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How banks and businesses can prep for the FedNow instant-payment system
July 04, 2023
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FedNow will be the first of its kind central bank instant payment system in the US and could revolutionize how businesses and consumers pay and receive money. But not everyone is prepared for it.

After a pilot program that lasted six months, the US Federal Reserve System plans to launch its FedNow real-time payment system in July. But many banks and businesses could be caught flatfooted when it launches.

The central bank’s payment and settlement rail is designed to increase liquidity, especially for small businesses and supply chain participants who can get paid instantly for goods and services. It also creates a new way for employees, especially gig and hourly-rate employees, to get paid more quickly and frequently — perhaps every day.

The new system will allow banks, businesses, and consumers to send and receive payments in about 10 seconds anytime, any day. As with other payment systems, there are fees associated with the service, and banks will have to decide who foots the bill — merchants, consumers, neither, or both.

"Banks aren't 24/7 in their operations today," said Debbie Buckland, a director analyst in financial services for Gartner Research. "So, they'll have to have procedures set up to accomodate that liquidity management that happens in the middle of the night. Becasue if you give your customers the ability to do their banking in the middle of the night, they're going to do it."

Initally, FedNow will only let banks receive payments; the ability to send payments — and for consumers to be able to identify themselves by phone number and email only, as Venmo now allows — is expected to come later.

"The send part takes a little more work," Buckland said. "You have to have a vehicle for customers — both consumers and businesses — to initiate a real-time payment. That means adding that functionality to their digital and mobile channels. You need to be able to upgrade your product or turn on that service."

For consumers, the process is far easier. Those who want an instantaneous way to make payments, whether it's for a retail product or a mortgage installment, will need to download an app once their financial services provider offers it. 

There are two primary differences between FedNow and traditional payment systems such as automated clearinghouse services (ACH) and wire transfers, such as Western Union or the Fed’s own Fedwire service. ACH transactions settle just once at the end of a business day, and they settle in batches — not individually. Wire transfers are faster, but charge higher user fees. Wires are also not used for multiple or traditional batch transactions, and they’re still not real time; they can take several minutes or several days for remittances or cross-border payments.

For consumers not familiar with the ACH payment system, it's the funds transfer system used when employees sign up for direct deposit, make eChecks payments or authorize automatic payments to be deducted from their banking accounts.

FedNow is not a replacement for existing ACH and wire networks, but an additional payment option when real-time payments and settlements are needed.

Existing payment systems will be challenged by FedNow’s efficiency, and while the impact will be significant, it’s not likely to supplant other systems, according to Aaron Press, research director for Worldwide Payment Strategies at IDC.

“Electronic payments are growing fast enough in general that, even if other systems lose share, they won’t necessarily stop growing,” Press said. “But, they’re not taking this standing still. Every other payment system [operator] is thinking about how to position against FedNow. Even the [Federal Reserve] is thinking about the impact of FedNow on its own Fedwire service.”

The new system also means banks that adopt it will have to adjust to a 24/7 world where merchants or consumers might want to transfer funds between different third-party accounts at odd hours of the day or night. It also means banks won’t have a full business day, as they do now, to go through know-your-customer,  anti-money laundering, and anti-fraud processes. Those processes will have to be automated for real-time discovery.

For many banks, 'a real shift'

“For a lot of banks, this is a real shift in operational thinking,” Press said. “The margin of error is significantly smaller. The time to do things manually is essentially gone. We’re hearing a lot from banks and vendors who offer automation that there’s an increasing demand for automating a lot of tasks and workflows to better handle real-time messages.”

From a corporate standpoint, the use of FedNow is not just about being able to pay faster; it can be about paying slower or determining the last possible moment a payment must go out. For businesses that pay millions of dollars day in and out, holding onto money until it must be paid can amount to earnings.

“If you have an invoice with advantageous terms to pay at a certain time, you want to submit at last possible moment,” Press said. “FedNow gives you a lot of control over when precisely you pay. If those same invoices are paid over ACH, there’s some uncertainty to that.”

