Skip to main content

icnlive

WATCH LIVE. THINK BUSINESS.

© 2026 ICN.LIVE

ICN.live

  • The psychology of money, backed by research on money scripts, shapes results more than salary does.
  • Loss aversion, measured by Kahneman and Tversky in 1979, makes losing feel about twice as painful as winning feels good.
  • Sorting assets vs liabilities and buying back time move money in the right direction.
  • Three books, from Morgan Housel to Daniel Kahneman, map the field for readers who want depth.

The psychology of money decides more about a person’s finances than their salary ever will. Two people can earn the same and land in different places because the beliefs steering their choices differ. Financial psychologists have studied these patterns for decades. Some form in childhood. Others come from fear wired into the brain across thousands of years. The eight principles below pull from that research and from hard practice. Each names a habit that keeps people broke and the shift that turns it around. The last principle points to three books that go deeper than any short summary can. Read to the end for those.

Money scripts run before a person notices them

Every financial choice runs through a script most people never wrote. Researchers sort these subconscious beliefs into four money scripts. The first, money avoidance, treats wealth as something dirty, so a person undercharges and feels guilt about earning. Worship flips that, treating cash as the cure for every problem, so the chase never ends. Status ties self-worth to net worth, which pushes overspending to keep up appearances. Last comes vigilance, steady saving next to steady worry, even with plenty in the bank. Most people carry a blend, with one script leading. Each forms in childhood, often before a kid can define money at all. A child who hears that rich people are greedy stores that line and acts on it decades later. In the psychology of money, spotting the dominant script is step one, because a belief nobody can see keeps steering the wheel without any resistance.

Self-image sets a wealth ceiling

Limiting beliefs about money set a ceiling on income that ability alone cannot break. A person who sees themselves as a $100,000 earner tends to defend that number without meaning to. Earn more, and lifestyle rises to swallow the extra. Fall short, and effort climbs until the familiar level returns. A $200,000 opening slips past anyone still picturing a $50,000 version of themselves. The cap sits in the self-image, not the market.

The psychology of money treats this ceiling as a belief, not a fact. Changing it starts with one honest sentence. Write down the current financial identity, whether that is overspender, chronic saver, or someone scraping by. Beside it, write a truer target, such as a person who builds and manages wealth with ease. Read both before each money decision. As the self-image widens, income tends to move with it. The shift is slow, and it holds.

Assets pay their owner; liabilities charge them

Robert Kiyosaki reduced wealth to one test in Rich Dad Poor Dad. An asset puts money in a pocket. A liability pulls money out. The wealthy stack assets. Middle-class buyers collect liabilities and file them under assets by mistake. A car loses value the moment it leaves the lot, then bills its owner for fuel, insurance, and repairs. Living in a home brings a mortgage, taxes, and upkeep with nothing coming back. A rental property pays every month. Skill courses pay back through higher earnings later. Judging assets vs liabilities before each purchase is where a working money mindset begins. Idle cash carries a quiet cost too. Money parked in a low-rate account loses ground to rising prices year after year. Even savings, left to sit, can slide toward the liability column. The question that reorders spending is short: will this pay back, or drain over time?

A scarcity mindset makes decisions worse

A scarcity mindset does more than sour the mood. When money feels finite, mental bandwidth shrinks and judgment drops. The brain fixes on the next bill and loses the long view. That wiring made sense long ago, when food supplies could run out. Money works differently. It is created every day, and the supply is not fixed. An abundance mindset asks a sharper question. Instead of how to protect what exists, it asks how to create more. That single reframe moves a person from defense to offense. Fear says wait. Possibility says invest. The switch does not come naturally, since humans lean toward caution by default. Training helps. Each time the mind reaches for I cannot afford this, the stronger move is to ask how the thing could be afforded at all. Small reframes, repeated, widen what feels possible.

