How we help our clients
AI is revolutionising business by automating tasks, refining decisions, and extracting vital insights far quicker than the human mind. This transformative technology enhances efficiency, reduces costs, and propels organisations toward sustained success in today’s competitive landscape.
However, even though 75% of UK financial services firms are using AI1, senior executives are worried about data privacy, cybersecurity risks, regulatory compliance, model accuracy & reliability, and the AI skills gap. Where do you start with governing AI systems that are already accelerating in your business?
We believe that AI governance is simply a set of improvements to your existing governance and change lifecycle processes. It does require commitment but effective AI governance brings new opportunities for growth and efficiency. We see AI governance becoming a key differentiator in financial services firms over the next few years, as AI systems become more prevalent and commonly-used internally and by customers.
Our AI governance solutions
AI Inventory
The first step in effective AI governance is knowing what AI systems you have, what models they are using, and what datasets are required. This requires an AI inventory. We help you identify where AI is used in your organisation, what it is used for, and who uses it. This can be deployed as a dataset or a custom app. Most importantly, we embed this as BAU in your organisation.
AI Change Lifecycle
Using AI systems comes in many forms. AI system may be developed in-house, bought from vendors, created as AI agents using AI automation platforms, or used online like ChatGPT. Each of these models requires changes to existing change lifecycle and governance processes. We rapidly pinpoint what needs improving or adding in your existing change processes, giving you the confidence that AI use is governed effectively.
Embedded AI Risk
Using AI systems, whether developed in-house, bought from vendors, or online tools, brings new risks to your organisation. These risks can occur during procurement and development processes, or when using these AI systems in production. We help you understand these new risks, the changes to existing inherent risks, and embed them into your risk management framework.
AI Transparency
Senior managers often regard AI systems as “black boxes” with opaque algorithms, unclear data, and unknown risks. This feeling makes effective AI governance challenging. Our AI system deep dive breaks through these walls and gives you transparency and clarity on what the AI system is doing and the potential risks you are facing.
