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Power of Payments Ep. 24: Talking FedNow and real-time payments with Bottomline’s Jessica Cheney
March 01, 2023
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  • Jessica Cheney, VP of Product – Digital Banking Solutions at Bottomline Technologies, joins host Ismail Umar on this week’s podcast.
  • She discusses the current state of adoption of real-time payments in the US, and how the launch of FedNow is going to impact the banking industry.

Welcome back to the Power of Payments podcast. I’m your host Ismail Umar, and today I’m joined by Jessica Cheney, VP of Product for the Digital Banking Solutions group at Bottomline Technologies.

Jessica has been with Bottomline for over a decade. Prior to that, she held similar roles at a number of other fintechs, and was also part of the commercial product management group at US Bank. She has been involved with real-time payments for many years now, and says she has a comprehensive outlook on how payments impact financial services from a commercial, fintech, and retail perspective.

In our conversation today, Jessica discusses the current state of adoption of real-time payments in the US, and how the launch of FedNow – the Federal Reserve's instant payment service – is going to impact the banking industry. She also talks about how SMBs can use real-time payments to improve their day-to-day operations, and the overall impact that RTP adoption will likely have on banks, businesses, and consumers in the coming years.

The following excerpts were edited for clarity.

I lead the product management function for the banking segment of Bottomline Technologies. I've been there for about 11 years now. Prior to that, I was in similar roles at other fintech companies – S1 and Clear2Pay, most notably. I’ve also worked directly in the financial services industry in several areas. I was part of the commercial product management group at US Bank, and led the retail group at Skowhegan Savings Bank. So I sort of have a very comprehensive perspective on how payments impact the financial services world from a commercial perspective, a fintech perspective, and a retail perspective. I've also been involved with real-time payments since its conceptual launch with the Federal Reserve, for several years now. That really sparked my interest with the Fed Task Force, and I've been really involved in the industry ever since.

Given your expertise, what would you say is the current state of adoption of real-time payments in the US compared to other parts of the world?

I think that, to answer that question, it really depends on how clinical we’re going to be in using the term ‘real-time payments.’ And that is a concept that's applicable in the US and throughout the world. The term is really an umbrella that covers many payment options, especially in the US: P2P payments from Zelle, Cash App, Venmo, Same Day ACH supported by NACHA, the Fed, and The Clearing House, RTP launched by The Clearing House in November 2017, and now FedNow launching the instant payment network that's coming live this summer. In general, to answer your question, I would describe this as an industry that’s continuing to grow, though a bit more slowly lately. The P2P space continues to drive most volume and growth. Zelle reported over 550 million transactions, representing the movement of over $155 billion in June. That’s a 27% growth from 2021. Venmo is reporting more than $63 billion moved in Q3, a 6% growth over their record year in 2021.

Now, Same Day ACH, and ACH in general in the US, is continuing to grow. It saw 6% growth in Q3, with Same Day seeing the most increase in use. There were 176 million Same Day ACH payments made. And that's a huge, 102% increase since Q3 2021. The RTP network has also seen huge growth, reporting 49 million transactions in Q4, moving about $22 billion, another 9% growth over Q3.

When I really dig into this a little bit deeper, though, I think that there are some things driving this. There's a recent American banking article that noted disbursements and rent payments are among the fastest-growing Zelle use cases. And that kind of indicates that more users are relying on Zelle’s speed to make last-minute billing deadlines. The number of companies including insurance providers, education and government agencies, using Zelle to transfer funds also dramatically increased, 87% in the second quarter of 2022, compared to the year before. So while all this growth seems impressive, I think the industry is actually on the brink of truly having breakout adoption. There’s a saying that goes, ‘A rising tide lifts all boats.’ This tide is growing in the RTP industry, aided by the FedNow launch, as well as more B2C and B2B adoption. The current economic condition is also ripe for assisting growth in real-time payments as personal and corporate liquidity management becomes more and more important.

Can you share your thoughts on the kind of impact FedNow is going to have on the financial industry?

The biggest thing is that the Fed has for a very long time been seen as the preferred payment network provider. And that's probably based on their perceived stability and competitive neutral reach to all financial institutions. The Clearing House, for example, has roughly 280 participating banks. The Fed has a built-in customer base of over 9000 financial institutions that FedNow will now be offered to. That sheer jump in volume of banks reached that will have access to real-time or instant payments will lead to a really game-changing adoption in the future. The launch of the FedNow service also removes the “let's wait and see” excuse that some banks have used when it comes to real-time payments. Many until this point have seen RTP as only the purview of the largest banks in the US. Just as an aside, The Clearing House members that were initial drivers of RTP, and those member banks, are among the largest in the US. What the launch of FedNow does is make RTP mainstream in America. The Fed and NACHA launched ACH and direct deposit in the mid-70s, and that helped make ACH mainstream. Today, 94% of Americans get paid that way. FedNow has the potential to do the same thing with real-time or instant payments.

