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Mid-size retail bank: establishing a generative AI governance model

As a mid-size retail bank operating in a rapidly evolving AI landscape, our client’s challenge was to integrate generative AI into their tech stack and operations while balancing innovation with security. We worked with their teams to help create a governance model to drive mobilisation, ensure compliance, foster ethical AI use and oversee responsible innovation across the bank. Our approach involved reviewing best practices, collaborating with key bank representatives and developing crucial governance guidelines. This strategic effort led to the creation of a model that aligned AI initiatives with the bank’s strategic goals, mitigated risks, promoted operational efficiency and fostered customer trust. The result was a flexible, scalable governance framework that empowered our client to confidently navigate the complex AI landscape, differentiating it in the market.

  • Outcome 1: Designed a tiered AI governance framework that established a scalable infrastructure that empowered employees to leverage AI, ranging from basic ChatGPT applications to advanced AI POCs, fostering an inclusive and innovative technological environment
  • Outcome 2: Developed 5 foundational governance processes to effectively and securely operationalise its AI capabilities and set up for sustainable expansion
  • Outcome 3: Delivered 3 generative AI policies around AI ethics, AI model risk management and AI transparency and disclosure

The Challenge

In the retail banking sector, the AI landscape is marked by rapid innovation, evolving regulation and a push for responsible use. Mid-size banks are at the forefront, navigating this dynamic terrain to leverage AI for enhanced customer experiences and operational efficiency, while also addressing ethical considerations and compliance requirements. Our client, a proactive mid-size retail bank, recognised the urgent need for a robust AI governance model to balance innovation with social responsibility and ensure their strategies aligned both with business objectives and societal values in this ever-evolving industry. 

Faced with the challenge of integrating generative AI into their operations, our client sought to establish a governance model that balanced innovation with security. The model’s purpose was to drive mobilisation, ensure compliance, foster ethical AI use and oversee responsible innovation. Recognising the complexity of this task, the bank’s Chief Information Officer, Chief Risk Officer, and Chief Information Security Officer turned to our team for assistance. The objective was to create and implement foundational governance, inclusive of policies and procedures, essential for embedding and effectively scaling generative AI across the organisation, while maintaining a secure and ethical framework.

The Approach

Our tailored approach involved a strategic, multi-step process to establish a generative AI governance model. Initially, we reviewed market best practices and our client’s existing documentation on generative AI governance, identifying rollout challenges. Collaborating with operational, technology and business representatives, we sought to truly understand what this new governance model would look like for our client and prioritised policies and processes. This led to the creation of: 

1. Proposed forums and roles & responsibilities: We provided an in-depth analysis of executive and expert-level governance forums, detailing participants’ purposes, areas of expertise, and roles within expert-level working sessions.

2. Organisational approach to scaling AI: We made recommendations for the optimal organisational approach to support a scalable enterprise AI capability, including suggestions for how responsibilities of key processes and roles should evolve with the scaling of AI.

3. AI discipline deep dives: We delved into AI ethics, security & privacy, AI development, AI usage & enablement and AI management, offering comprehensive insights for each.

4. Foundational governance: We provided an overview of the essential day-1 processes required to operationalise an AI capability, complete with supporting documents and key considerations.

5. AI use case governance: We outlined how governance would vary across different levels of AI use cases within the various AI disciplines.

6. Foundational policies: We drafted three foundational policies to support the implementation of the AI governance framework and activities, setting a best-practice policy baseline to enhance existing or related AI policy efforts within their information security department.

This holistic approach aimed to equip our client with a robust, scalable generative AI governance framework, tailored to their unique operational landscape and strategic goals. 

The Impact

The framework enabled our client to execute POCs, effectively navigating the bank’s risk tolerance and adhering to regulatory mandates. The generative AI governance model and policies we developed for the bank delivered significant value, including:  

• Strategic alignment: Ensuring that initiatives are now closely aligned with wider strategic objectives, enhancing focus and effectiveness.

• Risk mitigation: Reducing exposure to AI-related risks and creating resilient response methods to incidents to ensure safe practice.

• Operational excellence: Clearing guidelines and standards promoting operational efficiency in implementation and ongoing management.

• Customer trust: Instilling confidence in customers by guaranteeing ethical and responsible AI practices that improve their experiences.

The model served as a foundational baseline and guide, empowering leaders within risk to establish the necessary governance for introducing and implementing enterprise AI capabilities. This empowerment was a game-changer, providing the bank with the tools to navigate the complex AI landscape confidently. In addition, our flexible, tiered governance approach, addressing oversight, ethics, and security, ensured innovation thrived under appropriate control, setting the bank apart in the market. 

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Steve Steinberg

Steve Steinberg