EMERGING TECHNOLOGY AND POTENTIAL USE CASES

EMERGING TECHNOLOGY AND POTENTIAL USE CASES

  • Alex Ross-Wilson, Illia Simutin

 

In the fourth of our series exploring four key themes to emerge Sibos 2022, we assess how key emergent technologies might be applied to transform the payments ecosystem.


Emerging technologies continue to shape the payments market, determining how payments are designed, implemented and delivered from an operational perspective, and how customers interact with banks and payment systems. This year, Artificial Intelligence (AI) and blockchain/tokenisation (covered in another blog in this series) were joined by the metaverse as leading-edge innovations promising to reshape the industry.

 

Although these innovations enjoyed plenty of airtime during Sibos (and indeed at other recent conferences), their current and future use cases variously lie on a spectrum that runs from short-term applicability to the largely speculative.

 

Certainly, there is no significant consensus around blockchain’s use case in financial services (though it has its adherents and champions) given current concerns around scalability, efficiency and security. The metaverse, meanwhile, is a deeply nebulous concept encompassing a spectrum of technologies and a myriad of potential experiences and applications – though that also means there is everything to play for if you are prepared to jump aboard.

 

All in all, for the time being we would recommend that most market players limit their exposures to discovery investments and maintain a stringent focus on the end customer and identifying use cases that are at once practical and impactful.

 

All aboard the metaverse

 

The virtual, immersive constructs of the metaverse hold clear appeal for financial services organizations in terms of customer reach and engagement. We would highlight two categories of opportunity: a digital channel for physical economies; and a new digital ecosystem.

 

Today, the fledgling metaverse (such as it exists beyond semi-sandbox environments) is primarily viewed as a new channel for a traditional physical economy, with banks performing the same role inside and outside the metaverse – see JP Morgan's lounge in the Decentraland construct, South Korean KB Kookmin Bank’s custom metaverse branch, and HSBC’s latest metaverse initiative to “create innovative brand experiences” for new and existing customers.

 

The more intriguing scenario is if the metaverse (or metaverses) becomes the foundation for new digital ecosystems that exist entirely virtually. In such a scenario, banks would have an opportunity to leverage their brand credibility and heritage to act as trusted intermediaries, liquidity providers, identity stewards, and financial and economic advisors to facilitate the growth of such burgeoning virtual economies and spaces. Certainly, this scenario is unproven – but also promising. Businesses that recognise the value they might bring would have sufficient motivation to become pioneers on these new digital frontiers.

 

Institutions that want to stake their metaverse claim need to be exploring and understanding the potential today, or run a risk of missing out on what may potentially be billions in future digital payment and trade flows, while also ensuring they remain relevant to future generations of virtual metaverse denizens. Again, clearly much of this is presently (educated) speculation – but a focus on refining collaboration and engagement experiences, whether for customers or their own employees (in the context of internal teamwork and learning & development opportunities) and a relentless focus on measurable outcomes will be key.

 

AI – anything but artificial

 

AI, and particularly machine learning (ML), remains one of the main topics of futuristic visions among the industry. Based on current trends, financial institutions which do not incorporate AI and its enabling components into their decision-making will only have to do it so later, at a price of market share.

 

Use of ML algorithms is becoming a competitive requirement, and the long-term success of a financial services business will depend on its data sourcing and processing capabilities. To unlock the full potential of ML, financial institutions will need to explore organisational and technological enablers, and develop expertise in areas not previously considered core. On the infrastructure side, a specific set of software and hardware backbones are required for the training and deployment of ML algorithms, and these will have to be integrated into existing infrastructures.

 

This technological enablement will also have to be supported by both a robust policy component and a thorough legal assessment, as well as a more broad-based organisational shift in attitudes towards data. An example of a successful use case if the deployment of ML algorithms in anti-fraud work, which demonstrated that generated insights not only increase speed and operational efficiency but also help deliver frictionless customer experiences.

 

Conclusion

 

Emerging technology is reshaping the market by impacting existing processes and/or triggering reactions in the form of new investments and customer propositions. To capitalise on the opportunity it presents whilst also avoiding the pitfalls engendered by hype, it will be key that firms ally a deep understanding of emergent trends with a clear sense of what constitute meaningful use cases for their customers.

 

At Capco, we use next-gen technologies to transform legacy infrastructure and platforms building business resilience and efficiency for our clients to operate more competitively in an evolving marketplace. Capcos technology specialists collaborate with our digital experts and industry consultants to pioneer technologies across the entire IT value chain, striving towards making tomorrows technology a reality today.

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