Finance
Jim Justice Tied West Virginia Coal to Global Financial Capital
West Virginia governor James C. Justice II seeks to fill the Senate seat left open by Joe Manchin’s retirement. “Big Jim” Justice, like Manchin, is a coal executive and former Democrat. But in contrast to Manchin’s run-of-the-mill crony capitalism, Justice has pursued innovative business practices that pushed the mines of West Virginia deep into the grasp of global financial capital.
Justice did it, he says, to keep his mines open and his businesses out of bankruptcy. But Justice’s strategy has meant that a string of unrelated third parties — JPMorgan, a Russian steel oligarch, Credit Suisse — get a little bit richer every time a coal miner goes to work for Justice. And West Virginians — local governments, Justice’s miners, small businesses, and local banks — hold the bag. If this is the way to stay out of bankruptcy, Justice’s prescribed treatment is worse than the illness.
How did Big Jim make such a big mess, and why? To be fair, it is not all his fault. Jim Justice’s business fortune, like the fortune of West Virginia itself, is impossible to understand without reference to the ups and downs of global commodity markets. Dealing with these commodity cycles has been the central preoccupation of the coal business for several decades. If the unemployment rate is the most important economic indicator for the world’s industrial regions, the price of commodities is the most important economic indicator for its resource-extraction regions.
Justice is a creature of resource extraction. Justice’s money comes from two sources: coal and agriculture. He inherited his stake in both the coal and agriculture industries from his father. Both coal and farming are commodity businesses.
The price fluctuation of coal has several implications for those who want to make money mining it. Coal mines are not all created equal and can be broadly sorted into two classes. There are mines that are highly productive, typically meaning that they are highly mechanized with expensive “longwall” mining machinery imported from Germany. These mines usually continue to operate when coal prices drop because their labor inputs are low and their capital costs (interest payments) remain the same whether the price is high or low. High-productivity, mechanized mines are typically operated with union labor.
Then there are low-productivity mines — sometimes called “doghole” mines. Smaller and less mechanized dogholes tend to shut down when the price of coal drops. Doghole mines close because their marginal cost (that is, the cost that they have to spend to mine an additional ton of coal) is higher than that of the high-productivity mines. The existence of doghole mines ensures that the price of coal does not rise too high. Doghole mines don’t require large investments, which means that when the price of coal rises above normal, a whole host of them open up. Doghole mines are typically nonunion.
Throughout most of the twentieth century, many large, high-productivity mines were owned and operated by large industrial corporations that consumed coal, like US Steel, Ford, and others. When demand for their goods increased, they didn’t open new mines; rather, they turned to the market and purchased coal from the doghole mines. During the industrial downturn of the 1970s and 1980s, this system of major, company-owned mines began to break down. Changes in the geography of world industrial production led to the decline of domestic coal-consuming industries. US Steel and similar companies stopped investing in coal production and shed their coal assets.
A new class of coal companies stepped in to develop and operate the expensive, high-productivity mines. Pure-play coal companies like Massey and Peabody expanded rapidly into central Appalachia in the 1980s. Bluestone Industries, owned by Big Jim’s father, was part of this growth.
Unlike the older major producers, the new companies engaged in both high-productivity and doghole mining — a business strategy that mitigated against the fluctuations in the price of coal. Owners of high-productivity mines had never been able to see the full benefits of their investments because the doghole mines kept prices relatively low during coal booms. For a company like US Steel, this had not been a problem. US Steel was not looking to make money mining coal. It was looking to secure a reliable supply of coal. The new companies, including the Justice family’s Bluestone, had different incentives.
As the major industrials exited coal production and left the mining business to Massey, Peabody, Bluestone, and other coal-exclusive businesses, the problem of how to increase profit margins during upswings became acute. The answer was to innovate a new method of mining that combined the low capital intensity of the doghole mine with the low marginal cost of the high-productivity mine.
That method was mountaintop removal. Mountaintop removal is exactly what it sounds like: a process of removing a mountain top — “overburden,” in industry speak — so that coal can be mined with bulldozers and front loaders rather than expensive, specialized underground mining equipment. Mountaintop removal could not fully match the cost efficiency of a well-run, highly mechanized underground mining operation, but it certainly beat the older small-scale, low-productivity mines — sometimes called “doghole” mines — that it succeeded. And it beat high-intensity mines on capital cost: big trucks, bulldozers, front loaders, and dynamite are cheaper and more liquid than specialized underground mining equipment. Mountaintop removal is far more environmentally destructive than other methods of mining coal.
By the 2000s, the benefits of that companies like Massey, Peabody, and others derived from mountaintop removal and the diversification of mining interests had played out. They succeeded in taking control of the coal market away from the large industrials, but the inevitable question of question of how this new arrangement might fare in a volatile coal market was unanswered.
