Helping you make sense of going Cashless | Best-selling author of "Cashless" and "Innovation Lab Excellence" | Consultant | Speaker | Top media source on China's CBDC, the digital yuan | China AI and tech

As a best-selling author and consultant, I combine my passion for fintech, AI, and innovation with my extensive experience in the banking industry and the Asian market. I wrote two No. 1 international bestsellers, "Cashless: China's Digital Currency Revolution" and "Innovation Lab Excellence," that provide insights, strategies, and practical solutions for the digital transformation of the financial sector. I have also been a top media source and speaker on China's digital yuan and mobile payments, sharing my firsthand knowledge and analysis of the world's most advanced cashless society.

With over 25 years of experience in risk management, structured credit, and debt financing, I deeply understand fintech and AI's challenges and opportunities for the banking industry. I have worked with start-ups and established insurance and asset management players, helping them navigate the uncharted waters of the latest cognitive, AI, blockchain, and analytic technologies. I have also led and contributed to multiple innovation labs and projects across Asia, applying the latest IBM technologies to real-world problems our banking clients face. I am a tireless evangelist for using technology to democratize access to financial markets and to enhance customer experience and value.

Richard Turrin

Accenture sees six trends that are rewriting banking’s future and contributing to “unconstrained banking,” where digital assets, new business models, and accelerated decision-making enable banks to do more than ever if they’re fast enough.

I give tremendous credit to Accenture for the best banking trends report I’ve seen so far this year!

Accenture backs up every trend with statistics that are designed to make even the most conservative banker sit bolt upright in panic.

Whether banks can move fast enough is the question, and Accenture’s advice on “what to do” is, on occasion, insipid and doesn’t do justice to the magnitude of the effort required. 

My take is that banks are in trouble. 

Banks are universally recognized as poor technology adopters, and virtually every one of these six requires banks to “move fast and break things.” 

When is the last time you saw a bank do that? 

While a few of these trends might be plausible for a bank to manage, it’s hard to imagine all but a few of the most tech-adroit running meaningful programs in all six! 

That leaves us with only digital money, agentic AI, and legacy tech as the three that banks will absolutely be forced to deal with in 2026. 

These six read like a death sentence for slow banks. 

Can they pull it off before running out of time?

👉 The Top Six

1️⃣ Dumb money gets smarter 
Adopting stablecoins, CBDC, and tokenized deposits.

2️⃣ Banking everywhere it matters 
GenAI assistants.

3️⃣ Agentic AI shatters traditional capacity barriers
Digital human-agent teams

4️⃣ The high cost of low cost 
Upgrade legacy tech.

5️⃣ Risk: Seeing the big picture beyond the pixels  
Integrated risk management. (Yawn, I read this every other year.) 

6️⃣ The battle for the balance sheet intensifies 
The very real threat from fintech, stablecoin, and private credit.


♻️Repost to share this great bank trends report
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The Top 6 Tech Bank Trends – If They Don't Run Out of Time

🚨 2025 Top 10 — No. 1 🚨 Mastering AI Agents: A comprehensive guide for evaluating AI agents

Want to learn how to build AI agents that tell the truth? Read on to learn more about 2025's hottest topic from a great e-book! 

👉Why this report is No. 1, and matters in 2026:

↳ Learning about AI Agents is your No. 1 priority in 2026!
↳ This eBook is a solid read for beginners and more advanced practitioners.
↳ Save this post for future reference.  What is stopping you from diving in?
↳ I'm back from holiday and writing NEW content tomorrow!!

From the author: 

"This e-book aims to be your go-to guide for all things AI agents. If you’re a leader looking to guide your company to build successful agentic applications, this e-book can serve as a great guide to get you started. 

We also explore approaches to measuring how well your AI agents perform, as well as common pitfalls you may encounter when designing, measuring, and improving them.

We hope this book will be a great stepping stone in your journey to build trustworthy agentic systems."

👉The book is divided into five chapters:

🔹 Chapter 1 introduces AI agents, their optimal applications, and scenarios where they might be excessive. It covers various agent types and includes three real-world use cases
to illustrate their potential.

🔹 Chapter 2 details three frameworks—LangGraph, Autogen, and CrewAI—with evaluation criteria to help choose the best fit. It ends with case studies of companies using these
frameworks for specific AI tasks.

🔹 Chapter 3 explores the evaluation of an AI agent through a step-by-step example of a finance research agent.

🔹 Chapter 4 explores how to measure agent performance across systems, task completion, quality control, and tool interaction, supported by five detailed use cases.

🔹 Chapter 5 addresses why many AI agents fail and offers practical solutions for successful AI deployment.

♻️Repost to share this important read on AI Agents
#Fintech, #AI, and Tech at the speed of Asia and China.

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Mastering AI Agents eBook

🚨 2025 Top 10 — No. 2 🚨  The Future of Mobile Banking: The Top 18 Trends for 2025

This is a page-turner and fun read that will help show you the killer features your mobile banking app should have now. 

👉Why this report is No. 2, and matters in 2026:

↳ The real examples in this report are a great way for banks to focus on what is possible in 2026!
↳ Banks need more than excuses when confronted with features that are real and available elsewhere. 
↳ What is stopping your bank from offering these cutting-edge features, and are any of them enough to make you switch? 

What makes this report such a page-turner is that it includes two real examples currently in production for each of the 18 trends. 

This report isn't about daydreaming about what we might have in the future, but rather demonstrates what we should have and can have if more banks cared about mobile users.

What bothers me most after reading this is that I'm paying several banks for their services, and the apps they force me to use are outdated junk! 

It isn't just me who feels that way, 69% of users think their bank app lags behind!

👉 Why mobile banking matters: 

🔹 3.8 billion users will rely on mobile banking in 2025.

🔹 62% of consumers use banking apps daily.

🔹 78% of users log on to banking apps at least once a week.

🔹 86% of users now prefer a single app to handle everything from managing loans and tracking expenses to booking travel and entertainment.

🔹 53% of consumers report that mobile banking increases their financial awareness. Younger generations, particularly Gen Z and Millennials, are leading adopters of features like credit monitoring, budgeting, and savings tools.

🔹 64% of consumers research a bank's tech offerings before committing to services.

Will reports like this make your bank act and update its app? 

♻️Repost to share this stunning report on what is possible in banking apps now! 
#Fintech, #AI, and Tech at the speed of Asia and China.

