The rapid evolution of artificial intelligence (AI) presents unprecedented opportunities and challenges, particularly within the financial services sector.
As technology continues to advance, the importance of a multi-stakeholder approach to discussions on responsible AI has never been clearer. Such collaboration fosters a rich dialogue among various industry players, academics, governments and regulators, and wider civil society, ensuring that across the AI lifecycle diverse perspectives and broader societal impacts have been considered.
The power of collaboration
‘’Conversations on AI’’ is an event series developed last year out of a partnership between Cognizant and Northeastern University London. The event series has blossomed into a vibrant, multi-stakeholder network of over 400 individuals dedicated to exploring the intersection of AI and its human impact. The most recent event tackled the difficult question ‘how can AI responsibly transform financial services?’. The event was opened with remarks from The Lord Mayor of London, Michael Mainelli. The discussion continued with expert panellists: Sofia Zanon di Valgiurate (HSBC Office of Applied AI), Rob Garlick (Citi), Dr Yali Du (The Alan Turing Institute) and Eric Van der Kleij (Edenbase). The conversation was further enriched by host George Littlejohn (CISI) and an insightful and engaging audience.
Insights from the event
The growing potential of AI in financial services
The power of AI as an influencer of the economy comes as no surprise. Cognizant Research’ New Work, New World predicts that as many as 46% of businesses will have adopted generative AI in the next 10 years, injecting $1.043 trillion into the economy.
Several use cases highlighted during the event exemplified this message and the transformative potential of AI for financial services in particular:
- Knowledge Management: AI can significantly enhance data management and retrieval processes, streamlining access to vital information.
- Content creation and summary: Automated tools can facilitate faster and more accurate generation of reports and summaries, freeing up valuable human resources.
- Productivity enhancements for developers: AI-driven coding assistants can help developers write code more efficiently, reducing time spent on routine tasks.
- Support for compliance and financial analysis teams: By monitoring trends, spotting outliers, and tracking due diligence, AI tools can bolster compliance efforts and enhance financial analysis.
- Secure financial services: AI-enabled fraud analytics works to identify and prevent malicious intent or security breaches, keeping customer’s assets secure.
Practical lessons for driving responsible AI
While the opportunities are promising, the discussions at the event also emphasised the importance of doing this right. Here are some practical lessons shared by both our expert panel and engaged audience:
1. Develop technically robust AI tools: Technical guardrails should ensure that AI agents operate transparently and reliably, aligned with developers' goals.
2. Identify the right AI Solution: Ensure that the chosen AI solution fits the specific problem at hand, minimising the risk of inappropriate applications.
3. Understand use case risks: Recognise that risks associated with AI can vary significantly by use case. Familiarising yourself with regulatory frameworks, such as the EU's AI Act, can help assess potential risks more effectively.
4. Establish AI codes of conduct: In regions with less regulatory clarity, organisations should implement their own AI codes of conduct. Resources like ISO 42001 and the AI Risk Management Framework | NIST can provide valuable guidance.
5. Manage workforce transition: Upskill employees on how to leverage AI tools effectively while understanding associated risks. Creating a culture of risk management is vital for fostering innovation while ensuring accountability. Initiatives such as the Lord Mayor’s Ethical AI Certification offer practical strategies for cultivating this mindset.
6. Collaborate and influence: Given the interconnectedness of financial services with various industries, setting responsible standards can create a ripple effect, encouraging compliance among affected companies and promoting industry-wide accountability.
Conclusion
As AI continues to reshape the financial landscape, the importance of a multi-stakeholder approach to responsible AI cannot be overstated. By fostering collaboration, sharing knowledge, and adhering to best practices, industry players can harness the transformative potential of AI while mitigating risks and ensuring responsibility and resilience are front and centre. This proactive dialogue will pave the way for a more responsible, inclusive, and innovative future in financial services.
