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GAM Global Special Situations Fund calls for Crypto transparency and value maximisation in SBI Holdings
December 17, 2024
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On the 3 December 2024, the investment managers of GAM Global Special Situations Fund issued an open letter calling for SBI Holdings Inc (8473:TYO) to enhance crypto transparency and actively maximise shareholder value. The letter highlights the significant, yet under recognised, value of SBI's investment in Ripple Labs and its vast XRP holdings—valued at JPY 1.6 trillion against SBI's market cap of JPY 1.2 trillion.

GAM Global Special Situations Fund urges SBI Holdings Inc to:

  • Publish daily updates on the indirect value of its XRP holdings.
  • Clearly outline its strategy in blockchain technology and cryptocurrencies.
  • Provide regular, transparent calculations of its Net Asset Value (NAV).

GAM Global Special Situations investment managers also recommend SBI consider an XRP buyback program to further leverage its blockchain investments, similar to the strategy adopted by MicroStrategy in the US. By taking these steps, SBI can significantly close the gap between its market value and its NAV, estimated at JPY 3.9 trillion.

++end++

Open Letter:

Yoshitaka Kitao
CEO
SBI Holdings
Izumi Garden Tower 19F
1-6-1 Roppongi, Minato-ku, Tokyo 106-6019
cc. Bloomberg, FT, WSJ

December 3, 2024

Dear Kitao San,

We are the managers of the GAM Global Special Situations fund, which is a shareholder in your company, and we take a keen interest in it. As such, we had the honor of visiting your Roppongi office last September 11 where we met with Mr Motoaki Shiino and Mr. Toshiki Aoyama.

Over the years, we noted how SBI became a key player in the Japanese banking and securities businesses but also a significant investor in blockchain technology, particularly through its investment and ownership in Ripple Labs and SBI Ripple Asia. Ripple Labs owns at last count 48bn XRP. SBI owns between 8 and 9% of Ripple Labs and is its largest outside shareholder. That stake is worth at least JPY 1.6tr (through its XRP holding, and this does not take into account the valuation of Ripple Labs itself) vs. SBI’s entire market capitalization of JPY 1.2tr. The value of this investment is little known by the market and SBI’s strategy around Ripple’s blockchain technology is not clear. In fact, your IR company presentations, while very long and detailed, are very confusing.

As a result, SBI is selling at a very significant discount to its Net Asset Value (NAV) and SBI’s board and management is implicitly destroying shareholder value by not having a pro-active stance when it comes to its blockchain/cryptocurrencies and Ripple investments. The following chart shows the implicit value of SBI ascribed by the market after simply deducting the indirect value of its XRP holdings:

Hence, while SBI’s share price may have gone up this year from about JPY3000 to JPY4000, this increase is in fact “illusory” as SBI’s implicit value excluding its indirect holdings of XRP has actually plunged into negative JPY357bn. The following chart clearly highlights that point: (the orange line is SBI’s market capitalization; white line is SBI’s market ascribed value ex-XRP value).

We believe that SBI shareholders would benefit greatly if:

1/ SBI would publish a daily “live” indirect value of its XRP holdings

2/ SBI would detail clearly its strategy in blockchain technology and cryptocurrencies businesses

3/ SBI would regularly provide a clear calculation of its NAV components and overall NAV. We would be happy to assist your IR department to develop an investor friendly webpage to communicate such information.

We also urge SBI to have an active and public XRP coin buying program. Rather than pay a cash dividend, SBI shareholders would benefit greatly if SBI had a XRP buyback program by recycling a part of its cash flow from its banking and securities business. We suggest that the company announces such a program and embarks on a XRP crypto strategy similar to the highly successful XBT strategy pursued by MicroStrategy in the US.

SBI’s board should aggressively work towards getting the company’s value closer to its NAV which we calculate to be around JPY 3.9tr (including XRP’s indirect holdings) or over 3x its current market capitalization. Having a transparent strategy and communication around your Ripple and blockchain/crypto strategies are key to reaching your fiduciary duty to increase shareholder value.