The Future of Mobile Banking

🚨Top 2026 Trends, No. 3🚨: Tokenization will be big in 2026, JP Morgan recently launched its first tokenized money market fund (MMF), “MONY” on the public Ethereum blockchain in what is likely to be a model for others to follow. 

What makes this noteworthy is that JPM is the first of the largest systemically critical banks to issue tokenized funds, meaning more will follow. 

JPM follows asset managers BlackRock, Franklin Templeton, and Fidelity in issuing MMFs. 

MONY can be purchased only by institutional investors with USDC, and offers faster settlement times, around-the-clock trading, and real-time visibility into ownership.

↳ The trend is clear: the dollar has been tokenized through stablecoins, and assets will soon follow. 

↳Tokenization of “real world assets” (RWAs) has grown to $19 billion from $5 billion in a year, according to the more optimistic views of crypto proponent, RWA.xyz data.  

↳Estimates of the future potential of RWA tokenization range from McKinsey’s low of $2 trillion to “the sky is the limit.”  

What is clear is that this transition will not happen overnight, with the need to adapt tokenization to meet securities regulations being the most pressing issue.  

The Broadridge Tokenization Survey earlier this year showed how, among early tokenization adopters, 65% fear regulatory risk, and among future adopters rises to a lofty 78%. (below)

Tokenization also faces another problem in that it impacts the profits of investment banks, broker-dealers, and asset servicers. (below) 

No matter how good tokenization is from a technical perspective, expecting these institutions to welcome blowing up their existing business model is a stretch.

Still, the trend towards tokenization is inevitable, and while it might take longer than we want, it will become very real in 2026. 

♻️Repost to share this great read on tokenization!
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JPM Shows How Tokenization Is Going Mainstream in 2026

Quantum computers are coming — and within the next decade, they could break the public-key encryption (RSA, ECC) protecting bank transactions, crypto, and more.

Citigroup calls it a trillion-dollar threat — and they’re not exaggerating.

The real danger: “Q-Day” (when quantum breaks current crypto) and “Harvest Now, Decrypt Later” attacks — adversaries are already stealing encrypted data today for future decryption.

Long-shelf-life data is most at risk: SSNs, biometrics, medical records, IP, and blockchain-exposed crypto addresses (25% of Bitcoin, 65%+ of Ethereum vulnerable).

HNDL makes data leaked onto the dark web today, which may not make front-page news, damaging in the future. 

We’ve heard quantum warnings for years — but experts now flag the next 10 years as high-risk. 

The scale is so massive (economic, geopolitical, even ideological for crypto) that ignoring it is no longer an option.

NIST-approved post-quantum cryptography (PQC) is ready — but it demands huge industry migration.

Citi urges banks: inventory crypto exposure, prioritize critical systems, and start the long migration now.

The question: With AI already stressing institutions, will finance find the bandwidth for quantum readiness?

♻️Repost to share this great read on quantum
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The Trillion-Dollar Quantum Threat to Banks and Crypto 

Asian banks are making faster progress toward the use of agentic/multi-agent systems in operations than banks in the West, which are still focused on siloed pilots.

Leading Asian banks, the top 10% of AI users, are achieving 30-50% efficiency gains and 2-3x productivity uplifts through agentic AI, beating global peers. 

“Banks in Asia find themselves at an AI inflection point. They have a window of opportunity to pick up the pace of their transformations and to create distance from peers that may be slower to recognize and seize this moment.”

Asia’s banks are trying to widen the “AI-divide” with their competition to drive efficiency and increase revenue using AI. 

Why the focus on operations instead of sexy front-office use-cases?

↳ Approximately 75% of GenAI’s economic potential comes from just four functions, customer operations, marketing & sales, software engineering, and R&D. 

↳ End-to-end operations represent an estimated 60–70% of a bank’s overall cost base, making operational transformation through AI (especially agentic AI) the biggest potential value unlock in banking — far more disruptive than other functions

↳ McKinsey’s latest Global Banking Annual Review 2025 estimates that AI could bring gross reductions of 15 to 20% of a bank’s entire cost base

These gains will not be easily won due to regulatory complexity, legacy stacks, and institutional inertia that inhibit AI deployment. 

Another factor is that in parts of Asia, the cheaper cost of labor has historically prevented many banks from pursuing tech-enabled transformations of operations.

This is why Agentic AI, with its human-in-the-loop requirement, allows Asian banks’ larger teams, often deployed in repetitive, high-volume tasks, to be redeployed to higher-value work.

That said, Asia’s AI frontrunners, like DBS in Singapore with GenAI assistants, are pushing boundaries and showing the region’s banks significant improvements in frontline productivity, KYC/AML transformation, and end-to-end process redesign.

Asia’s banks are ripe for AI transformation, and their fast actions will likely make them models for the West to follow. 

♻️Repost to share how Asian banks are leading on AI!
#Fintech, #AI, and Tech at the speed of Asia and China.

Asian Banks Lead Agentic AI Surge Compared to West

Deloitte sees five major trends in payments for 2026.  How many of the five do you think will make the cut?  

My take is that a few look strong, but always the skeptic, I can't see some of them going big in 2026.

The Five Trends:

1️⃣ Regulation meets innovation: Stablecoin enables seamless global payments

Stablecoins are still not fit for mass adoption. Banks need serious infrastructure changes for them to be used in wholesale or retail payments. And while some may argue that banks aren’t necessary for retail payments, the only way they will go mainstream is if banks are fully onboard. I agree that they'll be big in 2026 but not mainstream.  Note that I like how Deloitte acknowledges that on major transfer corridors, stablecoins offer little benefit.  

2️⃣ Mandates in motion: Speed is the new standard
  
Deloitte is correct, real-time payments are the future, but the US’s FedNow is late to the party and doesn’t deliver. FedNow payments are 100% bank controlled, unlike fast payment systems in Brazil, India, and China. It processed a mere $853B in 2025 compared to card’s $13T! I don’t expect FedNow to even dent cards in 2026. It would cost banks too much!  

3️⃣ Beyond compliance: Turning data standards into competitive advantage

ISO 20022 is great messaging tech and means that reports of SWIFT’s demise at the hands of stablecoins are way too premature. With global adoption, it will reduce the cost and time for cross-border payments at a time when stablecoins are vying to make their mark. It’s the tech behind FedNow, Singapore’s PayNow, and Australia’s NPP.   And it helps banks with AML/KYC.

