1)
Business strategy: Boards should consider how AI can be used to support
the bank's business strategy and goals, and how it can be integrated
into existing processes and systems, like customer service chatbots,
fraud detection, credit risk assessment or personalized service offering
2) Governance
and oversight: Banking Boards should establish clear governance
structures and processes to oversee the development and deployment of
AI, including defining roles and responsibilities, setting performance
metrics, and establishing risk management procedures. Given the dynamics
of AI and the need for constant calibration and validation of AI models
boards need to establish a frequent model oversight process.
3)
Talent and skills: AI requires specialized skills and knowledge, and
boards should ensure that the bank has the necessary talent and
resources trained in both banking and AI to develop and implement AI
initiatives.
4)
Legal and regulatory compliance: It is important for the board to
ensure that the use of AI in the banking industry complies with all
relevant laws and regulations. This includes data protection laws,
consumer protection laws, digital operational resilience act, and any
other laws that may be relevant to the use of AI in the banking
industry.
5) Data
and data privacy: The use of AI in the banking industry often involves
the collection and processing of large amounts of sensitive data. The
board should consider how this data is collected, stored, and used, and
ensure that appropriate measures are in place to protect the privacy of
customers and other stakeholders. All AI models are dependent on high
quality data. There is the risk of garbage in, garbage out. Therefore,
boards must provide framework conditions that ensure robust and high
data quality.
6)
Ethical considerations: The use of AI in the banking industry can raise
ethical concerns, such as the potential for bias in decision-making or
the impact on employment. The board should consider these ethical
concerns and ensure that the use of AI is consistent with the values and
mission of the organization.
7)
Risk management: The use of AI can introduce new risks to the banking
industry, such as the risk of biased decision-making or the risk of data
breaches. The board should consider these risks and ensure that
appropriate measures are in place to mitigate them.
8)
Transparency: It is important for the board to be transparent about the
use of AI in the banking industry and to ensure that customers and
other stakeholders are informed about how AI is being used. This may
include providing information about how decisions are made and what data
is being collected and used.
Finally, AI training for board members is recommended to make them
knowledgable about the concepts, methods, needs, challenges and risks.