Every loss can work as tuition

Loss aversion keeps more people poor than bad luck does. Daniel Kahneman and Amos Tversky measured it in 1979, and the finding still holds. Losing $100 hurts about twice as much as gaining $100 feels good. Kahneman later won the 2002 Nobel Prize in economics for the wider work. That imbalance explains a lot of stuck lives. People grip losing stocks and pray for a rebound instead of cutting the loss. Some sit in dead-end jobs because quitting feels like defeat. Others skip raises and dodge investing, since the fear of losing beats the pull of gaining. The cost can be steep.

A person might stay in a draining job two years too long, losing income, energy, and health, all to avoid the feeling of a loss. One fix reframes the setback. A failed venture becomes tuition for a lesson that pays later. Once the loss reads as a receipt for learning, it stops running the show.

Time matters more than money saved

Money multiplies. Time does not. That gap is why saving every dollar can quietly cost a fortune. Consider a worker worth $100 an hour. Two hours spent cleaning to avoid a $50 fee does not save $50. It burns $150, once the lost earning time is counted. Wealthy people run the math the other way. They hire help, buy back hours, and steer that time toward work worth far more. The habit does not require millions to start. Hiring a first assistant early frees a founder to chase revenue instead of chores. The rule scales down as much as up. Someone earning $60,000 a year works out to about $30 an hour, so low-value chores are worth handing off. Anyone can find the number. Divide annual income by roughly 2,000 working hours, and the rate appears. From there, the test is simple. Any task worth less than that rate belongs to someone else.

A new money mindset gets written down first

A money mindset does not change by wishing. It changes on paper, through a small daily act. The method is plain. Write the earliest money memory, then note what parents said and did with cash. That memory usually holds the original script. Once it sits in plain view, a new line can replace it, such as money is a tool for freedom and for helping more people. The same trick works for identity and for spending. List the last ten purchases, then mark each one as an asset or liability with full honesty. Patterns show up fast. Reading these notes before decisions retrains the reflex over weeks, not minutes. The point is not a burst of motivation. Repetition rewires the default, so the calm choice starts to feel normal. Behavior follows the script it is fed, so a better script pays off in time.

The three books worth reading on the psychology of money

Short summaries can point the way, but three books map the whole field. The Psychology of Money by Morgan Housel, published in 2020, sits at the top. It runs on 19 short stories and one core claim: that behavior beats intelligence when it comes to wealth. The book has sold more than 10 million copies worldwide. Thinking, Fast and Slow by Daniel Kahneman comes next. Kahneman, the Nobel laureate behind loss aversion, lays out the two mental systems that drive every money call, one fast and emotional, the other slow and deliberate.

The third pick is Your Money and Your Brain by Jason Zweig, from 2007. Zweig ties neuroscience to investing and shows why the brain chases risk and panics at the wrong moments. None of the three sells a slogan. Each leans on evidence, from Nobel-winning research to market history. Together, they cover the beliefs, the biases, and the brain chemistry behind spending and saving. The psychology of money makes far more sense after reading all three. One honest read can shift the next decision more than any raise.

TAGS

EXPLORE MORE ON:

Lamborghini Revuelto SV

The Lamborghini Revuelto SV launched Friday as a limited-edition hybrid version of the automaker’s V12 flagship, and the company is calling it the fastest, most powerful production car it has ever built. Only 1,963 will be made worldwide.

The number carries meaning. It marks the year Lamborghini was founded, a detail the brand has leaned on before with other limited runs. Buyers who secure one join a small club that tends to hold its value well after the sale.

What powers the Revuelto SV?

The Revuelto SV starts with Lamborghini’s naturally aspirated V12 engine and pairs it with three electric motors. Combined, the setup pushes output past 1,050 horsepower, enough to send the car from a standstill to 100 kph, or 62 mph, in 2.4 seconds. That places the Revuelto SV among the quickest production cars sold anywhere.

