Amyn Dhala speaks at AI World 2019 on AI-based solutions for fraud, credit risk and customer lifecycle management and shares these fintech insights

Last week, Amyn Dhala, Vice President, Global Product Management, AI Express, Mastercard, spoke at AI World in Boston. As an active and experienced AI practitioner, Amyn shared real-world insights with attendees regarding the state of AI in the fintech sector, including:

  • How a range of executives currently view the technology
  • Common use cases and challenges
  • A programmatic approach for addressing AI-related challenges

With the number of connected devices perpetually increasing (it’s estimated there will be 50 billion connected devices by 2022) and fintech organizations transitioning to offering almost entirely digital services, technology budgets are evolving. As Amyn explained to AI World attendees, the current focus across almost all verticals is on digitizing existing services to enhance customer experiences, streamline historical processes and products, and improve profitability. This leads to an exponential increase in data that organizations can derive intelligence from by leveraging AI.

Major fintech pain points and how AI can help

For fintech organizations in particular, there are major pain points that impact end-customer experiences and profitability. These include credit delinquency, customer attrition, fraud, product recommendations, automation and chatbots. In a hyper-personalized world, it’s imperative to deliver the right experience to the right customer at the right time. Amyn illustrated that AI can address these pain points by delivering a personalized experience and reducing the number of false positives.

In his presentation, Amyn highlighted the critical AI differentiators that can deliver impact and scalability to fintech organizations, namely:

  • Personalization and performance
  • Multi-access content handling
  • The ability to scale to billions of events
  • Automated model generation (including custom model generation, as off-the-shelf models don’t usually suffice)
  • Needs-specific and near real-time adaptive learning

Of the AI-related challenges that still need to be addressed across the enterprise, Amyn called out:

  • Identifying productive business cases and ensuring alignment
  • Tackling data and governance issues (in particular, the quality of the data)
  • Achieving production readiness by ensuring AI is deployed in an effective manner and able to sustain optimal performance

Success requires tailored models and continuous optimization

It’s critical that organizations assess where the technology can be best leveraged and develop an appropriate roadmap to achieve success with AI. For prioritized use cases, a tailored AI model and business case should be developed. After deployment, the model needs to be continuously optimized. As Amyn demonstrated during his presentation, AI Express solves this challenge by developing fully functional models very quickly (within six to eight weeks) that are customized to specific business situations.

Ultimately, for fintech organizations to remain relevant, they must adopt impactful and scalable AI across all of their strategic priorities. According to Amyn, AI is already fundamentally transforming fintech by enabling organizations to create new products and services. Using AI improves decision-making for existing products and processes and increases automation and operational efficiency—all of which stand to drastically improve customer experiences and organizational profitability.

To hear more from Amyn Dhala, check out his explanation of AI Express as part of our AI Innovators video series.