More than 75% of City firms now use AI, with insurers and international banks among the biggest adopters. More than 75% of City firms now use AI, with insurers and international banks among the biggest adopters. UK exposed to'serious harm' by failure to tackle AI risks, MPs warn Consumers and the UK financial system are being exposed to "serious harm" by the failure of government and the Bank of England to get a grip on the risks posed by artificial intelligence, an influential parliamentary committee has warned. That is despite looming concerns over how the burgeoning technology could disadvantage already vulnerable consumers, or even trigger a financial crisis, if AI-led firms end up making similar financial decisions in response to economic shocks. More than 75% of City firms now use AI, with insurers and international banks among the biggest adopters.

The question isn't whether the AI bubble will burst - but what the fallout will be Will the bubble ravage the economy when it bursts? What will it leave of value once it pops? The California Gold Rush left an outsized imprint on America. Some 300,000 people flocked there from 1848 to 1855, from as far away as the Ottoman Empire. Prospectors massacred Indigenous people to take the gold from their lands in the Sierra Nevada mountains. And they boosted the economies of nearby states and faraway countries from whence they bought their supplies.

We investigate the application of large language models (LLMs) to construct credit networks from firms' textual financial statements and to analyze the resulting network structures. We start with using LLMs to translate each firm's financial statement into a credit network that pertains solely to that firm. These networks are then aggregated to form a comprehensive credit network representing the whole financial system. During this process, the inconsistencies in financial statements are automatically detected and human intervention is involved. We demonstrate that this translation process is effective across financial statements corresponding to credit networks with diverse topological structures. We further investigate the reasoning capabilities of LLMs in analyzing credit networks and determining optimal strategies for executing financial operations to maximize network performance measured by the total assets of firms, which is an inherently combinatorial optimization challenge. To demonstrate this capability, we focus on two financial operations: portfolio compression and debt removal, applying them to both synthetic and real-world datasets. Our findings show that LLMs can generate coherent reasoning and recommend effective executions of these operations to enhance overall network performance.

The financial sector, a pivotal force in economic development, increasingly uses the intelligent technologies such as natural language processing to enhance data processing and insight extraction. This research paper through a review process of the time span of 2018-2023 explores the use of text mining as natural language processing techniques in various components of the financial system including asset pricing, corporate finance, derivatives, risk management, and public finance and highlights the need to address the specific problems in the discussion section. We notice that most of the research materials combined probabilistic with vector-space models, and text-data with numerical ones. The most used technique regarding information processing is the information classification technique and the most used algorithms include the long-short term memory and bidirectional encoder models. The research noticed that new specific algorithms are developed and the focus of the financial system is mainly on asset pricing component. The research also proposes a path from engineering perspective for researchers who need to analyze financial text. The challenges regarding text mining perspective such as data quality, context-adaption and model interpretability need to be solved so to integrate advanced natural language processing models and techniques in enhancing financial analysis and prediction. Keywords: Financial System (FS), Natural Language Processing (NLP), Software and Text Engineering, Probabilistic, Vector-Space, Models, Techniques, TextData, Financial Analysis.

Throughout history many traditions have believed that some fatal flaw in human nature tempts us to pursue powers we don't know how to handle. The Greek myth of Phaethon told of a boy who discovers that he is the son of Helios, the sun god. Wishing to prove his divine origin, Phaethon demands the privilege of driving the chariot of the sun. Helios warns Phaethon that no human can control the celestial horses that pull the solar chariot. But Phaethon insists, until the sun god relents. After rising proudly in the sky, Phaethon indeed loses control of the chariot. The sun veers off course, scorching all vegetation, killing numerous beings and threatening to burn the Earth itself. The gods reassert control of the sky and save the world. Two thousand years later, when the Industrial Revolution was making its first steps and machines began replacing humans in numerous tasks, Johann Wolfgang von Goethe published a similar cautionary tale titled The Sorcerer's Apprentice. Goethe's poem (later popularised as a Walt Disney animation starring Mickey Mouse) tells of an old sorcerer who leaves a young apprentice in charge of his workshop and gives him some chores to tend to while he is gone, such as fetching water from the river. The apprentice decides to make things easier for himself and, using one of the sorcerer's spells, enchants a broom to fetch the water for him.