Alessandro Farmeschi, the Revuelto’s product line director, told CNBC the SV gives buyers a way to push further into what the platform can do. “The Revuelto SV gives our customers the opportunity to go beyond in terms of performance,” he said. He described the goal as building something race-oriented while keeping the experience fun rather than purely clinical.

The V12 remains central to that mission. Farmeschi pointed to engine sound as a defining part of what buyers expect from the brand. “The V12 has been the key since the very beginning, since the foundation of the company,” he said. The hybrid system adds power without pulling focus from that signature note.

Design changes built for the track

Lamborghini announced that beyond the powertrain, the Revuelto SV picks up sharper aerodynamic elements. Lamborghini reworked the fins, wings, and air intakes to direct airflow more precisely and generate added downforce at speed. A retuned suspension and new carbon-ceramic brakes back up the extra power, and a new Pilota driving mode unlocks a setup built specifically for track use.

The cabin follows the same theme. Lamborghini refitted the interior to feel closer to a race car or fighter jet cockpit than a road car. Buyers can choose sport seats built around a carbon shell, or step up to optional monocoque carbon fiber race seats. The latter trade some comfort for a more direct connection to the car, similar to what a driver would find in motorsport.

Pricing and demand for the Revuelto SV

The Revuelto SV starts at $741,172, a jump over the standard Revuelto that reflects both the added hardware and the limited production run. Lamborghini’s past limited editions have often sold out before the public even sees a formal announcement, and SV variants in particular tend to draw stronger demand and higher resale prices in the collector market.

Farmeschi framed the appeal beyond raw numbers. “When you buy a Lamborghini, you buy a Lamborghini because you want it, because you like it, you want to experience driving it, but also because it’s a car that keeps its value over time,” he said. For a car built in such small numbers, that combination of desire and scarcity tends to matter as much as the spec sheet.

Photo Credit: Lamborghini

Nvidia Lines Up $500 bn for AI Buildout

Nvidia just found $500 bn for AI buildout, and it didn’t have to write the check itself.

On Monday, the chipmaker announced memorandums of understanding with six of Wall Street’s biggest names: Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. The goal is to stand up independent compute financing platforms that pull in more than $500 billion in third-party capital, money that flows toward building the data centers running on Nvidia hardware.

Think of it like a mortgage for GPUs. Instead of a cloud provider or AI lab draining its own balance sheet to buy chips, an outside lender fronts the capital, and the GPU cluster itself, plus the revenue it generates, backs the loan. That’s the model Nvidia is pitching to the market this week.

Why $500 bn for AI Buildout Matters Now

Big Tech isn’t slowing down. Combined AI spending across the major players is on track to clear $730 billion this year alone. Every one of those dollars has to come from somewhere, and increasingly, that somewhere is outside the tech companies’ own books.

This is where Nvidia AI financing platforms come in. The arrangements are designed to widen access to Nvidia-based infrastructure for frontier AI developers, enterprises, governments and cloud providers. For the six financial firms, it opens a new kind of long-duration, usage-linked investment tied directly to compute demand rather than to a company’s broader credit profile.

Huang framed it plainly in Nvidia’s statement: “These financing platforms will help customers access scarce compute at scale and build the AI factories that will power every industry and country in the age of AI.” Nvidia also said the setup would create dedicated pools of capital at attractive rates, though it stopped short of naming a timetable or individual commitment sizes.

What This AI Infrastructure Financing Actually Looks Like

Here’s the part worth watching closely. Nvidia hasn’t disclosed which of the six firms will lend, which will insure, and which will package and resell the risk. KKR has already floated the idea of securitizing AI infrastructure revenue, carving it into pieces institutional investors can buy. BlackRock’s Larry Fink went further, comparing the setup to the early mortgage-backed securities market of the 1970s.

That comparison cuts both ways. Mortgage-backed securities eventually built a trillion-dollar market. They also became infamous decades later. Nobody is claiming AI compute financing will follow that same arc, but the analogy signals how seriously Wall Street is treating this compute financing opportunity.