In 2009, the problem was a high price. Justice decided to sell out. He found a buyer in the Russian steelmaker Mechel, which, like many large Russian industrial concerns, maintained close ties to Vladimir Putin and, unlike most American industrials, was growing. The sale of Bluestone’s assets to Mechel went through in 2009, before the financial crisis hit the commodity markets. Bluestone’s coal assets received a high price: $425 million and preferred shares in Mechel.
Justice was riding high: he subsequently purchased the ailing luxury Greenbrier resort in White Sulphur Springs, West Virginia, a longtime haunt of the Washington elite. Justice relished the company that he could keep as the owner of a big fancy hotel with a large bank account.
But the party didn’t last long. By 2015, the financial crisis had hit the commodity markets. The coal market was sluggish, and global industrial demand (excluding China) recovered very slowly. Mechel, holding what was at that point a money-losing business, sold the properties back to the Justice family for $5 million paired with per-ton royalty payments on future coal sales.
Five million dollars was a low price, but it probably wasn’t low enough. The properties were saddled with delayed upkeep and unpaid invoices. When Big Jim resumed leadership of the Bluestone coal assets, the old problems of navigating a coal company through commodity cycles resumed. Justice did not want to pull money from any corner of his business empire in order to operate his coal business in a sluggish market. So he turned to the burgeoning world of shadow banking that had grown up in the era of low interest rates.
Justice has since defaulted on the royalty payments, landing him in court. A judge recently ordered the seizure of one of the Justice family helicopters that Big Jim’s son Jay regularly taxied around Beckley, West Virginia. (Justice’s Democratic opponent in this year’s Senate race has suggested that Justice’s ongoing legal entanglement with Mechel could compromise his ability to serve as a US Senator.)
To solve the financial problem created by the repurchase of its coal properties, Bluestone found a partner in Lex Greensill of Greensill Capital. In the Donald Trump era, Greensill Capital was a darling of the transatlantic banking world. Lex Greensill was himself deeply familiar with global commodity markets, having grown up on a sugarcane farm in Queensland, Australia (which also grew watermelons, he likes to add in a folksy flourish). He moved to London in the heady days before the financial crisis, where he worked for Morgan Stanley and Citigroup.
Founded in 2011, Greensill Capital was an “innovative” supply chain lender. Supply chain lending is a straightforward business. Sellers of goods like Bluestone make deliveries of their goods and then issue invoices to the purchaser, which are usually due sixty days from delivery. Supply-chain lending is a very useful tool for a business that has liabilities that recur regularly but have uneven payment. That business, say Foxconn, might need to take out a loan to expand its operation to produce a large shipment of iPhones. Foxconn would invoice Apple after the delivery and could expect to be paid at some point in the coming months, but it might already have interest payments due on the loan. Enter supply chain finance to smooth the cash flow problem. Foxconn could take a copy of their invoice to Greensill and get cash now.
The fees and interest rates that Greensill regularly charged on transactions like these were quite high. In the low-interest-rate environment of the late 2010s, Greensill was able to borrow money at low rates and return a much higher rate on this kind of supply chain financing. With this model, Greensill attracted enormous investments. The largest private investment fund in the world, SoftBank’s Vision Fund (funded by the Saudis), contributed $1.5 billion to the business, seeking the high returns that Greensill could generate. Greensill quickly started to roll out supply chain financing to companies like Bluestone.
Only some companies are well-suited for supply chain finance; Bluestone is not one of them. Unlike an Apple iPhone supplier, Bluestone does not go deeply into debt in order to finance coal shipments. Thanks to the changes brought about by mountaintop removal, coal mining is now an asset-light business. Expansion of mining operations ought not to impose major financial obligations. A partnership with Greensill was incorrect on the fundamentals.
Nevertheless, over the course of five years, Greensill lent Bluestone $850 million. As their relationship deepened, the loans morphed from clear-cut supply chain finance (wherein Bluestone simply got payment earlier than they might for coal that had been already shipped) into something else. As Bloomberg’s Matt Levine has reported, based on court documents, Bluestone started submitting and Greensill started accepting invoices for coal that had not been shipped. In fact, it had not even been mined, or even ordered from any coal customer whatsoever.
Justice’s strategy stood in stark contrast to all of his competitors in the coal business, which fell like dominoes to bankruptcy. Following a methane explosion that killed twenty-nine miners in 2010, Massey was acquired by Alpha Natural Resources. Alpha went bankrupt in 2015 along with the two largest coal companies in the nation, Peabody and Arch.
The short-term effect of Bluestone’s relationship with Greensill was to allow the Justices to continue operating without very much attention to their profit margin. Greensill treated Bluestone like a growth tech stock. To convince Greensill to continue lending, all Bluestone and the Justices had to do was invent future growth prospects.
