AI in Action: Real-World Use Cases for the Financial Services of Tomorrow

 

 

At the Singapore FinTech Festival, Industry leaders convened to discuss the transformative role of artificial intelligence in financial services, emphasising responsible adoption, innovation, and collaboration.

 

Key Highlights

 

1. Current AI Integration Across Firms

  • PayPal:
    • Focus Areas: Fraud detection, personalization, and software development.
    • Impact: Fraud losses halved during the pandemic despite a surge in transactions.
  • MasterCard:
    • Focus Areas: Fraud detection on 150 billion annual transactions, personalization through Dynamic Yield, and operational efficiency.
  • Prudential:
    • Focus Areas: Transitioning from manual processes to scalable AI-driven operations.
    • Initiative: Google Cloud AI Lab to foster innovation in insurance operations.
  • SMBC:
    • Focus Areas: AI-enabled call centers, trade finance automation, and internal tools like SMBC Gai for employee productivity.

 

2. Mitigating Risks and Fraud

  • Fraud Prevention:
    • AI Capabilities: Identifying patterns, anomaly detection, and predictive models.
    • MasterCard Example: A 12% reduction in authorized push payment fraud in the UK.
  • Generative AI Challenges:
    • Accelerated threat development cycles.
    • AI-enabled fraud as a service (e.g., on the dark web).
  • Key Strategies:
    • Proactive threat detection.
    • Leveraging partnerships for collective defense (e.g., World Economic Forum Coalition for Secure AI).

 

3. Ensuring Trust, Transparency, and Human Oversight

  • Ethical AI Frameworks:
    • Alignment with NIST and OECD principles.
    • Emphasis on fairness, privacy, explainability, and security.
  • Human in the Loop:
    • AI complements human judgment in contextual decision-making and complex problem-solving.
    • Example: MasterCard's internal risk panel evaluates AI applications before deployment.
  • Customer Trust:
    • Transparent data usage and consent practices.
    • Education on AI capabilities and limitations for employees, customers, and partners.

 

4. Safest and Most Promising AI Use Cases

  • Low-Risk Use Cases:
    • Fraud detection and prevention.
    • Internal process automation (e.g., contract scanning, policy analysis).
  • High-Value Use Cases:
    • Hyper-personalised customer experiences.
    • Enhanced claims management in insurance.
  • Innovation in Healthcare:
    • AI solutions to deliver timely, accurate health services.

 

5. Addressing Inaccuracies and Challenges

  • Generative AI Accuracy:
    • Key concern in customer interactions and real-world financial decisions.
    • SMBC’s Strategy: Joint experiments with customers to fine-tune models.
  • Experimentation and Value Creation:
    • Balanced focus on safe, high-impact use cases.
    • Upskilling teams to integrate AI seamlessly into daily operations.

 

Vision for the Future

The panel envisions a future where:

1. Financial services are hyper-personalised, safe, and invisible to customers.

2. AI complements human expertise, enhancing efficiency and innovation.

3. Collaboration across regulators, industry players, and partners fosters a secure and responsible AI ecosystem.

 

Conclusion

The panel underscored that while AI is reshaping financial services, trust, collaboration, and responsibility remain critical. By aligning innovation with customer and societal values, the industry can unlock AI’s transformative potential while safeguarding its integrity.

 

Watch Full Session

 

 

Speakers:

  • Akio Isowa, Senior Managing Executive Officer & Group Chief Digital Innovation Officer, Sumitomo Mitsui Banking Corporation (SMBC)
  • Anette Bronder, Chief Technology & Operations Officer, Prudential plc
  • Matthew Driver, Executive Vice President, Head of Services, Asia Pacific, Mastercard
  • Shaun Khalfan, Senior Vice President & Chief Information Security Officer, PayPal

 

Moderator:

  • Hongbin Jeong, Producer & Presenter, MONEY FM 89.3
 
 

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