Huang has also said Nvidia itself may back up to 25 percent of a given financing deal, which keeps the company financially tied to its own customer base. If demand for AI computing power cools, Nvidia isn’t fully insulated from that risk. It’s a partner in the platforms, not just a hardware vendor standing on the sidelines.

The Numbers Behind the $500 bn for AI Buildout Push

None of the six firms has confirmed exactly how much capital they’ll each put toward the effort. The $500 billion figure describes the target ceiling across all six platforms combined, not a jointly pooled fund sitting ready to deploy. Terms, borrowers and timelines remain, in Nvidia’s own words, still being worked out.

Still, the direction is clear. This is meant to be the first AI data center funding structure of its kind at this scale, built specifically around Nvidia’s ecosystem. BlackRock and Goldman Sachs both manage retirement and pension money, so if the platforms scale as planned, exposure to AI infrastructure debt could eventually touch retirement accounts most people never think to connect to a GPU order.

The Financial Times reported the deal first on Monday, with Reuters confirming shortly after. For now, the framework is set. The dollar figures, and the risk that comes with them, are still being written.

eRedCap live network test

e& UAE has completed an eRedCap live network test on its commercial 5G network, the first such test announced by any telecom operator. eRedCap, short for enhanced Reduced Capability, is a stripped-down version of 5G built for devices that do not need full 5G speed or power. The company said the result gives businesses and public bodies a practical way to move Internet of Things (IoT) equipment off older LTE technology and onto a 5G-native IoT platform.

What the eRedCap live network test showed

The eRedCap live network test ran on e& UAE’s live commercial network, not a lab setup. Engineers reached download speeds of up to 10Mbps on eRedCap devices while using a 5MHz slice of NR-FDD spectrum. A Data Transmission Unit, a module that sends device data across the network, confirmed the service worked from end to end. That narrow 5MHz channel matters. It keeps device hardware simple and cheap, which suits equipment made in large volumes.

eRedCap 5G IoT sits between two extremes. Full 5G handles phones and heavy data. Low-power options like NB-IoT handle slow trickles of data from simple sensors. Many devices fall in the middle. Smart utility meters, industrial sensors, fleet trackers, payment terminals, building systems, and some wearables need steady coverage and long battery life, not top speed. The technology targets that middle band. It runs on a 5G Standalone network, meaning a 5G core rather than one leaning on 4G underneath.

RedCap battery life is already improved on standard 5G. RedCap pushes it further. Because peak data rates stay low and the channel is narrow, a device can run 5 to 10 years on one battery, against 1 to 3 years for RedCap. That figure sits close to the low-power radio technologies many meters use today. On cost, coverage, and battery life, eRedCap matches LTE Cat-1 and Cat-1bis. That makes it an LTE Cat-1 replacement built for 5G, which matters as operators plan to switch off LTE and reclaim that spectrum.

What it means for enterprises

The step builds on earlier work. In 2024, e& UAE became the first operator in the Middle East and Africa to bring Ericsson’s 5G Standalone RedCap into a commercial network. eRedCap extends that effort to an even lower cost and power tier.

Abdulrahman Al Humaidan, Senior Vice President, Access Network Development at e& UAE, said eRedCap brings everyday IoT applications into the 5G era at the right cost, power, and coverage. He said proving the capability on a live commercial network gives utilities, manufacturers, logistics providers, and smart-city operators a credible path to scale connected devices and prepare for the shift beyond LTE. e& UAE’s eRedCap live network test points beyond a single demo.

The practical gain is fewer parallel networks to run. Firms can move more IoT use cases onto 5G Standalone instead of keeping separate paths for high-performance 5G and LTE-based devices. That can simplify how devices are managed over their lifetime and tighten security across large fleets. It also supports the long-term reuse of LTE spectrum, since not every device would need full 5G hardware to make the move. The eRedCap live network test gives that transition an early proof point on a working network.

Share this post

on your favourite social platforms

or copy the link