Welcome to the final part of our Credit Data Strategy blog series.
Based directly on conversations with our clients and other market participants, this special blog series will spotlight how the credit market is leveraging technology and automation to unlock greater performance. Whether your firm has already implemented a credit data strategy or is yet to begin, this series will help you benchmark your practices and offer resources and advice on how to succeed in an ever-shifting landscape.
The accelerating rate of change
Non-technologists are often surprised by the accelerating rate of change in the Artificial Intelligence field, unfamiliar with the historically convex path of such advancements. It’s natural to look backwards and use recent experience to predict what comes next, but such an approach will lead one to significantly underestimate the degree to which advanced computing will be applied to credit investing only several years from now. If anything, market participants should expect the pace of change to continue accelerating from here.
One only needs to consider how rapidly the sub-field of text summarization has emerged in recent years to consider what comes next for the broader use of AI in investment analysis. But these emerging technologies are only as good as the data that’s available to feed them. Which is why we feel so strongly that all credit businesses need to invest in a solid data foundation today to prepare for the not-too-distant future.
Given the speed at which certain changes are taking place, a failure by credit investors to leverage innovation today will put them at a significant competitive disadvantage in just a few years. This applies to all investment firms, as technology increasingly levels the playing field, reducing the traditional importance of operational size and legacy brand positioning.
"If anything, market participants should expect the pace of change to continue accelerating from here."
We have outlined herein how credit research is evolving and why all credit investors will need to implement a data-oriented model within their businesses to prevent falling behind. The benefits are numerous, both in terms of increasing quality of output and productivity in the near-term as well as preparing for further technological change soon thereafter. However, in order to achieve this, a robust credit data strategy is required, characterized by clearly defined goals, top-down empowerment, effective sourcing, and budget flexibility.
While understandably challenging, now is the time for senior management at leading investment firms to lean into this opportunity. By prioritizing innovation and committing their businesses to execute the necessary data investments, they will position their organizations for success in an increasingly dynamic credit market in the years to come.
How could a credit data strategy help your business?
Whether you have yet to develop a credit data strategy or are already deep into implementation, we can help. At Cognitive Credit, we have already guided many of the world’s leading banks and asset managers through this process.
If you would like advice on how data & automation can unlock extra efficiency and performance in your credit research operation, simply request your personal demonstration of our web application today.