Once FedNow is launched, do you expect to see rapid adoption of real-time payments in the US, or do you think it will slowly build up over time?

Unfortunately, I think at least the next couple of years, we will continue to see a little bit of a slow adoption curve. And then we will reach a major launching point where we will have critical mass in both receivers and senders of real-time transactions. Too many banks have waded into this pool as receivers only, and not enough have jumped into the deep end to be senders as well. And you really can't have a network that is full of receivers but not senders and be successful.

Another unknown factor in how much interoperability will occur between these two networks will really impact adoption. Once we know that, and though the interoperability between the two networks is established, that's the linchpin of growth going forward. The networks have both been set up for interoperability, and they’re using similar message sets, similar operating guidelines and value propositions. But actual interoperability remains to be improved between the two.

A key point here is that eventually, the demand that we're seeing in the P2P space will also push into the business payments space. That, along with FedNow's reach, will really push adoption rates along. When payments become mainstream, their value is more widely understood, and that obviously drives demand as well.

Do you think there is a sufficient level of awareness among American businesses about what adopting real-time payments would mean for them? And what do you think is most important for FIs and businesses to understand about adopting real-time payments?

Unfortunately, I think the comprehension level of the value of RTP remains low. I’ll share a story with you. I was talking to a CFO of a midsize fintech about RTP about 18 months ago. And his initial question to me was, ‘Why on earth would I want to pay invoice faster? I want to hold on to my cash.’ So I went on to explain that RTP is actually the liquidity and cash management tool that helps him do that better than any other payment type out there. RTP lets you wait till the absolute last minute to pay an invoice, and either take advantage of payment terms offered or to get shipments released and delivered when needed.

I think lots of energy is now going into the education and benefits for businesses to use RTP to make payments, and RFP, request for payments, to get paid. First and foremost, I think that RTP and RFP are key business operating tools for small businesses. They help with liquidity management, financial planning, customer service, and efficiencies in both the accounts receivable and accounts payable processes.

First of all, liquidity management. As I mentioned before, RTP allows small businesses who are managing their cash really tightly to make payments at the absolute last minute. Sure, they can be scheduled in advance, but when cash is tight and you need to pay a vendor just in time, RTP provides that. RFP, or request for payment, is the ability to send an electronic invoice and request a real-time payment in response. This can really streamline the invoice to collection process for any small business and aid in reducing collection time. It is also a very cost-efficient way to send electronic invoices. Many merchant services providers are now offering instant settlement, providing access to funds immediately, which helps small businesses meet their immediate cash flow needs. What these merchant services are doing is, at the end of any particular sales period, where the small business will close out their credit card sales for the day, the merchant service company is providing settlement to these small businesses via RTP. On the flip side of this, RTP can also be used for instant payroll, and it can help many small businesses attract employees in this highly competitive labor market.

The other part of this that I haven't really talked about before is the fact that real-time payments can also have an accompanying real-time acknowledgment, meaning a payment that has been made by RTP can be acknowledged by the receiver. And that can also aid in reducing some of the financial anxiety that many small businesses are facing when they make just-in-time payments.

How do you think the current macroeconomic conditions and market volatility will impact the adoption and effectiveness of real-time payments?

I think that it’s absolutely going to have an impact. We don't have to look too far to see proof of that. During the COVID-19 pandemic, the use of cashless, contactless, and real-time payments grew like crazy. You just have to look at the volumes from Zelle, Venmo, and Cash App to see that impact. But today's economic conditions are driving consumers and businesses away from wanting to use credit or credit cards as means of payment – the interest rate’s just way too high. Companies and consumers alike do need to wait till the last minute to make key payments for things like rent and utilities, but they also need the financial certainty that these last-minute payments have been acknowledged. And RTP can do that.

Looking into the future, what kind of impact do you think the adoption of real-time payments is going to have on banks, businesses and consumers in the coming years?

I really think that RTP is the next revolution in payments. I think it’ll be a soft change. We've evolved into real-time payments in the P2P space being mainstream. And that will continue to flow into the B2B and B2C aspects of this industry. Financial institutions are already making investments to take advantage of this. It’s just going to be the next expectation, just like the expectation we have that the phones we carry in our pockets are mini-computers and basically can do everything that we want to be done instantaneously. That's the natural evolution and the next wave of payments in the industry.

There's a couple of things that I did want to mention, though. I think that people get hung up on the speed of these payments. But there are other aspects of RTP that also add value. The added value to this also takes advantage of some of the other things that we've grown very accustomed to. And that’s the instant communication that goes along with these payment types. There’s the ability to have these real-time payments instantly acknowledged. There are communication vehicles built into the payment rails that allow the sender and receiver to communicate with each other about questions that they have, either about the amounts that have been received or the amounts that have been requested to be paid. Again, it kind of takes what’s become very mainstream in our personal lives, with the use of instant messaging and texting, and goes along with the natural change in payments that’s occurring. I think that's the key to why RTP is the next revolution in payments.

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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 notes, Massachusetts 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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