The Key Takeaways:
1. Strategic Implementation of AI in Finance
AI’s potential in the financial industry is vast, but its successful implementation requires selecting the right use cases and starting with smaller projects to build trust. Organizations are focusing on automating value chains and enhancing productivity, primarily by assisting employees rather than directly targeting customers. Knowledge sharing and transparency in AI deployment are critical for a smooth transition and widespread adoption.
2. Overcoming Challenges and Building Trust Financial
Professionals and organizations face significant challenges, including regulatory resistance, data privacy concerns, and the need for critical thinking in navigating AI technologies. Addressing these challenges involves demystifying AI, ensuring ethical practices, and fostering a culture of bold, visionary thinking. Building trust through smaller, manageable projects and demonstrating AI’s tangible benefits can help overcome resistance and pave the way for broader acceptance.
3. Future Outlook and Skills Development
The future of AI in finance is promising, with immense potential for innovation and growth. However, success hinges on the ability of financial professionals to adapt, think critically, and embrace a mindset open to bold moves and new possibilities. Developing skills in critical thinking, ethical considerations, and a deep understanding of AI technologies will be essential for professionals to harness AI’s full potential and drive the industry forward.
Keynote: How AI is Shaping the Financial Industry of the Future
The evening kicked off with a keynote by Benedikt Höck, Partner and Head of AI at KPMG. Benedikt highlighted the transformative potential of AI, stating, “The future is already here today.” He emphasized the rapid advancements in AI technologies, noting, “AI is seeing and hearing us – we will have more intelligence and autonomous agents.”
Benedikt pointed out that while automation is becoming prevalent, the true value lies in highly automated value chains and organizations. “A lot of the stuff that we are doing will be automated,” he said, emphasizing the importance of integrating humans and robots to create a digital workforce. He concluded with an optimistic outlook: “We really have a huge journey ahead and that’s exciting.”
Despite KPMG not yet fully utilizing AI, Benedikt shared that the firm plans to roll it out across the entire organization in the coming months. Knowledge sharing will be a critical part of this transition.
When asked about the most promising AI use case in finance, Benedikt stated, “It’s about selecting the right use case.” He observed that many organizations are currently using AI to assist employees rather than customers, with a strong focus on enhancing productivity.
Keynote: Accelerating Mortgage Growth Using AI & Open Finance
Roya Borchers-Fardi, Product Area Lead at ING’s Tribe Home, delivered a keynote on leveraging AI and Open Finance to accelerate mortgage growth. She highlighted the application of DALL-E, a popular AI tool for image generation, to improve waiting times in mortgage processes.
“Right now, buying a house takes a lot of time and research for the customer and the broker,” Roya explained. By harnessing publicly available data points and open banking, AI can streamline these processes, making it easier and faster for all parties involved.
"The potential for AI is everywhere."
Presentation: AI Use Case by GFT
Jonathan Gross, Customer Engineer AI/ML at GFT, discussed the challenges and opportunities of implementing AI in highly regulated industries. He noted, “We have a huge resistance to change – it’s a black box.” Jonathan emphasized the importance of capturing and retaining company knowledge, especially as experienced employees leave.
GFT’s solution involves a speech-to-text tool that documents and captures the knowledge of their workforce, similar to using voice messages. The next step is to clean the data, build a structure, and add a chatbot to retrieve information. Jonathan advised, “Keep it simple. Don’t go for the biggest project. Build trust with smaller projects.”
Panel: AI in Finance: Buzz or Business Value?
Biggest Challenges
Roya highlighted the challenge of overcoming risk auditors, while Jonathan emphasized the need to demystify AI and demonstrate its benefits. Björn pointed out that customers often have FOMO (fear of missing out) and CEOs struggle to navigate the plethora of AI technologies available.
“Adopt a different mindset from the traditional one. Don’t be afraid to make bold moves. Have a vision and pursue it. Be detail-oriented. Prove your vision. And most importantly, have fun in what you do.”
AI’s Role in Identifying Financial Risks
Jonathan stressed the importance of understanding the customer journey and using AI for anomaly detection. Björn noted that while generative AI is gaining attention, classic AI and machine learning remain powerful tools. Roya added, “When you get the foundations right, you can integrate various types of data.”
Addressing Ethical Challenges
Björn acknowledged the significant issues of data protection and privacy with generative AI, urging companies to use available tools to safeguard data. Jonathan emphasized transparency, focusing on features like gender and race to ensure ethical AI practices. Roya remarked that machine learning, rather than generative AI, is key.
Skills for Financial Professionals
Roya encouraged professionals to adopt a bold mindset, stating, “Don’t be afraid of making bold moves. Have a vision and go for it.”
Björn stressed the importance of critical thinking and reflecting on the information presented by AI tools.
Jonathan added, "Be curious, be positive, and consider the impact on others."
Tuesday, July 2 · 6 - 8pm CEST
Source: June 10, 2024 TechQuartier from 10.Juni 2024
Image source: TechQuartier
