Consensus Live | Avenir Group, Tiger, AMINA, and CoinRoutes Discuss Institutional Capital Efficiency and Financial Infrastructure Evolution

marsbitPublished on 2026-02-11Last updated on 2026-02-11

Abstract

At Consensus Hong Kong 2026, the institutional investment narrative is structurally shifting toward multi-asset allocation, yet cross-system frictions are diluting capital efficiency. Avenir Group, in partnership with Tiger Brokers, AMINA Bank, and CoinRoutes, led a roundtable on next-generation institutional trading infrastructure. Key consensus emerged: the industry must transition from an asset-centric to a capital-centric framework to optimize efficiency in a multi-asset environment. Panelists highlighted challenges including fragmented capital utilization due to segregated systems, misaligned clearing cycles causing idle capital, and the need for natively compliant, scalable infrastructure. Avenir Group and partners signed an MOU to explore collaborative solutions, emphasizing that future competitiveness hinges on unified capital management and cross-asset operational capabilities within regulatory frameworks.

At Consensus Hong Kong 2026, the narrative focus of institutional investors is undergoing a structural shift. As regulatory frameworks mature, crypto assets are accelerating their integration into institutional portfolios, moving beyond exploratory allocations. However, this transition towards multi-asset allocation has highlighted a new theme: although portfolios are expanding across asset classes, cross-system friction is diluting capital efficiency.

Avenir Group, an investment group dedicated to promoting the integration of traditional finance and digital assets, has observed that as the scale of institutional participation grows, the completeness of infrastructure is increasingly impacting institutional capital efficiency. As an official partner of Consensus Hong Kong 2026, Avenir Group initiated a roundtable discussion titled "Next-Generation Institutional Trading Infrastructure." Industry leaders from global leading tech brokerage Tiger Brokers, Swiss FINMA-regulated crypto bank AMINA Bank AG (“AMINA Bank”), and leading multi-asset institutional trading platform CoinRoutes systematically deconstructed the reasons behind constrained capital efficiency in a multi-asset environment and jointly explored potential evolutionary directions.

Industry Consensus: A Foundational Restructuring from "Asset-Oriented" to "Capital-Oriented"

During the discussion, a core consensus was reached: the industry must shift from an "Asset-Centric" infrastructure framework to a "Capital-Centric" framework.

In the past, an asset-centric model, optimized for single asset classes, could meet demands. However, in the complex era of multi-asset markets, this model may lead to a certain degree of capital efficiency drain. When institutions manage traditional and digital assets in parallel, the inherent differences between these assets—from price volatility to clearing and settlement cycles—result in hidden capital occupation and execution friction. These are no longer mere operational inconveniences but can become significant structural constraints affecting overall capital efficiency.

Roundtable guests shared deep insights from different parts of the value chain:

· Holistic Capital Efficiency Utilization: Felix Huang Shuojun, Global Partner at Tiger Brokers International, pointed out that traditional markets improve capital utilization through margin interoperability; however, the inclusion of digital assets disrupts this synergy. Existing systems are often designed around "asset isolation" rather than "overall capital efficiency," making it difficult for institutions to achieve cross-asset capital allocation within a unified framework.

· Efficient Execution and Liquidity Linkage: Ian Weisberger, CEO and Co-Founder of CoinRoutes, added that misaligned clearing rhythms leave substantial funds idle during trading gaps. What institutions urgently need is unified execution capability across markets and for multi-leg strategies, as well as flexible rotation of positions and risk across different asset classes.

· Compliance-First Infrastructure: Myles Harrison, Chief Product Officer at AMINA Bank, emphasized that compliance is not the opposite of efficiency but a prerequisite for the safe operation of the system. The pain point lies in the industry's lack of a natively multi-asset supportive infrastructure that also possesses high transparency and scalability, thereby unlocking capital potential within a global compliance framework.

