CubeLogic Building It’s AI Strategy
CubeLogic has been looking into and working on automation, and an AI strategy this last year or so, Karl Sees of CubeLogic told me recently. The early results of this work will be actually available in version 11 released this month that will feature full automation in areas like data extraction from sources like S&P, Moody’s and other sources. But this is just the beginning, he said, and the end goal is to reduce the amount of time users spend on the solution performing manually intensive activities through automation and AI allowing users to focus on value added activities.
“Clients are innovating internally,” he said. “And they are sharing this with us in terms of what they are doing with regard to AI and automation and expectations in those areas.” Karl suggests that it isn’t about giving over decision making to machines at this point – “We are not quite there yet,” he said. “It’s more a case of looking at AI in terms of what client demand is and the feasibility of deploying it at this stage.”
Indeed, CubeLogic has a strategy and desire to leverage the technology for the benefit of clients, while recognizing that it needs to start with the foundations first, he told me. During 2025, it has been looking at adding and building in automation in terms of data acquisition and the calculation of interim results – later in 2025, it will release improvements in scoring and other models because of this foundational work. “We are now starting to move forward and look at how to leverage this technology better for clients and what is feasible via focus groups and research,” he said. “Where can we do more with less and improve the users experience and productivity.”
In a particular example, he told me that CubeLogic has been looking at the annual credit scoring process to see what can be automated, supplemented with AI and streamlined allowing users to focus more on the result – the credit score and what that means. “The idea is to strip out costs and improve the overall quality of risk management with AI,” he said. He also talked about finding ways to further automate parts of this process, for example, dealing with credit downgrades and how perhaps it may be possible to signal changes in sentiment around credit worthiness. Another area is the use of AI agents that can assist the analyst and serves up information in a more digestible way to allow the user to make decisions.
Karl says the entire initiative has the interest and oversight of Lee Campbell, CubeLogic’s CEO, who is very keen to find ways to utilize these technologies at add value, reduce cost and improve the quality of credit risk management. The results will be released incrementally as it establishes the feasibility and applicability of the technology, Karl Said.
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