host of other various data types contribute to the overall picture of the institutions business health. Not only must a financial institution track, analyze, and report on the mountain of structured financial data required by regulators, but must pair this information with operations, marketing, and product development to move their business forward. These requirements necessitate powerful analytics tools to both meet regulatory standards and determine the road ahead for the business.

Data analytics with artificial intelligence and machine learning can help financial institutions merge their data from proprietary enterprise sources, 3rd party sources, and even public sources whether structured or unstructured. Creating a complete overview of their data will allow financial institutions to fully comply with regulators now and in the future, while gaining true customer insights to inform emerging products, employee engagement, and customer experience. Powerful AI driven data analysis will augment the hard working analysts and data engineers who work tirelessly to keep up with the mountain of information, provide clear results to decision makers, and create the detailed reports required for compliance. AI and ML are moving analytics forward for businesses of all kinds, revealing the hidden insights locked away inside vast amounts of information.

Tim Roberson