Looking forward to hearing from you,

Best regards,

Albert Saporta
Co-CIO GAM Alternatives
GAM Investment Management (Switzerland) AG

Randel Freeman
Co-CIO GAM Alternatives
GAM USA Inc.


About the GAM Global Special Situations Fund

The investment managers of the GAM Global Special Situations Fund have long held the fundamental belief that markets can be inefficient, and securities go through distinct periods of mispricing, especially in complex corporate situations and when related securities are traded across different markets.

We believe by incorporating these securities in a thoughtfully structured portfolio and employing sophisticated hedging strategies we can achieve superior uncorrelated risk-adjusted returns across all market cycles.

The GAM Global Special Situations Fund invests globally long and short in securities of companies, intra and across markets and within complex corporate capital structures, which are often undergoing significant corporate change. Rigorous quantitative modelling and screening is combined with fundamental analysis and our deep understanding of event-driven dynamics.

The investment strategy is co-managed by Albert Saporta and Randel Freeman − two of the pioneers in global event-driven and special situations investing with over 70 years combined experience.

About GAM

GAM is an independent investment manager that is listed in Switzerland. It is an active, independent global asset manager that divers distinctive and differentiated investment solutions for its clients across its Investment and Wealth Management Businesses. Its purpose is to protect and enhance its clients’ financial future. It attracts and empowers the brightest minds to provide investment leadership, innovation and a positive impact on society and the environment. Total assets under management were CHF 19.0 billion as of 30 June 2024. GAM has global distribution with offices in 14 countries and is geographically diverse with clients in almost every continent. Headquartered in Zurich, GAM Investments was founded in 1983 and its registered office is at Hardstrasse 201 Zurich, 8037 Switzerland. For more information about GAM Investments, please visit www.gam.com.

For further information please contact:

 

Albert Saporta, Co-CIO GAM Alternatives
GAM Investment Management (Switzerland) AG
[email protected]

 

Randel Freeman, Co-CIO GAM Alternatives
GAM USA Inc.
[email protected]

 

Media Relations
Colin Bennett
T +44 (0) 207 393 8544

 

Visit us: www.gam.com
Follow us: X and LinkedIn

 

Other important information

This release contains or may contain statements that constitute forward-looking statements. Words such as “anticipate”, “believe”, “expect”, "estimate", "aim", “project”, “forecast”, "risk", “likely”, “intend”, “outlook”, “should”, “could”, "would", “may”, “might”, "will", "continue", "plan", "probability", "indicative", "seek", “target”, “plan” and other similar expressions are intended to or may identify forward-looking statements.

Any such statements in this release speak only as of the date hereof and are based on assumptions and contingencies subject to change without notice, as are statements about market and industry trends, projections, guidance, and estimates. Any forward-looking statements in this release are not indications, guarantees, assurances or predictions of future performance and involve known and unknown risks, uncertainties and other factors, many of which are beyond the control of the person making such statements, its affiliates and its and their directors, officers, employees, agents and advisors and may involve significant elements of subjective judgement and assumptions as to future events which may or may not be correct and may cause actual results to differ materially from those expressed or implied in any such statements. You are strongly cautioned not to place undue reliance on forward-looking statements and no person accepts or assumes any liability in connection therewith.

This release is not a financial product or investment advice, a recommendation to acquire, exchange or dispose of securities or accounting, legal or tax advice. It has been prepared without taking into account the objectives, legal, financial or tax situation and needs of individuals. Before making an investment decision, individuals should consider the appropriateness of the information having regard to their own objectives, legal, financial and tax situation and needs and seek legal, tax and other advice as appropriate for their individual needs and jurisdiction.

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Revolut Leak Shows the Cost of Constant ID Collection
Revolut’s mistake is the news, but the bigger problem is the growing number of companies being encouraged or required to keep copies of our most sensitive identity documents.

Online bank Revolut has revealed that it gave out sensitive personal and financial information of an undisclosed number of its customers in response to a fake government request.

