As we predicted, 2019 has become the year of data for the financial services industry. As technology and trends such as artificial intelligence, the Internet of things and open banking begin to accelerate the pace of change globally, data complexity increases accordingly. Now is the time for banks to get their data houses in order. Data, after all, is the foundation which will determine which banks excel based on service, relationships, efficiency, and effectiveness, and which banks fail.
At Gradient Ascent, we deal with many clients in the financial services industry and we can’t help but notice that they face some common challenges and tough questions as they begin to launch their data-driven projects.
Three of the key challenges we see are centred on:
Also, as data grows in terms of the geographic scale it covers, being able to categorize, report, and make predictions based on that data becomes increasingly complicated. To address this, we have to look at a number of factors, including:
It can be daunting, yes, but as you approach your data-driven AI projects, here are some initial questions to ask:
As the importance and complexity of data continue to grow, getting started on the right foot will improve data readiness and overall project success.
We will provide more on how to successfully approach the data challenges in the coming weeks. Contact me directly to learn more about our data services for the financial services industry.