Jacob Zhong, Managing Partner of Strategic Investment and Cooperation at Avenir Group, stated: "Synthesizing industry insights, the direction of infrastructure evolution has become relatively clear. As institutional participation in multi-asset environments deepens, the market increasingly requires an infrastructure capable of unified cross-asset capital allocation, synchronized trading execution and clearing rhythms, and embedding compliance capabilities natively into the system (rather than as an afterthought patch). In this direction, more integrated and regulation-adaptive infrastructure is gradually becoming a crucial support for enhancing capital efficiency and enabling cross-asset operations at scale."

Building the Ecosystem Together: Advancing Financial Infrastructure Evolution Through Collaborative Action

At the conclusion of the thematic discussion, Avenir Group, Tiger Brokers, AMINA Bank, and CoinRoutes formally signed a Memorandum of Understanding (MOU) to explore potential future cooperation.

The integration of traditional finance and digital assets is not merely a technical or product-level consolidation but a progressive, systematic compliance engineering project. As multi-asset allocation becomes the norm, the competitive focus among institutions is shifting—it no longer depends solely on market access capabilities but on the systemic ability to manage and flexibly allocate capital under a compliance framework.

Avenir Group looks forward to collaborating with a broader range of financial institutions and technology partners. By fostering dialogue and cooperation across the entire ecosystem, Avenir Group aims to join hands with industry partners to jointly promote a more synergistic and scalable infrastructure path, gradually turning the enhancement of capital efficiency from an industry consensus into verifiable practice.

About Avenir Group

Avenir Group is a pioneering investment group focused on driving the integration of traditional finance and digital assets, building the financial infrastructure of the future. The group adopts an integrated "Investment—Incubation—Operation" strategy, with a core investment portfolio focusing on digital asset management, trading and financial services platforms, payment finance (PayFi) infrastructure, and real-world asset (RWA) tokenization, providing the industry with institutional-grade products and services, and continuously promoting financial innovation and the development of emerging technologies. As the largest institutional holder of Bitcoin ETFs in Asia, Avenir Group expands its business globally, covering Hong Kong, Singapore, Tokyo, London, San Francisco, and more. Leveraging robust capital strength and professional operational capabilities, the group is committed to becoming a strategic hub connecting Eastern and Western capital, driving efficient global capital flow and collaboration. Learn more: https://avenirx.com

Related Questions

QWhat is the main shift in the narrative focus for institutional investors at Consensus Hong Kong 2026, as discussed by Avenir Group and partners?

AThe narrative focus is shifting structurally from exploratory allocation of crypto assets to their accelerated integration into institutional portfolios, highlighting the theme that cross-system friction is diluting capital efficiency despite multi-asset expansion.

QAccording to the roundtable, what fundamental change is needed in infrastructure frameworks to improve capital efficiency in multi-asset environments?

AThe industry must transition from an 'Asset-Centric' infrastructure framework to a 'Capital-Centric' one to enable unified capital scheduling across assets, synchronized execution and settlement rhythms, and natively embedded compliance capabilities.

QWhat specific capital efficiency challenge did Felix Huang Shuojun from Tiger International highlight regarding digital assets?

AHe pointed out that while traditional markets improve capital utilization through margin interoperability, the inclusion of digital assets disrupts this synergy. Existing systems designed for 'asset isolation' rather than 'overall capital efficiency' hinder unified cross-asset capital scheduling.

QHow did Ian Weisberger of CoinRoutes and Myles Harrison of AMINA Bank contribute to the discussion on infrastructure needs?

AIan Weisberger emphasized the need for unified execution capabilities across markets and flexible rotation of positions and risk between asset classes, citing idle funds due to misaligned settlement cycles. Myles Harrison stressed the necessity for native multi-asset infrastructure with high transparency and scalability that operates within global compliance frameworks to unlock capital potential.

QWhat action did Avenir Group and its partners take following the roundtable discussion, and what is their broader goal?

AThey signed a strategic Memorandum of Understanding (MOU) to explore future collaboration. Avenir Group aims to work with financial institutions and tech partners to promote dialogue and cooperation, advancing more synergistic and scalable infrastructure paths to turn capital efficiency consensus into verifiable practice.

Related Reads

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbit42m ago

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbit42m ago

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbit47m ago

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbit47m ago

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbit47m ago

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbit47m ago

Trading

Spot
活动图片