The information that was handed over to an “unauthorized third party” reportedly includes names, dates of birth, occupations, addresses, phone numbers, account numbers, transaction histories (including Bitcoin), and even copies of government-issued IDs and onboarding verification selfies.

Revolut claims that derived biometric face data was not.

The company said that the data was handed over in response to an email that came from a real government agency’s domain, but was not actually sent or authorized by that agency.

The email passed several authentication checks (SPF, DKIM, and DMARC) that are designed to establish the authenticity of a message’s origin and integrity, but do not verify the legitimacy of the legal request itself.

Revolut said that it complied with the request “under the reasonable belief that it was an authentic government agency request” – and only later found out that it was not.

Revolut said it later realized its mistake, blocked the email address, and reported the incident to the relevant authorities.

Revolut said that only a “limited” number of its customers were affected by the data leak, and that the company’s systems were not hacked, nor was any money stolen.

The story broke on September 11 when Revolut customers started receiving an email notice about a data leak, and the news was picked up by media outlets the following day.

Revolut notice explaining customer identity and financial data was shared after an unauthorized government email request.

The reason this is a recurring problem is that companies are keeping highly sensitive information about their customers’ identities, and sometimes even financial transactions, for a long time, and this data is then available to be disclosed to third parties – either in response to valid legal requests, or, as in the case of Revolut, fake ones.

One reason for this is know your customer (KYC) and anti-money laundering (AML) rules. Revolut’s current UK customer privacy notice spells it out: the company generally keeps personal data of UK customers for no more than seven years after the relationship ends, and sometimes longer – for legal reasons.

This means that even if you close your account, your identity documents don’t disappear.

And while the incident with Revolut happened in the financial sector, it’s by no means the only one that requires customers to hand over sensitive identity information. Discord, a popular chat service, said in an October 9, 2025 security update that government ID photos of approximately 70,000 users may have been exposed after a third-party customer service provider got hacked.

This was not a financial service, nor the same type of attack. But the result was similar – because the underlying business process was the same: requiring and storing sensitive identity documents. In the case of Discord, these were used to review age-related appeals.

It’s hard to do anything about a copy of your old passport, or a photo of your face, or a record of your past transactions. These can be used to identify and profile you, and can be used to carry out targeted fraud. And this can happen even if the initial disclosure didn’t result in financial loss.

The more companies are forced to collect and store such information, and the more of it they have, the more opportunities there are for this data to be leaked, either by the company itself or a third party it works with. That's what makes governments' push for more ID checks just to access ordinary parts of life so reckless.

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This Is The Income A Family Needs To Live Comfortably In Every US State

Here’s the short version of what it takes for a family of four to live comfortably in 2026 by state:

In Massachusetts, you’d need nearly $330,000 a year - the highest figure in the entire country. Only three states clear the $300,000 mark: Massachusetts, Hawaii, and California. At the other end of the spectrum, Mississippi is the most affordable at about $188,000. That’s a full $142,000 less than what you’d need in Massachusetts.

So… how much does a family of four need in your state?

This map shows the pre-tax income a household with two working adults and two kids needs to live comfortably in every U.S. state.

The numbers come from SmartAsset (as of February 2026). They’re based on the familiar 50/30/20 budget: 50% for necessities, 30% for discretionary spending, and 20% for savings or other goals. These aren’t bare-minimum survival numbers—they’re what it takes to live pretty well while still putting money aside.

And as Visual Capitalist notesMassachusetts sits at the very top of that list. Massachusetts tops the ranking, with a family of four needing $329,555 per year to meet the 50/30/20 benchmark.

Hawaii follows at $313,165, while California ranks third at $302,682.

