Artificial intelligence is rapidly reshaping how regulatory and compliance teams operate, but concerns remain around the safety of generative AI in sensitive enterprise environments.
The solution, according to Shwetha Shantharam, AVP and product head at 4CRisk.ai, lies in combining Trustworthy Gen AI with private specialised language models (SLMs).
Shantharam recently delved into what AI-powered regulatory intelligence products and solutions really need to do.
AI-powered regulatory intelligence has the potential to deliver efficiency gains and competitive advantage, but only if deployed responsibly. Products that are recognised by the AI and RegTech community as leaders are often those that incorporate both privacy and governance at their core, Shantharam explained.
Trustworthy systems stand apart through transparency, explainability and security. They provide confidence scores, evidence linking and techniques such as LIME and SHAP to demonstrate reasoning. These measures support audits and ensure regulators can trust outputs. Equally important is the governance framework, which should cover data sourcing, bias detection, fairness testing and continuous validation to maintain reliability.
Specialised language models are trained exclusively on compliance and regulatory data, making them more accurate and efficient than public large language models. They operate within organisational boundaries, preventing sensitive information from being shared externally and reducing the risk of intellectual property concerns.
Despite the sophistication of these tools, human oversight remains essential. Professionals must validate and refine AI-driven results to ensure accuracy and build trust. Ultimately, combining trustworthy AI, specialised models and expert judgement offers firms a way to future-proof their RegTech systems against the fast pace of regulatory change, Shantharam said.
For more about AI, read the full story here.
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