4️⃣ Autonomous payments: Agentic AI is reshaping the role of humans in finance 

Yes, autonomous payments are coming, but I can’t square people outside of Silicon Valley using them with the US having one of the lower global scores in AI trust. Let’s face it, if Americans don’t trust AI, will they let it spend their money? I’m willing to be wrong on this, but tech is way ahead of citizens on this one.  Big in 2026?  I'm not buying it. 

5️⃣ AI vs. AI: AI-powered fraud meets real-time defenses

So ask yourself, who is more innovative, banks or criminals? This is why banks will always be a half-step behind the crooks. New tech will certainly help banks reduce losses and will bring the curve down, but this is a game without end, and banks will always be playing catch-up. 

👉Which Didn't Make the Cut?

By my standards, real-time payments with FedNow and autonomous payments don't yet make the cut!   

FedNow adoption is still low, and autonomous payments still have major trust hurdles to clear.  

So that's 2 out of 5 that I don't see going bigtime in 2026! 

Tell me why I'm wrong!

♻️Repost with your thoughts
#Fintech, #AI, and Tech at the speed of Asia and China.

Five trends in payments: How many make the cut?

“Sovereign AI” has become a strategic imperative. Nations want to cut dependence on foreign tech, protect national interests, and stay competitive in the AI race.

But here’s the reality: AI is the new oil — no country can afford to ignore it. 

Yet full “build-it-yourself” sovereignty is a myth for most. The US and China already control ~65% of global AI investment.

Chips, LLMs, infrastructure — they come from somewhere. A rigid go-it-alone policy is unrealistic when the resources are concentrated in just two powers.

The WEF offers a smarter path: prioritize strategic control and resilience over total self-sufficiency. 

Quote from WEF:
“Success in the AI era will be determined not by isolation, but by strategic interdependence – balancing domestic investment in key AI infrastructure with international collaboration.”

↳ This pragmatic approach helps nations avoid being forced to pick sides between the US and China. 

↳ It wisely promotes interoperable systems to dodge vendor lock-in. Run Chinese models on US servers (or vice versa) if it makes sense. 

↳Use “digital embassies” for data sovereignty.

No country — not even the US or China — can own the entire AI value chain. 

The winners will control partnerships, focus on adoption, and stay ecosystem-agnostic.  

Nations like India, Singapore, and the UAE featured in the report have winning formulas. 

That’s how you capture AI’s economic value and close the gap between AI makers and AI takers.

What’s your take? Is full AI sovereignty realistic, or is smart interdependence the only viable path forward?

♻️Repost to share this great read on AI sovereignty
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Sovereign AI: Go It Alone Means Fall Behind

🚨Top 2026 Trends, No. 4:🚨 Strong AI Governance Will Become The Norm — But Only After a Meltdown Forces Companies to Act

AI Governance will become a hot-button issue in 2026 because a global brand will experience an AI meltdown, triggering bad headlines, an apology from the CEO, and public questions about governance.

No one should be surprised that AI governance will be a key trend for 2026 when it is on the evening news.  

The paradox is that IBM shows how governance is not a hindrance to AI deployment but an accelerant! 

IBM’s survey of 1,000 global senior business and technology leaders showed that:

↳executives credited more than a quarter (27%) of their efficiency gains to strong governance. 

↳companies that invest more in AI ethics report 34% higher profit from AI as well as faster launches and stronger security.

These results show that the common belief that AI governance impedes the development of AI or is a mere “check-the-box” compliance issue is simply false.

The problem, however, is that while IBM shows governance accelerates AI development, the majority of surveys show that companies are ill-prepared for managing AI:

↳ Less than 1% of Firms Build Responsible AI (Sept 2025)

↳ 72% of organizations using AI report that their CEO is not responsible for overseeing AI governance and that 83% of boards do NOT oversee AI governance. (March 2025)

↳ Only 23% of organizations surveyed said they were highly prepared for “GenAI Risk and Governance” (August 2025)

I expect 2026 to be the year when AI governance lands front and center in front of every major company.  

Sadly, it will take an epic meltdown and a global news event to do so. 

♻️Repost to share this important read on AI governance.
#Fintech, #AI, and Tech at the speed of Asia and China.

AI Governance Will Need a Meltdown to Be Taken Seriously

One in six people now uses AI daily, while 6.8 billion remain left behind in the widening global divide as global adoption of GenAI tools reached 16.3% of the world’s population, and the Global South falls further behind.

Microsoft’s latest report on AI diffusion confirms my call last week: the AI divide is the No. 1 trend for 2026. (see link below)

Microsoft’s “telemetry” shows that AI adoption in the Global North grew almost twice as fast as in the Global South, widening the gap from 9.8 to 10.6 percentage points. 

The AI gap is growing, and AI’s benefits are not expanding equally among nations, companies, and people.

↳ The world leaders are the UAE and Singapore, treat AI as a national priority with build-outs of digital infrastructure, regulatory assistance, and policies that integrate AI into daily life. 

↳ The US dropped from 23rd to 24th place, reflecting the fact that a smaller proportion of the US population uses AI compared to smaller nations.

↳ The US’s low adoption rate also tracks with AI trust; only 32% of Americans trust AI, compared to 67% in the UAE.

I’ve long argued that Chinese open-source models would bridge the gap for developing nations priced out of Silicon Valley subscriptions.

↳ Microsoft, agrees: “DeepSeek removed both financial and technical barriers that limit access to advanced AI.” 

↳ DeepSeek’s surge is most striking in Africa, where usage is estimated 2–4× higher than in other regions — reaching millions who otherwise would have zero access.

Simply put, if people cannot afford AI, they can’t use it! 

Whatever side of the geopolitical US-China divide you fall on, you have to give DeepSeek credit where it’s due: 

DeepSeek is delivering AI to the underserved.

Never forget that OpenAI was at its start designed to be open-source, and Sam Altman is clear that OpenAI is on the ‘wrong side of history.’ 

What do you think — will open-source AI narrow the divide, or will it widen further?


♻️Repost to share this great read on the AI-divide
#Fintech, #AI, and Tech at the speed of Asia and China.

AI Divide: North-South Gap Widens – 6.8B Left Behind

Weekend Read:  300,000 voices across 20 countries show that people feel more stretched, less healthy, and less confident about the future than they did a few years ago.

