Fintech & Payments

Inside Noah’s Black Diamond Summit: How AI Is Rewriting the Future of Global Wealth

As global financial landscapes shift, Noah outlines a new AI-first approach to helping families protect and grow their wealth.

Updated

January 8, 2026 6:31 PM

Noah’s Black Diamond Summit. PHOTO: ARK WEALTH

Noah Holdings, one of Asia’s leading wealth management firms serving global Chinese high-net-worth families, hosted its annual Black Diamond Summit in Macau from December 7–11. The city has become a significant gathering place for Noah’s community, where clients, partners, and experts converge each year to explore how global trends are transforming wealth and family life. This year’s theme, “AI Together, Co-Generating the Future”, set the tone for a conversation about how modern wealth management must adapt in an age defined by artificial intelligence.

More than 3,000 attendees joined discussions that connected technology, global mobility, and long-term family planning. The Summit built on earlier sessions held in Shanghai, creating a continuous dialogue around one central question: how can families prepare for a world that is becoming more digital, more complex and more interconnected?

A major moment came when Noah introduced “Noya”, its new AI Relationship Manager. Noya is now part of the upgraded iARK Hong Kong and Singapore apps. It is built to support licensed human advisors, not replace them. The goal is simple: combine human judgment with AI intelligence to help clients understand their wealth more clearly and manage it across borders. Noya offers real-time insights, deeper personalisation, cleaner access to global financial information, smoother coordination between regions, and end-to-end execution through Noah’s global booking centres.

The Summit’s tone shifted toward long-term thinking when Co-Founder and Chairwoman Norah Wang delivered her keynote, “From Chaos to Clarity: Building a Global Operating System for Wealth Management”. She reflected on twenty years of serving more than 400,000 clients and explained that families today face new pressures. As she put it, “The real pain point for Chinese families today is not investment performance, but navigating the growing complexities of a global lifestyle”. Her message was straightforward: wealth is no longer just about returns. It is about managing uncertainty in a world where technology, geopolitics, and mobility collide.

Wang described how two major shifts have shaped modern wealth—first the Internet Era, which changed how people built wealth, and now what she calls the AI Civilisation Era, which is changing how people must protect it. She outlined the forces that influence today’s decisions: geopolitical shifts, persistent inflation, the rising importance of security and supply-chain technologies, the spread of AI, and the need for stronger family governance across generations. Each of these factors adds complexity, and families need tools that help them see the bigger picture.

To respond to this reality, Noah presented its integrated global wealth infrastructure. It is built on three pillars:

  • Olive, which focuses on asset management and global investment growth
  • Glory, which supports families in governance, succession planning, and legacy architecture
  • ARK, the company’s global booking and execution centre, which enables cross-border wealth operations

Together, these pillars function as an AI-supported system designed to simplify global complexity and help families preserve long-term stability.

One of the most discussed conversations featured Noah’s CEO, Zander Yin, and Tony Shale, Co-Founder & Chairman of Asian Private Banker China. They spoke about how AI is transforming private banking in Asia. Their view was that wealth management is moving from a product-centred model to one led by insight, trust, and human-tech collaboration. AI may accelerate analysis, but human expertise will continue to guide judgment, relationships, and long-term strategy.

The closing message of the Summit centred on redefining what prosperity means in an AI-driven age. For Noah, wealth is no longer a destination. It is an ongoing journey through a world that is increasingly fast-moving and unpredictable. As Wang noted, “With AI reshaping the very foundations of civilisation, wealth and financial freedom represent not a static endpoint, but a continuous journey. Here, we find our purpose: to help global Chinese investors navigate an increasingly complex world and achieve true prosperity, supported by resilient wealth management infrastructure and deep human expertise”.

The Summit ended on that note—a reminder that the future of wealth is not only about financial assets, but about clarity, confidence and the ability to adapt as the world transforms.

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Startup Profiles

How Startup xCREW Is Building a Different Kind of Running Platform

A look at how motivation, not metrics, is becoming the real frontier in fitness tech

Updated

February 7, 2026 2:18 PM

A group of people running together. PHOTO: FREEPIK

Most running apps focus on measurement. Distance, pace, heart rate, badges. They record activity well, but struggle to help users maintain consistency over time. As a result, many people track diligently at first, then gradually disengage.

That drop-off has pushed developers to rethink what fitness technology is actually for. Instead of just documenting activity, some platforms are now trying to influence behaviour itself. Paceful, an AI-powered running platform developed by SportsTech startup xCREW, is part of that shift — not by adding more metrics, but by focusing on how people stay consistent.  The platform is built on a simple behavioural insight: most people don’t stop exercising because they don’t care about health. They stop because routines are fragile. Miss a few days and the habit collapses. Technology that focuses only on performance metrics doesn’t solve that. Systems that reinforce consistency, belonging and feedback loops might.

Instead of treating running as a solo, data-driven task, Paceful is built around two ideas: behavioural incentives and social alignment. The system turns real-world running activity into tangible rewards and it uses AI to connect runners to people, clubs and challenges that fit how and where they actually run.


At the technical level, Paceful connects with existing fitness ecosystems. Users can import workout data from platforms like Apple Health and Strava rather than starting from scratch. Once inside the system, AI models analyse pace, frequency, location and participation patterns. That data is used to recommend running partners, clubs and group challenges that match each runner’s habits and context.


What makes this approach different is not the tracking itself, but what the platform does with the data it collects. Running distance and consistency become inputs for a reward system that offers physical-world incentives, such as gear, race entries or gift cards. The idea is to link effort to something concrete, rather than abstract. The company also built the system around community logic rather than individual competition. Even solo runners are placed into challenge formats designed to simulate the motivation of a group. In practice, that means users feel part of a shared structure even when running alone.

During a six-month beta phase in the US, xCREW tested Paceful with more than 4,000 running clubs and around 50,000 runners. According to the company, users increased their running frequency significantly and weekly retention remained unusually high for a fitness platform. One beta tester summed it up this way: “Strava just logs records, but Paceful rewards you for every run, which is a completely different motivation”.

The company has raised seed funding and plans to expand the platform beyond running, walking, trekking, cycling and swimming. Instead of asking how accurately technology can measure the body, platforms like Paceful are asking a different question: how technology might influence everyday behaviour. Not by adding more data, but by shaping the conditions around effort, feedback and social connection.

As AI becomes more common in consumer products, its real impact may depend less on how advanced the models are and more on what they are applied to. In this case, the focus isn’t speed or performance — it’s consistency. And whether systems like this can meaningfully support it over time.