NBFI Sydney

Key takeaways

  • Rapid advances in artificial intelligence capabilities are set to boost productivity and cut costs across non-bank institutions such as asset managers and insurance firms.
  • Many companies are still in the early stages of assessing AI, with compliance and fraud processes stand-out areas gaining immediate traction.
  • The ethical issues underlying an AI rollout also need to be considered and included in an overarching AI governance framework.
  • J.P. Morgan is also using AI for payment validation screening and to automatically show insights to clients, such as cashflow analysis, when they need it.

Rapid advances in artificial intelligence capabilities are set to boost productivity and cut costs across non-bank institutions such as asset managers and insurance firms.

“We are at the beginning – there's no question,” Rebecca Engel, Director, Financial Services Industry, Microsoft, said during a panel session on AI.

The area is gaining significant attention for its potential to transform the global economy, with McKinsey estimating that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across 63 use cases it analysed1.

“We are at the beginning – there's no question.” 

Engel likened the current shift to a knowledge worker-based industrial revolution, with financial services businesses focused on three main use cases:

  • Reducing costs.
  • Improving productivity, such as back office functions and the cost to serve.
  • Boosting revenue growth.

However, many companies are still in the early stages of assessing AI, with compliance and fraud processes stand-out areas gaining immediate traction.

J.P. Morgan has been using the underlying AI-powered large language models for payment validation screening for more than two years. It also speeds up processing in other ways by reducing false positives and enabling better queue management. The result has been lower levels of fraud and a better customer experience, with account validation rejection rates cut by 15-20 per cent. J.P. Morgan is also using AI to automatically show insights to clients, such as cashflow analysis, when they need it.

Meanwhile Microsoft recently announced a partnership with risk assessment firm Moody’s to develop enhanced risk, data, analytics, research and collaboration solutions powered by generative AI2. Engel cited another example of companies using AI to analyse call centre logs to improve services.

“We’re able to analyse it to say what was the real problem and what's the solution?”

Optimize data governance capabilities to get full value from AI

Engel recommended organisations looking to incorporate AI into their business should start building up their data governance capabilities.

“Start now – make it part of your culture, appropriate to the size and maturity of your organisation. Bring it up to your board level and have a really good conversation about your parameters and risk appetite.”

The ethical issues underlying an AI rollout also need to be considered and included in an overarching AI governance framework. Microsoft has an Responsible AI Standard which addresses the design, built and testing of AI systems, while it also ensures that client data remains the property of clients.

“Your data is your data – we don’t take it and do anything else with it. That is a big question that we've had from customers.”

Microsoft has been providing leading Financial Services Industry bodies with information about AI’s risk compliance and legal implications so they can effectively help organisations move from proof of concept into production.

“We're finding at the moment that the demand to build the proof of concepts is outstripping the supply of people able to build it, and the mechanics of the organisation to deliver the change. There's a lot AI can do, but there's still a challenge incorporating it into organisations' day-to-day activities.”

Engel said AI’s rollout will transform organisations, creating new job roles that don’t yet exist, while freeing up staff to focus on higher value producing activities.

“The work that these tools will take away in the next couple of years will simply be the work that no one really wants to do,” she said. “This technology will reduce the burden of non-value producing work – that trend is just going to accelerate.”

For more information contact:
Tom Lydon, Head of Financial Institutions Group, Australia and New Zealand and Head Non-Banking Financial Institutions, APAC, J.P. Morgan
T: +613 9633 4097
e:
tom.lydon@jpmorgan.com

The future of payments: less visible but more powerful

Real-time payments and embedded finance are set to make payments even more seamless, according to Cyrus Bhathawalla, Chief Administrative Officer, Asia Pacific, Payments, J.P. Morgan.

While AI promises to lead to many new use cases, there are other payment trends that promise to create significant new value for businesses and consumers.

Perhaps the biggest is embedded finance – seamlessly integrating financial offerings such as digital interfaces, digital wallets, and loyalty apps into a much broader variety of everyday activities and services.

“A lot of the world around us is still being digitised and as we do that, embedded finance is almost guaranteed to be at the core of this transformation – because consumers don’t wake up saying ‘I want to make a payment’; instead they are engaged in a broader business transaction,” Cyrus Bhathawalla, Chief Administrative Officer, Asia Pacific, Payments, J.P. Morgan said in an interview after the NBFI Forum.

Real-time payments have been rolled out in many regions but greater speed will be required to enable more embedded finance experiences. Most real-time systems still take several seconds to process, which is too long for consumers to walk out of a brick-and-mortar shop with items that automatically debit payment.

“And we want payments to work seamlessly in the background to support these interactions. This is not a two-year play – this is our longer term vision for the future of commerce, with an ecosystem including omnichannel experiences, biometrics, and more.”

References

1.

Chui, M., Hazan, E., Roberts, R., Singla, A., Smaje, K., Sukharevsky, A., ...Zemmel, R. (2023). The economic potential of generative AI: The next productivity frontier. McKinsey & Company. Retrieved from https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#key-insights

2.

Microsoft News Center. (2023). Moody’s and Microsoft develop enhanced risk, data, analytics, research and collaboration solutions powered by Generative AI - Stories. Stories. Retrieved from https://news.microsoft.com/2023/06/29/moodys-and-microsoft-develop-enhanced-risk-data-analytics-research-and-collaboration-solutions-powered-by-generative-ai