This stunning report by Oliver Wyman is my best Weekend Read in ages, as it affects every one of us who feels stuck in a treadmill of "more striving, less thriving."

For fintech and AI lovers, go straight to Chapter 3, page 50 for the chapter on AI investing with some shocking revelations:

-In two years, the share of people using AI for investing has jumped by nearly a third, to 44%. 

-Those confident they can outperform advisers are nearly 50% likelier to use AI for investing and financial planning. 

-Even as AI use has climbed, interest in letting AI invest automatically has fallen from 41% to 32%. Most see the technology as a co-pilot, not an autopilot.

-65% of middle to high income earners say they "can get better returns on their own than with a financial adviser."

👉This report offers so much more than AI in investing. It covers the big trends that are making us feel worse, not better.  

It also shows how the forces below are all reinforcing one another and, frankly, making everyone miserable: 

↳ We value achieving, caring, and being healthy more — yet we feel worse. 

People report feeling 9% worse physically and mentally than a few years ago. The pattern is “more striving, less thriving.” 

↳We turn to community, each other, and AI when the health system falls short. 

Quality-of-life indicators are at record highs, but people report feeling worse mentally and physically than a few years ago. Yet the pursuit of stability resembles a perpetual sprint: Everyone is running harder just to stay where they are.

↳We want fulfillment at work, but we’re settling for less — and slowing organizations down. 

 Employees are delivering “just enough,” and quietly draining momentum.

↳We’ve stopped forgiving bad experiences as consumers. 

 “Very right” has become the baseline expectation: 64% will dump a brand after a single poor experience.

↳We dream of never needing a paycheck again. 

Financial independence is now the fastest-growing unmet need, rising to 41% from 32% in 2022. Pressure to “make money to feel successful” has nearly doubled (+80%). 

↳We are the last generation to work only with humans. 

Two-thirds of employees (67%) already interact with AI in “human-like” ways and 28% prefer an AI manager over a human one. 

↳We’re leading through constant disruption and a fractured workforce. 

 51% say leadership models are outdated, and the share citing “subpar leadership” as a top dissatisfaction has jumped nearly 60% since 2023. 

Kudos to principle author Ana Kreacic and team! 

♻️Repost to share this report that shows why we all feel the same stress!
#Fintech, #AI, and Tech at the speed of Asia and China.

AI reshapes our world as more are striving not thriving

Boldly declaring that “the future is onchain” Dfns and BCG turn back the clock to blockchain’s boom year of 2017, where ICOs ruled, and blockchain was the solution to every problem.  

Let me state from the beginning that blockchain is great tech and that it has an important future in banking, payments, and securities.  

Even the ever-so-staid New York Stock Exchange is tokenizing securities following the US dollar going on-chain with stablecoins.

So yes, institutional adoption of blockchain will be big in 2026, and it is very much a “transformational” technology. 

That said, it is a stretch to say that crypto, which the paper innocently refers to as “blockchain native” firms, will:  

1) Disrupt tradfi if they don’t transition to “on-chain banks” or,

2) Provide the tech to rebuild a bank’s tech stack.

Crypto firms still have a long way to go in the trust department before they replace incumbents.   

Similarly, their ability to rebuild a bank's admittedly ancient core systems is seriously in doubt. 

The paper suggests that blockchain tech is unto itself, sufficient for crypto firms to overcome the tremendous societal momentum banks have in their favor. 

This is wishful thinking, especially given crypto’s checkered history and lack of integration into people’s daily lives.  

Has anyone you know used BTC or stablecoins to buy groceries or a car recently?  

I don’t doubt that we will be using stablecoins sometime soon, and banks will adapt; they have no choice. 

But this notion that they must go on-chain or die off is out of 2017, when articles were actually written stating that blockchain may help cure cancer.  

Can I interest you in an ICO?

Banks Must Go On-Chain or Die: The 2017 Boom is Back

🚨Top 2026 Trends, No. 1🚨: AI Inequality and Why APAC Is the Ultimate AI Testing Ground 

While we accept that banks and companies will rise and fall based on their AI capabilities, do we accept that nations, too, will face a similar fate, rising and falling with access to AI, the new “oil” fueling growth? 

AI is the world’s next essential infrastructure, like power, roads, and schools, with big upsides and the ever-present risk of falling behind.  

That’s why it is No. 1 on the list for the Top Trends of 2026! 

Access to AI will be crucial, and APAC will be ground zero for AI implementation. 

Why APAC?  

APAC’s 200x gap between the richest and poorest nations will make it a key testing ground for AI.

AI will be abundant in rich nations, with a gap that can hopefully be closed by deliberate diffusion to poorer nations.  

Add to that reasonably good connectivity, high trust in AI, and a broad diversity from island nations to AI juggernauts like China, makes it a natural front in the battle against AI inequality. 

But here’s the wild card.

So far, the expectation from the West is that nations and peoples without AI access will simply sit it out and wait patiently as the “AI Race” passes them by.  

This is, at best, naive and, at worst, ignores the urgent needs of billions without access.

Developing nations, particularly those in APAC, with generally good connectivity, unlike those in Africa, will not sit it out on the sidelines.  

They won’t watch while AI helps to transform education, healthcare, and agricultural management for others.

They will reach out for AI wherever they find it, and this leads us inevitably to the geopolitical and philosophical battle between China and the US over open-source AI access.

China’s AI is generally open-source and available to all, while Silicon Valley’s subscription model, used to generate revenue for massive data center expansion, largely bypasses developing nations. 

Even Sam Altman believes OpenAI has been “on the wrong side of history” when it comes to open-sourcing its technologies. 

Putting people first by enabling women, men, and children in the most vulnerable or remote communities to be empowered by the best that human achievement has to offer through AI is unstoppable. 

How it plays out in APAC will be a key feature of 2026 that we should all watch carefully as the “Next Great Divergence” plays out.

♻️Repost to share this Top Trend for 2026!
#Fintech, #AI, and Tech at the speed of Asia and China.

AI Inequality: APAC is the Ultimate Testing Ground

Weekend Read:  2026: The Year AI Transforms Jobs Forever – Supercharged, Displaced, Co-Piloted or Stalled?

The WEF looks at the biggest question facing society in 2026: the future of jobs as AI transforms and displaces them. 

The Four Potential Scenarios for jobs will be:

1️⃣ Supercharged Progress:
Exponential Al breakthroughs reshape industries, business models and workflows. Productivity soars and innovation flourishes. Widespread Al readiness allows people to harness the "agentic leap."  