Retail merchants and others who want to offer consumers an instant-payment option will have to work with their payment providers, such as FISFiservJack Henry and Q2 to ensure the point-of-sales (POS) system has the proper APIs and ensure their systems are properly connected.

The FedNow instant-payment system will use the new ISO 20022 global financial messaging standard, meaning banks will need to be sure they can submit messages in that format. Many banks may already have the ability to submit messages through ISO 20022, because FedNow is actually the second real-time payment system.

In 2017, a consortium of banks called The Clearing House launched the Realtime Payments network or TCH RTP. But the network failed to achieve wide adoption because smaller banks were wary of using a payment system backed by their larger competitors. However, TCH RTP does use the ISO 20022 standard.

At its core, FedNow serves as an interbank instant-payment infrastructure. Banks, credit unions, and other eligible institutions have accounts at the Federal Reserve that allow them to hold reserves. Banks pay each other by transferring reserves from the paying bank’s Fed account to the receiving bank’s Fed account using several interbank payment options. FedNow is a new addition to the suite of options to make such transfers.

Sam Aarons, co-founder and CTO of middleware payments provider Modern Treasury, said the payments industry is excited about the promise of FedNow. Modern Treasury provides the translation layer for corporate accounting systems to transfer funds over a network using API calls systems. Bank systems are sorely outdated, however, and still rely on technology from the 1970s and 1980s.

"That’s also why Modern Treasury is excited about FedNow, because it is going to force a lot of people into figuring out what is a modern technology stack for payments," Aarons said. "As I like to say, what is a business day if money can arrive and leave your bank account 24/7, 365 [days a year]? Are you going to have accountants stay up at midnight to close the books? You need to change the software for your company that’s looking at the precipice of that."

While integration with FedNow is one issue, moving payment systems to be real-time is the bigger problem, according to Aarons.

"Where we usually see the hiccups is in fraud checking and [Know Your Customer]," he said. "A lot of those systems throw up a red flag when there's a questionable transaction, and then you have a day and a human can look at this payment. When you’re trying to send out payments in 10 seconds, you have to automate that or make your decision quickly. 'Yes, I can send this out,' or 'No, I can’t send this out.'"

A gig worker’s dream

One advantage to using FedNow is that organizations who employ gig or hourly workers can pay them at the end of a shift because the money transfers instantaneously. Today, when a gig worker is paid, it’s through a credited system and the actual money doesn’t transfer from bank to merchant until the next day. Gig workers, however, will need a bank account to be paid, versus a payroll debit card as many use today.

The United States is a follower in rolling out a central bank-based instant payment system. Forty to 50 other countries have already implemented same-day payment systems — and their uptake was fast, quickly reaching nearly ubiquitous use.

For example, Brazil’s Central Bank launched the Pix instant payment system in 2020; within a year, it had reached more than 100 million users and today it serves more than 150 million people. That suggests FedNow will be quickly adopted across banking and business sectors.

There’s a good reason for the quick uptake. When businesses are making thousands of payments a day to distributors and suppliers, it behooves everyone to get their money faster. Like Brazil's Pix, FedNow will allow companies to pay vendors, contractors, or any business partner instantly. And it will enable better cash-flow management because funds are instantly available, allowing for faster reinvestment.

Because most US companies now use the ACH system to make and receive payments, they experience next-day clearing for batch transfers, or they pay extraordinarily high fees for faster wire transfers

"FedNow represents huge advances for the businesses of today that are moving money around," Aarons said. “FedNow is an opportunity to deliver a great consumer experience, but also one for banks as well. It’s a really good opportunity for the US to catch up with the rest of the world.

"I think there's going to be a big lift-off when FedNow launches, and the hope is to get to universal coverage that we have with ACH and wire," Aarons said.

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September 13, 2026
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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.
 
 

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