For a coal company, the idea that one should run a deficit in the short term with the hope of future growth — the logic of tech company finance — is silly. It is silly not because betting on coal mining growth in the context of global warming is a bad bet. (It is a bleak, nihilistic bet, but it may win the day.) What makes the structure of the Greensill-Bluestone relationship incorrect, rather, is the idea that future profits in coal mining require running present-day losses. There is little reason to think that, should the market take an upswing, Bluestone would be particularly well-placed to take advantage of that upswing simply because it had continued operating when it perhaps should not have. And yet that was an implicit assumption of the relationship.
Despite its obvious flaws, that assumption would never be tested. As the consequences of the COVID-19 pandemic wound through the financial system, Greensill faced increased scrutiny from lenders and insurers. Credit Suisse froze $10 billion in funds linked to the company in March of 2021. Greensill went belly-up soon after. The loans that had been made to Bluestone by Greensill were now picked up by others, including the Swiss bank UBS.
In the process of tying Bluestone to Greensill, the Justice family made a huge fiasco, not just for Bluestone Industries but for West Virginians.
Bluestone has a tendency to stiff those who send them an invoice or a time card. The debt to Greensill made the problem worse. Today, among the myriad parties seeking overdue payment from Bluestone is Wyoming County, West Virginia. Wyoming County is a coal county, population 20,527, where the median income is $20,607. In recent years, when it wasn’t using COVID money from the federal government, Wyoming County’s school board has been balancing its budget by selling its property after shuttering schools and offices. In part due to the inability of local governments to fund it appropriately, the local jail is a death trap, with suicides and murders (perpetrated by both inmates and correctional officers) at extraordinarily high levels. Bluestone owes hundreds of thousands of dollars in taxes (largely tangible property tax, presumably levied on mining equipment) to Wyoming County.
Justice laments the fact that he regularly pays Russian taxes before he pays West Virginia taxes, but he defends his financial strategy: “If you’re really fair and you’ll step back from it, you’ll say ‘Well, when things were really tough, why didn’t they take bankruptcy like every coal company almost in the land that was in trouble that wrote off hundreds and hundreds of millions, if not billions of dollars.’ And we didn’t do it.”
Bluestone has not yet declared bankruptcy. Beyond that, much is muddy: Why should Swiss bankers, Saudi princes, and Russian oligarchs get paid before Wyoming County teachers? Because Bluestone Industries just didn’t want to declare bankruptcy?
Finance
How Natura &Co Is Transforming Finance with Generative AI on SAP S/4HANA
For a company navigating one of the most consequential transformations in its history, financial clarity is not optional—it is essential. Natura &Co, the Brazilian personal care and cosmetics group behind iconic brands such as Natura and Avon, has long been committed to combining purpose-driven business with commercial performance. After a period of strategic portfolio reshaping, including the divestiture of its Aesop and The Body Shop holdings, the company is now sharpening its focus on profitability and operational excellence across Latin America and global markets.
At the center of that effort sits a deceptively complex challenge: understanding, in real time, which revenue and cost factors are driving or eroding gross margin across a highly diversified business. For years, answering that question meant manual reporting, delayed insights, and finance teams spending valuable time on data gathering rather than analysis.
That’s now changing, thanks to a co-innovation initiative developed together with SAP and Numen, a global SAP partner specializing in digital transformation and enterprise software implementation.
From manual reporting to proactive decision intelligence
The project’s goal was to replace a labor-intensive gross margin analysis process with a generative AI application embedded directly into Natura &Co’s financial workflows. Built on SAP Business AI Platform, SAP’s unified foundation integrating business technology, data, and AI capabilities, the application connects directly to data in SAP S/4HANA to provide finance teams with automated insights and narrative recommendations in real time, without the need for manual data pulls or offline reporting.
The application enables users to explore revenue, cost, and margin drivers interactively, identifying at a glance which elements are protecting or eroding margin performance across markets and product lines. Crucially, human oversight remains central to the design: the AI application generates insights, while finance professionals retain full control over interpretation and decisions.
“The implementation of gross margin analysis using AI in SAP S/4HANA marked an inflection point in the analytical capability of our finance area,” said Rogério Dias Garcia, tech manager, ERP Latam, Natura &Co. “We overcame delays and raised the standard of insights by integrating margin analysis from SAP S/4HANA with a large language model connected via the SAP AI Core layer. This architecture allowed us to provide, in an agile, secure, and completely anonymous manner, a stratified and precise view of gross margin offenders and protectors—discriminating exactly which revenue or cost elements were driving market performance.”
