How Web3 and AI are transforming finance

GenAI’s potential to improve cost and operational efficiency and enable massively customized interactions at scale is unprecedented. Image: Shutterstock

SSince the birth of ChatGPT, writing summaries from long reports or creating personalized emails has become a thing of the past for many. One year later, the ability of generative AI (GenAI) to extract and synthesize data and sentiment from large amounts of data has made complex information more accessible than ever. It is now also possible to customize his one-on-one online customer interactions at scale, from product search to purchase.

Rapid increases in operational and cost efficiency enabled by GenAI are being observed in a variety of areas, including how financial services are delivered and experienced by consumers. Rishi Ramchandani, his APAC Web3 lead at Google, says market intelligence and its ability to quickly personalize a customer’s journey presents a huge growth opportunity.

This comes at a time when the world of finance is being disrupted by another formidable force: Web3 technology, or commonly known as blockchain. At the INSEAD Future Forum, themed “How will Web3 and AI transform finance?”, practitioners will take a deep dive into how these technologies are shaping finance as we know it. Ta.

heralding the arrival of a new era

GenAI’s potential to improve cost and operational efficiency and enable mass customization interactions at scale is unprecedented, experts at the Generative AI: A Game Changer for the Future of Finance panel said. I agreed. In an increasingly uncertain commercial and regulatory environment, it helps developers and analysts understand regulatory changes and identify or automate necessary changes. For example, GenAI can distill the essentials of the Basel Framework that are relevant to your business and identify relevant parts of your product documentation and code repositories that need to be modified.

Alex Honchar, director of AI engineering and partner at Neurons Lab, says the fact that GenAI processes not only images, audio, and video, but also text, not only enables a variety of use cases but also increases comprehensiveness. It is said that it will also make a significant contribution. Indeed, beyond the tangible changes, there are also philosophical changes, including financial inclusion, says Stefano Bury, an INSEAD graduate (MBA’13D) and COO of LongHash Ventures.

Blockchain allows everyone to access financial services from anywhere. In the past, large sums of money were often trapped in financial markets due to intermediaries and other operational frictions. However, the decentralized, community-based, and owned nature of blockchain technology makes it possible to bypass traditional institutionally owned systems, along with their associated rules regarding fees, minimum transaction volumes, and operational delays.

The panel discussion “How Web3 is shaping Finance 2.0” made it clear that lower costs, speed (think instant payments) and increased accessibility are big wins for financial inclusion.

Additionally, digital assets and their underlying blockchain technology are creating new asset classes. Following in the footsteps of cryptocurrencies, real world assets such as mortgages are being tokenized. Samar Sen (INSEAD MBA’08D), senior VP and head of APAC at Talos, said digital assets such as Bitcoin can be used to hedge against inflation (like gold) or to raise capital for venture capital. It states that it may also function as an economic instrument. However, he cautioned that different use cases are at different levels of maturity and it is too early to tell which ones will be successful.

Harald Eltvedt, INSEAD alumnus (GEMBA’20J) and venture builder at SC Ventures, asked, “You can tokenize everything, but should you tokenize everything?” His answer was “probably not.”

Also read: Global cryptocurrency exchange OKX strengthens presence in India Web3

Have you arrived yet?

Like many panelists, as these relatively nascent technologies continue to evolve, Hassan Ahmed, Coinbase’s country director for Singapore, said scalability remains a challenge, primarily due to a lack of interoperability and market stability. He pointed out that.

To achieve interoperability, market participants as well as relevant stakeholders must operate using common rules, standards, and systems. It requires a common language, both literally and figuratively.

Second, market stability is a necessary ingredient for increased trust and adoption. Regulatory cooperation and joint supervision can go a long way in ensuring more stable global markets. “We are now seeing cross-border cooperation between regulatory communities, such as Europe and Singapore, Asia and Europe, the US, Singapore and Africa,” said Anton Ludenklau, head of financial services at KPMG Singapore. Liquidity reserves can be introduced as a safety net for consumer confidence and protection. There will be shocks to the system and we need to build trust and liquidity in these systems, he said.

With little standardization, market stability and regulatory certainty, global progress will only look like a patchwork. Meanwhile, pension funds and major corporations will simply sit on the sidelines.

Four steps to business transformation

Ramchandani highlighted four steps for companies to more effectively leverage GenAI’s potential. In fact, these steps can also be applied to Web3 and other new technologies.

First, identify and prioritize potential use cases. A leader must assess business needs alongside her AI capabilities, both generative and traditional. Having a realistic view of the time-to-value for each use case helps companies determine the feasibility of each use case.

Second, once priorities are identified, companies need to adopt a “data first” strategy. Build a solid AI foundation by unifying disparate datasets with strong governance. To ensure that AI models are robust and serve the purpose for which they were built, organizations need to audit both their AI models and their training data, said Lawrence Liew, director of AI innovation at AI Singapore. says. A good example is that OpenAI spends most of its resources on humans checking the model output.

Third, integrating and implementing AI solutions will only be successful if your organization is ready. Therefore, leaders must look beyond the costs and benefits of their GenAI solution and consider their organization’s AI readiness. Like most panelists, Zaid Hamza, Managing Partner at FutureLaw.ai, agreed with the need for learning and reskilling, and the associated need to balance dependence and professional judgment. He said that investing in talent not only helps companies benefit from investing in GenAI, but everyone can benefit from GenAI.

Fourth, recognize that not all AI is created equal. Test your proof of concept to identify what works before scaling your business. By better understanding how technology works and what it does, decision makers no longer have to ask, “Where can I use it?” 01 Solar founder and AI consultant LingYi Chang answered, “How good is it now?”

Integrating GenAI continues to raise questions about how to manage data. How do we make it accurate and explainable? How do we integrate existing data and applications? How do we manage costs? How do we address fraud and security? Some of the issues can be tackled at the corporate level, while others require ecosystem efforts and even regulatory intervention.

Also read: How FlexiLoans grew quickly and profitably

Where do we go from here?

From a governance and regulatory perspective, the question is how to create guardrails and ensure responsible use. Vihang Patel, an INSEAD graduate (CGM’21) and founder and CEO of Splore, says that for GenAI, auditing is most important at the base model stage, where the model is run in a controlled environment. says. It’s much harder to regulate or put up guardrails “after the fact,” he said. Therefore, the optimal timing is earlier rather than later.

Moreover, regulating GenAI requires a different approach. Current regulations tend to focus on the inputs and outputs of AI models, and regulations are based on the responsible use of model size and outputs. But beyond model size, we need to consider human responsibilities in the use of GenAI, including issues of bias.

On the Web3 front, Sen pointed out that despite the recent collapse of FTX due to the influence of other cryptocurrencies, it has actually become more secure over the past five years. He said the “good things” that came out of the recent disasters include the liquidation of fraudulent companies, increased consolidation in the industry and, more importantly, a greater understanding of the need to separate custodians and trading. emphasized. He warned that the benefits of blockchain in making financial services accessible to everyone come with an urgent need for consumers to better educate themselves.

So at what point did we “arrive”? In an ideal, abstract world, Sen predicted, transactions would occur without the need for outside intervention. In any case, there is no going back. “We’re all in this boat together and there’s nowhere to run,” Chan said.

[This article is republished courtesy of INSEAD Knowledge
http://knowledge.insead.edu, the portal to the latest business insights and views of The Business School of the World. Copyright INSEAD 2023]