Responsible AI and AI-enabled Risk Solutions

Accelerating value creation and promoting responsible AI

Greater availability of data, computing power and advanced methods are increasing the adoption of artificial intelligence (AI) across areas of risk, with the promise of improving business strategy, operations and client experiences.

In the absence of proper controls, however, adoption of AI may expose the organization to regulatory, reputational and business risks. To address these risks, we’ve developed a responsible AI framework rooted in the following principles: accountability, bias and fairness, explainability, privacy, reliability, security, sustainability, transparency, and compliance.

Additionally, we’ve developed a broad catalogue of AI-enabled risk solutions to increase performance for risk modeling with a focus on responsible AI, speed of delivery and value creation.

Challenges

• AI is a fast-evolving field requiring agility across three pillars: people, technology and process.
• The regulatory landscape is shifting quickly across regions.
• AI academics lack industry knowledge, while industry experts lack AI knowhow.

How we can help

• We’ve designed an end-to-end governance framework including enterprise level AI policies, AI solution development and validation guidelines, and other procedures in compliance with regulations.
• Our responsible AI framework includes toolkits supporting the operationalization of the AI governance framework, such as a fairness toolkit and an ongoing monitoring toolkit.
• Our team includes AI professionals, ethical and privacy specialists, governance and compliance advisors, and sector experts.

Our collaboration with technology vendors such as Microsoft Research and academia, including MIT, support our AI strategy of innovation, incubation, governance, production, monitoring and enhancing.