2️⃣ The Age of Displacement: 
Exponential Al advancement outpaces the capacity of the workforce to adapt. Businesses race to automate as a stopgap, displacing workers faster than education and reskilling systems can respond.

3️⃣ Co-Pilot Economy: 
Gradual Al progress and availability of Al-ready skillsets shift the focus towards augmentation rather than mass automation. The Al hype of the 2020s has given way to pragmatic integration: most industries see incremental transformation as human-Al teams reshape value chains.

4️⃣ Stalled Progress: 
Steady Al progress meets a workforce lacking critical skills. Productivity growth is patchy, and businesses lean on automation to backfill scarce talent. Gains concentrate within businesses and geographies with Al expertise, while others face eroding competitiveness.

Read the “No-Regret” strategies to prepare for all of these potentialities on page 4!

Which of the four scenarios do you think will happen? 

My take?  The co-pilot economy mixed with stalling!  

I see the AI divide causing a big stall ahead. 

Am I too pessimistic?  

♻️Repost to share this great read on the future of jobs and AI!
#Fintech, #AI, and Tech at the speed of Asia and China.

2026: The Year AI Transforms Jobs Forever — 4 Scenarios!

IBM, with a practical guide on how to realize agentic AI ROI, that doesn’t just look at the barriers to attaining it, but asks the fundamental question: How do you define ROI?

2026 will be a make-or-break year for agentic AI, with users worldwide searching for its long-promised returns. 

IBM suggests that these users widen their search and acknowledge that agentic AI’s ROI should have many components beyond the one or two usually used. 

While the number one priority for most users is revenue growth, IBM prudently suggests considering productivity gains, employee and customer satisfaction, and cost reduction, along with special user-defined KPIs. 

IBM is on target, and the problem with the majority of surveys we saw on agentic AI returns in 2025 was that they tended to rely on revenue growth as the sole measure of return. 

The over-reliance on revenue in surveys and business has a simple origin. 

 It is a quantitative metric, easy to put on a questionnaire, and is easier to assess than more subtle measures like customer satisfaction or custom KPIs.

The problem is that by focusing on revenue, we are undercounting agentic AI’s potential benefits within the organization.

For example, an agentic AI that increases customer satisfaction and keeps bank customers from switching banks may not provide a revenue boost, but instead, prevents a fall. 

This is a problem that AI shares with innovation projects, where it is common to define new measures or KPIs to match the specifics of the innovation to judge its value.

IBM is one of the few to address this problem in this report and deserves credit for asking agentic AI users to look harder and wider for return.

This isn’t to say dollars are the wrong metric for agentic AI ROI, but they most definitely shouldn’t be the only metric. 

♻️Repost to share this great read on agentic AI ROI
#Fintech, #AI, and Tech at the speed of Asia and China.

How do you define ROI?  IBM says look more broadly.

Deloitte's latest report reveals a massive shift: AI tokens are driving enterprise IT budgets up by 20%+, replacing predictable SaaS pricing with volatile, usage-based GenAI costs.

↳ AI is now the fastest-growing corporate tech expense — some firms report it consuming up to 50% of IT budgets.

↳ ROI is lagging badly: only 28% of finance leaders see clear value, and half expect 3+ years to break even.

↳ Token spend is unpredictable — scales with model complexity, prompt length, reasoning steps, and infrastructure costs (high-bandwidth memory, storage, electricity).

The only real cost control? Open-source AI models — free to use, self-hosted, with data sovereignty benefits.  

Running an "AI factory" with a mix of open-source and other models is the ultimate cost control for larger organizations.  

Linux Foundation: 89% of orgs already use open source in AI stacks; McKinsey: ~50%.

Watch as Silicon Valley’s trillion-dollar data center bet just got riskier if open source dominates.

Key takeaways for banking & fintech:

↳ Token usage explodes unpredictably — no more fixed seats
↳ Governance is lagging — shadow spend is real
↳ Budget shock incoming — controls are non-negotiable
↳ Winners act now: track tokens, optimize prompts, negotiate volumes, build budgets
↳ Open-source AI is essential for cost reduction

Token economics demand active financial discipline, just like cloud spend did 10 years ago, and a hard look at using open-source AI. 

Drop a comment — curious how you're navigating this shift.

♻️Repost to share this great read on AI tokens! 
#Fintech, #AI, and Tech at the speed of Asia and China.

AI Tokens: The New Currency of Enterprise AI

The digital euro’s parliamentary approval is all but assured following Trump’s threat to EU sovereignty over Greenland, which reinforced the ECB’s consistent calls for the digital euro to bring “monetary sovereignty” to the EU.  

A few days ago, ECB Executive Board member Piero Cipollone stated the crux of the problem, pointing out that US companies like Visa, Mastercard, and PayPal own “critical parts” of the global financial infrastructure and “can theoretically pull the plug on us.”

Comments like Cipollone’s may sound alarmist at first glance, but real-world events show his concerns are far from unfounded.

Nicolas Guillou is a French judge at the ICC in The Hague, and is now under U.S. sanctions for authorizing arrest warrants against Prime Minister Netanyahu and former defence minister Gallant for war crimes in Gaza.

As a result of these sanctions, he can no longer use Visa, Mastercard, or Amex, maintain normal EU-based banking services, or use digital accounts or services with US companies.  

While Guillou’s case may be extreme, and readers may fall on different sides of his decision, it shows the need for EU monetary sovereignty in cases where the US and EU do not see eye to eye. 

Reports from late 2025 suggesting that the digital euro would face difficulty in the EU Parliament now seem like ancient history, and a vote is scheduled for May 5, with Germany announcing its backing of the project yesterday.

Bolstering the case for a digital euro are more than 60 economists who are imploring EU parliamentarians to back the digital euro, warning the Eurozone would “lose control of the most fundamental element in our economy: our money,” to US payment providers.  

The economists, including famed French academic Thomas Piketty, state: “A strong public digital euro is not a nice-to-have, it is an essential safeguard of European sovereignty, stability and resilience.” 

They are right, and after Trump’s Greenland threat and US sanctions, rejecting the digital euro would now be politically unthinkable. 

♻️Repost to share the love for the digital euro.
#Fintech, #AI, and Tech at the speed of Asia and China.