Financial crimes fast proliferation and sophistication require novel approaches that provide robust and effective solutions. This paper explores the potential of quantum algorithms in combating financial crimes. It highlights the advantages of quantum computing by examining traditional and Machine Learning (ML) techniques alongside quantum approaches. The study showcases advanced methodologies such as Quantum Machine Learning (QML) and Quantum Artificial Intelligence (QAI) as powerful solutions for detecting and preventing financial crimes, including money laundering, financial crime detection, cryptocurrency attacks, and market manipulation. These quantum approaches leverage the inherent computational capabilities of quantum computers to overcome limitations faced by classical methods. Furthermore, the paper illustrates how quantum computing can support enhanced financial risk management analysis. Financial institutions can improve their ability to identify and mitigate risks, leading to more robust risk management strategies by exploiting the quantum advantage. This research underscores the transformative impact of quantum algorithms on financial risk management. By embracing quantum technologies, organisations can enhance their capabilities to combat evolving threats and ensure the integrity and stability of financial systems.

House Speaker Mike Johnson met with OpenAI CEO Sam Altman at the U.S. Capitol on Thursday to discuss what kind of role Congress has to play in legislating on artificial intelligence. "It was a very good meeting," Johnson told reporters afterward. "We talked about where we are with regard to the approach of Congress to AI." He said they had a "very thoughtful discussion" about how the Senate and House can forge a bipartisan path forward. House Speaker Mike Johnson, left, and OpenAI CEO Sam Altman.

Financial regulators in the United States have named artificial intelligence (AI) as a risk to the financial system for the first time. In its latest annual report, the Financial Stability Oversight Council said the growing use of AI in financial services is a "vulnerability" that should be monitored. While AI offers the promise of reducing costs, improving efficiency, identifying more complex relationships and improving performance and accuracy, it can also "introduce certain risks, including safety-and-soundness risks like cyber and model risks," the FSOC said in its annual report released on Thursday. The FSOC, which was established in the wake of the 2008 financial crisis to identify excessive risks in the financial system, said developments in AI should be monitored to ensure that oversight mechanisms "account for emerging risks" while facilitating "efficiency and innovation". Authorities must also "deepen expertise and capacity" to monitor the field, the FSOC said.

Artificial intelligence could cause a financial crisis with "catastrophic" consequences, according to the historian and author Yuval Noah Harari, who says the technology's sophistication makes forecasting its dangers difficult. Harari told the Guardian a concern about safety testing AI models was foreseeing all the problems that a powerful system could cause. Unlike with nuclear weapons, there was not one "big, dangerous scenario" that everyone understood, he said. "With AI, what you're talking about is a very large number of dangerous scenarios, each of them having a relatively small probability that taken together … constitutes an existential threat to the survival of human civilisation." The Sapiens author, who has been a prominent voice of concern over AI development, said last week's multilateral declaration at the global AI safety summit in Bletchley Park was a "very important step forward" because leading governments had come together to express concern about the technology and to do something about it.

The creators of AI bots that masquerade as people should face harsh criminal sentences comparable to those who trade in counterfeit currency, the Israeli historian and author Yuval Noah Harari has said. He also called for sanctions, including prison sentences, to apply to tech company executives who fail to guard against fake profiles on their social media platforms. Addressing the UN's AI for Good global summit in Geneva, the author of Sapiens and Home Deus said the proliferation of fake humans could lead to a collapse in public trust and democracy. "Now it is possible, for the first time in history, to create fake people – billions of fake people," he said. "If this is allowed to happen it will do to society what fake money threatened to do to the financial system. If you can't know who is a real human, trust will collapse. "Maybe relationships will be able to manage somehow, but not democracy," Harari added. The advent of ChatGPT and other large language models means AI bots can not only amplify human content, but also artificially generate their own content at scale. "What happens if you have a social media platform where … millions of bots can create content that is in many ways superior to what humans can create – more convincing, more appealing," he said. "If we allow this to happen, then humans have completely lost control of the public conversation.