Rank State Income needed for family of four (2026)

  • 1 - Massachusetts - $329,555
  • 2 - Hawaii - $313,165
  • 3 - California - $302,682
  • 4 - Connecticut - $298,189
  • 5 - New Jersey - $295,110
  • 6 - New York - $291,533
  • 7 - Colorado - $283,213
  • 8 - Washington - $281,798
  • 9 - Oregon - $280,966
  • 10 - Vermont - $280,384
  • 11 - Alaska - $272,064
  • 12 - New Hampshire - $267,904
  • 13 - Rhode Island - $264,659
  • 14 - Minnesota - $263,078
  • 15 - Maryland - $257,837
  • 16 - Maine - $250,931
  • 17 - Montana - $249,434
  • 18 - Pennsylvania - $247,936
  • 19 - Illinois - $244,109
  • 20 - Virginia - $242,944
  • 21 - Nevada - $242,278
  • 22 - Indiana - $241,696
  • 23 - Wisconsin - $238,451
  • 24 - Arizona - $236,870
  • 25 - Utah - $235,789
  • 26 - Delaware - $228,134
  • 27 - Ohio - $226,221
  • 28 - Idaho - $226,054
  • 29 - Florida - $223,392
  • 30 - New Mexico - $223,142
  • 31 - Nebraska - $223,059
  • 32 - Missouri - $217,734
  • 33 - Georgia - $214,573
  • 34 - Michigan - $214,323
  • 35 - South Carolina - $212,909
  • 36 - North Carolina - $212,410
  • 37 - Wyoming - $212,410
  • 38 - Oklahoma - $211,910
  • 39 - North Dakota - $210,496
  • 40 - Kansas - $207,917
  • 41 - Iowa - $204,422
  • 42 - Texas - $203,424
  • 43 - West Virginia - $202,592
  • 44 - South Dakota - $201,760
  • 45 - Alabama - $198,931
  • 46 - Louisiana - $197,933
  • 47 - Tennessee - $197,267
  • 48 - Arkansas - $195,437
  • 49 - Kentucky - $194,854
  • 50 - Mississippi - $187,533

Connecticut, New Jersey, and New York aren't far behind, bringing the number of states with comfortable-income thresholds above $290,000 to six.

Colorado and Vermont Make the Top 10

As expected, many of the highest income thresholds are concentrated in the Northeast and along the West Coast.

However, Colorado has the seventh-highest threshold in the country at $283,213, ranking above Washington and Oregon.

Vermont rounds out the top 10 at $280,384, despite having the second-smallest population of any U.S. state. Meanwhile, nearby states like New Hampshire, Maine, and Rhode Island all fall outside the top 10.

Just Six States Come in Below $200,000

Despite the wide range in living costs across the country, only six states have a comfortable-income threshold below $200,000 for a family of four.

Mississippi ranks lowest at $187,533, followed by Kentucky. The states of Arkansas, Tennessee, Louisiana, and Alabama also fall below the $200,000 mark.

The gap between Massachusetts and Mississippi exceeds $142,000 per year, meaning the Massachusetts benchmark is about 76% higher.

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🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
 
That movement is decentralized AI.
 
Why Decentralized AI Exists
 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
  • Warehouse robots contribute operational data.
  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
 
In other words, the pieces are starting to appear.
 
Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
 
The goal is not simply decentralization for its own sake.
 
The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
But Here's the Reality
 
Decentralized AI faces the same challenge every decentralized technology faces.
 
Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
 
The challenge isn't just decentralizing intelligence.
 
It's decentralizing intelligence while maintaining performance.
 
That's much harder.
 
The Most Likely Outcome
 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
 
The companies building robots may use NVIDIA hardware.
 
Train on Azure.
 
Run foundation models from OpenAI.
 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
 
The Bigger Question
 
The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
 
Because the battle for the future of robotics is no longer about hardware.
 
It's about who owns the intelligence.
 
And that battle is just getting started.
 
 

🙏To support my work, Helping to keep the signal high and the noise low:

👉 Cashapp: $thedinarian

👉 Buy me a coffee: https://buymeacoffee.com/thedinarian

👉 PayPal: Scan the QR code below 📲 or Click Here

👇 Crypto Donations 👇

XRP: r9pid4yrQgs6XSFWhMZ8NkxW3gkydWNyQX
XLM: GDMJF2OCHN3NNNX4T4F6POPBTXK23GTNSNQWUMIVKESTHMQM7XDYAIZT
XDC: xdcc2C02203C4f91375889d7AfADB09E207Edf809A6

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