Digital Euro: Visa and MC Can "Pull the Plug" on the EU

Weekend Read: Mambu's "Predictions Report" is a great read that is both easy to skim and thought-provoking as financial services are being "radically rewritten." 

What makes this report such a great read is the inclusion of quotes from industry practitioners in every chapter.  

If you read nothing else, go straight to page 15 for the excellent and rare coverage of Islamic finance.  

"By 2026, Islamic finance will no longer be seen as a niche alternative but as a blueprint for ethical, inclusive and technology-driven banking worldwide." 

Other noteworthy chapters:  Pg 18, "The Transformation in Banking" and Pg 32, "Gen Z, Gen Alpha, the Future of Finance." 

👉Seven topics will define the next chapter of financial services in 2026.

↳ Al and the financial revolution
Artificial intelligence has reached a new frontier of capability

↳Compliance, regulation, and cybersecurity
As innovation accelerates, trust has become one of the most valuable assets in financial services

↳Islamic finance
A principles-led model of finance is taking shape in the digital-first world

↳Transformation in banking
Banking is no longer defined by balance sheets and branches, but by the technology that connects them

↳Payment innovation and Embedded Finance
Payments are disappearing into the background of daily life

↳Crypto and blockchain
Blockchain has moved beyond experimentation to become part of modern finance's digital infrastructure

↳Gen Z, Gen Alpha, and the future of finance 
Every generation reshapes how people live, connect, and create value

What is Mambu missing, if anything?  

♻️Repost this great banking trends report, especially if you're among the 97.6% of LinkedIn users who don't post.  How can you go wrong with this one? 

#Fintech, #AI, and Tech at the speed of Asia and China.

Read How FinServ is Being "Radically Rewritten" 

The quantum threat is a trillion-dollar risk that could break every bank & crypto wallet in a decade as nationalism and insularity impact AI sovereignty and fintech's global aspirations.

If you’re reading this newsletter, I’m sure you are as “alert and attentive” as are the “syndics” of the “drapers guild” in Rembrandt’s famous painting below! 

This week's headline article is all about the quantum threat to finance and crypto. We’ve covered this topic before, but with advances in quantum computing, the threat is getting more real by the day.  

The good news is that standards for quantum-proofing systems exist, so banks and payment companies aren’t being asked to invent the technology, just apply it.  

Application, however, is still a monumental effort in that they need to audit their systems and manage a coordinated roll-out of new quantum-proof tech with other industry participants.

Add quantum to banks’ AI transformation, and it’s not an overstatement to say that they are seriously “burdened!” 

Which leads us to Accenture’s report on the top 6 tech trends for banks in 2026. I give tremendous credit to Accenture for one of the best reports of its kind.  

I just said that banks are “burdened,” and after reading this, you’ll see how heavy the burden on their shoulders is. I seriously doubt that most banks have the tech bandwidth to move fast enough on all of these efforts. 

Who could miss this week’s Davos Forum?  I have two reports that are straight out of Davos that focus on the impact of nationalism and insularity on Sovereign AI and fintech.

This is a real issue for neobanks Revolut, Nubank, and bunq (no capital B), all of which aspire to launch in the challenging US market.  

Deutsche Bank analysts declare that the AI honeymoon is over and that profits need to flow in 2026!  

This is a great read that confirms my constant warnings in this newsletter that while AI is transformational tech, it will take longer to implement than advertised. 

Finally, we look at Mambu’s top predictions for banking, look at the sections on Islamic Finance and Gen Z. 

♻️Repost to share these great reads on quantum and AI sovereignty.
#Fintech, #AI, and Tech at the speed of Asia and China.

Thanks for reading the “Cashless” newsletter, an insider’s view on Asia’s fintech, CBDC, and AI for anyone striving to understand “the Asia Century.” 

Open article: The Quantum Threat: Trillion-Dollar Risk That Could Break Every Bank & Crypto Wallet in a Decade by Richard Turrin • 5 min read

The Quantum Threat: Trillion-Dollar Risk That Could Break Every Bank & Crypto Wallet in a Decade

🚨Top 2026 Trends, No. 5:🚨 Digital Public Infrastructure Goes Global — Powered by Payments Success in India, Brazil, and China

Digital public infrastructure (DPI) is one of the most important trends in payments, with strong success in India and Brazil, making the rest of the world pay attention. 

DPI is a trend that cannot be ignored, and before readers say, it won’t happen in the West, I point to the digital euro, which is a model of DPI development. 

The digital euro proves that DPI is not solely the domain of developing countries but is every bit as relevant for advanced economies. 

Brazil’s UPI and India’s PIX together account for nearly two-thirds of global instant payment transactions and are models of how universal instant payments are an engine for economic growth.

China’s WeChat and Alipay also proved the economic value of universal instant payments, and while not strictly speaking DPI, the state-owned Union Pay network, initially used to carry their payments, is in spirit. 

As DPI, all of these payment systems are universally available and the cornerstone of financial inclusion, economic growth, and fintech innovation. 

Whether UPI, PIX, WeChat, or Alipay, all of these systems reduce onboarding time and provide instant, secure, and nearly cost-free payments, saving time and money for quite literally billions of users. 

DPI is a trend that won’t go away, and I expect more nations, particularly those in the global south, to take note and press forward with DPI payments. 

By the way of all of the top trends lists I've seen this year, I'm the only one covering DPI!   Check back in 2027!!

♻️Repost to share this important read on DPI
#Fintech, #AI, and Tech at the speed of Asia and China.

DPI is going global and not just for developing nations 

Full Circle Foresight > Innovation > Strategy > Transformation experience and Skills

Daniel Koch

The book "Generative AI in Higher Education: The ChatGPT Effect" examines the profound shift in the academic landscape following the rise of Large Language Models, framing the future as a period of significant educational uncertainty regarding assessment, pedagogy, and the very definition of learning.

Uncertainty in Assessment and Academic Integrity
A primary concern is the potential collapse of traditional methods used to evaluate student knowledge.

-The "Cheating" Wildcard: There is deep uncertainty about how to distinguish between genuine student effort and AI-generated output, leading to a crisis of trust in high-stakes testing.

-Obsolescence of Traditional Tasks: Standard assignments, such as the five-paragraph essay, face an uncertain future as AI can produce them in seconds, forcing educators to reconsider what "evidence of learning" looks like.