A collaborative architecture for scalable AI adoption
Natura &Co’s application derived from a prototype SAP partner Numen created in early 2024 at SAP’s global Hack2Build on business AI, leveraging the generative AI capabilities of SAP Business AI Platform. The solution was designed and developed through close collaboration between Natura &Co, Numen, and SAP. From the outset, the approach was to align AI adoption with concrete business priorities, ensuring the application would be scalable and production-ready rather than a standalone prototype.
Numen brought deep SAP implementation expertise to the project, combining knowledge of SAP S/4HANA architecture with hands-on experience in building solutions on SAP Business AI Platform. The technology stack—SAP S/4HANA, SAP AI Core, SAP Fiori, and SAP Business Technology Platform—provided the secure, integrated foundation needed to connect financial data with generative AI capabilities in an enterprise context.
“SAP enabled the transformation by providing the technological foundation and expert support,” said Carlos Aravechia, head of Data Design & Intelligence at Numen.
The success of the project has validated a broader conviction at Natura &Co: that generative AI, embedded directly in ERP workflows, can fundamentally reposition finance from a transactional function to a strategic business partner.
A blueprint for other businesses
The Natura &Co project demonstrates a pattern that other organizations can replicate, particularly those running SAP S/4HANA. The combination of structured ERP data with the contextual reasoning capabilities of large language models creates a foundation for decision intelligence that goes well beyond traditional business intelligence tools.
The project was built within a six-month co-innovation sprint and went live in August 2025. It is currently in use across Natura &Co’s Equador operations.
Looking ahead, Natura &Co is already planning the next phase: integrating Joule Agents to further automate the extraction of standard analytical content and deepen the AI-driven optimization of financial processes.
“The success of this initiative validates the transformative potential of embedded AI within our ERP,” Dias Garcia noted. “We are now ready to move forward—deepening these insights and integrating the capability of Joule Agents to maximize the extraction of standard content and further optimize our business decisions.”
For SAP customers evaluating how to move from AI experimentation to AI in production, the Natura &Co project offers a concrete, replicable model: start with a high-value, well-defined business process, embed AI directly into existing workflows, and build in human oversight from the start.
Finance
Low-income Chinese girl aces gaokao, inspires live-streamers offering help
A girl from a disadvantaged rural family in central China topped this year’s gaokao, attracting numerous live-streamers eager to finance her education, which she declined.
The home of 18-year-old secondary school graduate Han Yaping in a Henan province village was recently bustling with live-streamers.
This attention came after Han achieved an impressive score of 699 out of 750 in the gaokao, China’s national college entrance exam.
She has received offers from China’s two leading universities, Tsinghua University and Peking University.
Han’s accomplishment is particularly remarkable given her family’s impoverished circumstances.
Her mother suffers from ankylosing spondylitis, an inflammatory arthritis affecting the spine, preventing her from working. Her father, who earns a living through farming and odd jobs, serves as the family’s sole provider. Han also has a younger sister.
Finance
UK financial regulator publishes landmark AI review
The UK’s Financial Conduct Authority (FCA) published a landmark review on Monday that proposes recommendations to regulate the impact of artificial intelligence (AI) on the financial decisions made by consumers.
The review, titled the Mills Review, anticipates that both consumers and firms will start delegating “more financial decision-making to AI systems,” including for agreements, initiating transactions, and executing decisions “within agreed parameters.” One of the key findings of the review outlined that while AI can help bridge advice gaps and “support growth,” there remain risks “associated with fraud, cyber security, and consumer harm.” Conducting the review, Sheldon Mills highlighted that “AI can also amplify risks: bias, discrimination, exclusion, opaque decision-making (particularly when multiple AI models interact), misleading or hallucinatory advice and erosion of consumer trust.”
The review stated that presently, one in five adults in the UK are “already open to AI making decisions for them,” particularly when decisions feel “complex or high stakes.” It found that roughly 26 percent of the population “trust general-purpose tools such as ChatGPT, Claude or Gemini for financial advice” with little awareness that such platforms provide no “formal routes to recourse” or protections.
Overall, the Mills Review identified four areas that it anticipates will be impacted by AI in the financial sector: “the transformation of firms,” “new consumer journeys,” “a reshaped competition landscape,” and “amplified financial crime and cyber risk.” The FCA projected the shift in how consumers and firms consult AI to take place by 2030.
The Mills Review put forth seven “priority” recommendations to be considered by the FCA Board. It recommended that any transitions to autonomous AI models be monitored and that regulatory frameworks and perimeters be adapted and secured. The review called for the strengthening of “system-wide coordination and oversight,” the scaling up of the FCA’s AI Lab to enable it to support AI models and innovation for agentic finance, and an “AI-enabled agentic supervisory model” to be built and adopted. Finally, it recommended that a trusted “public-interest AI-enabled financial capability service” be developed.
The FCA announced, in the press release, that it will launch an AI “good and poor practice publication” in late 2026.
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