-Detection Efficacy: The report highlights the unpredictable reliability of AI-detection tools, creating a volatile environment where false positives and negatives disrupt the teacher-student relationship.

Pedagogical and Curricular Uncertainty
The document explores the "unknown" future of how subjects should be taught when AI can serve as a universal tutor.

-The Role of the Educator: There is uncertainty regarding the future role of professors—transitioning from "knowledge providers" to "learning facilitators"—and whether institutions can adapt their training fast enough.

-Curriculum Lag: A critical uncertainty is the "lag" between the rapid advancement of AI capabilities and the slow pace of institutional curriculum reform, potentially leaving graduates ill-prepared for an AI-integrated workforce.

.Standardized Learning Risks: There is a concern that over-reliance on AI-generated content might lead to a "homogenization" of thought, where students lose the ability to engage in unique, critical inquiry.

Ethical and Socio-Economic Uncertainty
The broader societal implications of AI in education introduce significant strategic wildcards.

-The "AI Divide": There is profound uncertainty regarding whether generative AI will democratize education by providing personalized support or exacerbate existing inequalities between those with and without access to premium AI tools.

-Data and Bias: The future reliability of AI as an educational resource is shadowed by uncertainty regarding the "black box" nature of its training data and the potential for embedded algorithmic biases to influence student worldviews.

In conclusion, the document suggests that higher education is at a pivotal crossroads. The future is defined not by the certainty of AI’s dominance, but by the uncertainty of whether human institutions can reinvent themselves fast enough to harness AI's potential while protecting the core values of critical thinking and academic rigor.

Dr. Daniel Jeffrey Koch

More Future Hope, less Future Anxiety - Exploring Future Uncertainty for Progress & Growth ​> Full Circle from Foresight ​> Innovation ​> Strategy ​> Transformation and back again

GenAI in Education

The AI 2030 Scenarios report by the UK Government Office for Science is a strategic foresight document designed to help policymakers navigate the "extraordinary" levels of future uncertainty surrounding the development and adoption of Artificial Intelligence over the next decade.

The Drivers of Uncertainty
The report identifies several "critical uncertainties"—factors that will have a high impact on the future but whose trajectory is currently unknown:

-The Pace of Technological Progress: It is uncertain whether we will see a "smooth" evolution of capabilities or "discontinuous leaps" (recursive self-improvement) that outpace governance.

-Safety and Control: The technical feasibility of "aligning" advanced AI with human values remains an unsolved and highly uncertain problem.

-Geopolitical Alignment: Will the future be defined by international cooperation on safety standards, or a "race to the bottom" driven by zero-sum competition between major powers?

-Economic Structure: There is profound uncertainty regarding whether AI will be a tool for widespread productivity and job creation or a driver of extreme labor market disruption and wealth concentration.

Systemic and Institutional Vulnerability
A recurring theme is that the "velocity of AI" may exceed the "velocity of policy."

-The Regulatory Lag: There is significant uncertainty about whether democratic institutions can adapt their legal and ethical frameworks fast enough to remain relevant.

-Information Integrity: The report highlights an uncertain future for "truth," as AI-generated misinformation could permanently damage the cognitive security of societies.

-Market Power: The future is clouded by the risk that a few "frontier" companies will gain sovereign-like power, creating an uncertain environment for competition and public oversight.

Summary of Strategic "Wildcards"
The report identifies specific "wildcard" events that could shift the world from one scenario to another:

-The Emergence of AGI: A sudden leap to Artificial General Intelligence that renders current safety protocols obsolete.

-A Major AI-enabled Disaster: A catastrophic event (e.g., a cyberattack on critical infrastructure) that triggers a global regulatory "crackdown."

-Energy and Resource Constraints: The possibility that the energy demands of massive models hit physical limits, slowing the "intelligence explosion."

Conclusion: Planning for Multiple Futures
The document concludes that because the future of AI is "radically uncertain," policy must be resilient across all scenarios. It urges leaders to move away from "single-track" planning and instead build "optionality"—the ability to pivot strategies as the reality of 2030 begins to unfold. The greatest danger identified is not any specific AI risk, but the failure to imagine and prepare for the full range of possible outcomes.

AI Scenarios

The Deutsche Bank Research Institute report, "Three AI themes for 2026: the honeymoon is over," describes 2026 as potentially the "hardest year yet" for artificial intelligence. 

The document highlights a transition from early hype to a period of significant future uncertainty as the technology moves into production and faces real-world scrutiny.

The report organizes these uncertainties into three primary themes:

Disillusionment: The Economic and Practical Gap
There is deep uncertainty regarding the immediate return on investment for generative AI. As pilots move into production, users are encountering inherent limitations in accuracy and the difficulty of applying AI to unpredictable, real-life scenarios. A major "unknown" is how long it will take—if ever—for AI to become more economical than human labor in many sectors. While AI champions point to rapid improvements in areas like coding, average CEOs face uncertainty regarding when the technology will deliver material revenue generation or systemic operational fixes.

Dislocation: The "AI of the Storm"
The report identifies systemic disruptions that create an unpredictable environment for the workforce and broader economy. There is ongoing uncertainty about the scale and speed of job dislocation as AI agents begin to work reliably for short periods (e.g., 30 minutes) before needing human assistance. The convergence of AI "doing" rather than just "talking" (exemplified by tools like Claude Code) suggests a looming shift in professional roles that is currently difficult for most people to visualize.

Distrust: The Reliability Crisis
A central theme of uncertainty revolves around the lack of satisfaction and trust in AI outputs. The "Distrust" theme suggests that AI has reached a point where it "can't get no satisfaction," implying that the unpredictability of its outputs remains a major barrier to enterprise-wide adoption. The shift from a novelty to a tool that must work reliably 24/7 introduces new risks that organizations are only beginning to confront.

The report suggests that while AI will survive, the year 2026 represents a deep uncertainty as the technology faces its hardest test: proving its worth beyond the Silicon Valley bubble in the messy reality of the global economy.

Three AI Themes

The Deutsche Bank Research report, "2026 Geopolitical Outlook: Geopolitical Realignment," argues that geopolitical volatility is no longer a temporary "glitch" but has become a structural feature of the international system. The document focuses on the profound future uncertainty facing investors and corporates as the global order undergoes a fundamental realignment.

Structural vs. Transitory Uncertainty
The report posits that the "unpredictable and fragmented" operating environment of the past few years is now the "new normal."

-Beyond Defensive Measures: Because volatility is structural, the report suggests that simply reacting defensively is insufficient. Investors must prepare for a future where geopolitical shifts happen with such pace and scale that identifying short- versus long-term risks becomes increasingly difficult.

-The Direction of Travel: Rather than providing a specific blueprint, the outlook emphasizes that the "direction of travel" for 2026 is toward deeper fragmentation, making a single global strategy for businesses nearly impossible to maintain.

Geopolitical Realignment and "Friend-Shoring"
A major source of future uncertainty is the shift from globalization to geopolitical blocs.

The Risk of Misalignment: There is a constant risk that a corporate's geographical footprint may suddenly fall on the "wrong side" of a new geopolitical divide, leading to sudden operational or reputational crises.

Key Themes of Uncertainty for 2026
The outlook identifies several critical areas where the future remains highly obscured:

-The "Fragmentation" Trap: As nations move toward protectionism and technological sovereignty, the future of global standards and trade agreements is in doubt.

-Resource and Tech Competition: Competition over critical minerals and AI leadership is driving national policies that are often "unpredictable," making it hard for firms to forecast input costs or regulatory hurdles.

-Interconnectedness of Risks: Geopolitical events are increasingly triggering "cascades" of financial and operational risks, where a conflict in one region can lead to immediate energy price shocks or supply chain paralysis globally.

Strategic Implications: Resilience as a Competitive Advantage
To manage this future uncertainty, the report suggests a shift in mindset:

-Dynamic Anticipation: Investors are urged to move from static risk management to a model of "anticipating and mitigating" risks in real-time.

-Seizing Opportunities: Paradoxically, the report suggests that those who can master the "structural volatility" will find opportunities that their more cautious or "defensive" competitors miss.

In conclusion, the document warns that 2026 will be characterized by a "realignment" where the old rules of global trade no longer apply. The greatest uncertainty lies in whether institutions and investors can adapt their "mental maps" fast enough to keep up with a world that is reorganizing itself in real-time.

Deutsche Bank

The joint report by the European Patent Office (EPO) and the OECD, "Mapping the global quantum ecosystem," provides a data-driven analysis of the quantum technology (QT) landscape. A central theme of the report is the tension between the immense potential of these technologies and the profound future uncertainty regarding their commercialization, standardization, and geopolitical impact.

Uncertainty in the "Quantum Breakthrough" Timeline
While the report celebrates a century of quantum mechanics, it acknowledges that the transition from laboratory science to mass-market application is fraught with unpredictability.

-The Scaling Challenge: There is significant uncertainty regarding when "Fault-Tolerant Quantum Computing" (FTQC) will be achieved. Current systems are in the NISQ (Noisy Intermediate-Scale Quantum) era, where errors are high and practical utility is limited.

-Investment Volatility: While venture capital and government funding have surged, there is a "strategic uncertainty" about whether these investments will yield returns before a potential "Quantum Winter"—a period of cooled interest if breakthroughs stall.

Competitive and Geopolitical Uncertainty
The report highlights a shifting global landscape where quantum capabilities are increasingly seen as a matter of national sovereignty.

-The Global Race: The U.S., China, and Europe are in a high-stakes competition. Uncertainty arises from how different regions prioritize different sectors (e.g., China's focus on quantum communication vs. the U.S. focus on computing).

-Export Controls and "Sovereign" Tech: As countries develop national quantum strategies (over 30 countries to date), the future of international scientific collaboration is uncertain. Increased sensitivity around "dual-use" applications (cryptography and defense) may lead to fragmented global research silos.

The Standards and Skills Gap
Future stability in the quantum ecosystem is hindered by a lack of infrastructure:

-Standardization: There is currently no global consensus on quantum standards for hardware or communication protocols. This creates a "waiting game" for industries that are hesitant to adopt technologies that might soon become obsolete.

-Talent Shortages: The report identifies a "quantum skills gap." The future growth of the ecosystem is uncertain because the supply of specialized physicists and engineers is not keeping pace with industry demand.

Summary of Technological Pillars
The report categorizes the future of the ecosystem into three main areas, each with its own set of uncertainties:

Conclusion: Navigating the Unknown
The report concludes that while the "quantum revolution" is inevitable, the pathway to that future is non-linear. Strategic flexibility and "ecosystem thinking" are recommended to manage these inherent uncertainties.

Quantum Computing

The Roland Berger "Foresight 2026" report characterizes 2026 as a critical transition period for China, moving from the 14th to the 15th Five-Year Plan. This transition is marked by a "strategic pivot" toward high-quality growth and sustainable modernization, which introduces significant future uncertainty across industrial, technological, and geopolitical dimensions.

Economic and Industrial Uncertainty
The report identifies several "bottlenecks" and shifts that create an unpredictable landscape for China’s development:

-Structural Transformation: There is uncertainty regarding the "rebalancing" of the economy as China moves away from traditional growth drivers toward high-tech sectors like AI, biotech, and humanoid robots.

-Resource Allocation: The transition requires more efficient planning for resource allocation and regional coordination to address issues like industrial overcapacity.

-Global Growth Contribution: While China accounts for 30% of global economic expansion, the report highlights the uncertainty of maintaining this momentum amid "evolving global dynamics".

Technological and Innovation Wildcards
China has emerged as a frontrunner in several advanced technologies, but their long-term impact remains a source of strategic uncertainty:

-The High-Tech Race: The rapid improvement in fields such as quantum computing, space technology, and biotech creates a volatile competitive environment where today's leaders must constantly innovate to avoid obsolescence.

-Sustainable Modernization: There is uncertainty about how quickly China can embed sustainability into all industrial projects while maintaining its position as the world's largest manufacturing powerhouse.

Geopolitical and Global Order Uncertainty
The report frames the future within a "New World Order," emphasizing the challenge of maintaining balance:

-The "Art of Balance": A central theme is the uncertainty of navigating China’s potential within a shifting global order, requiring leaders to balance domestic industrial goals with international geopolitical pressures.

-Market Integration: As China pivots toward "high-quality growth," the future of its integration with global markets and supply chains remains subject to the "evolving dynamics" of international relations.

In conclusion, the report suggests that 2026 will be a year defined by strategic pivoting. The "vast unknown" for China lies in whether it can successfully navigate the transition to the 15th Five-Year Plan while balancing the demands of high-quality growth with the uncertainties of a changing global landscape.

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