A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper assesses financial potential for enterprise development.
This paper surveys enterprise financial risk analysis from Big Data and LLMs perspectives.
This study identifies financial risk paths in digital-transformed enterprises.
This research develops a dynamic risk management system for industrial companies.
A new method to protect enterprise data privacy in AI models.
Paper proposes a method to evaluate SME credit risk using meta paths.
It was not until the beginning of the 1990s that the effects of information and communication technology on economic growth as well as on the profitability of enterprises raised the interest of researchers. After giving a general description on the relationship between a more intense use of ICT devices and dynamic econ…
Study combines intra-risk and contagion risk for SME bankruptcy prediction.
Graph neural networks improve SME credit risk assessment.
We present a macroeconomic agent-based model that combines several mechanisms operating at the same timescale, while remaining mathematically tractable. It comprises enterprises and workers who compete in a job market and a commodity goods market. The model is stock-flow consistent; a bank lends money charging interest…
For researching the association between coal enterprise management and return in financial market, this paper applies the method of time difference relevance and PageRank method to seek the leader-index of a stock set containing 21 coal enterprises in A-share market and score those stocks. Based on the return in 2011, …
Margin trading and short selling boost green tech innovation in China.
Networked-guarantee loans may cause the systemic risk related concern of the government and banks in China. The prediction of default of enterprise loans is a typical extremely imbalanced prediction problem, and the networked-guarantee make this problem more difficult to solve. Since the guaranteed loan is a debt oblig…
Study reveals holiday effect on China's time-honored brands, especially alcoholic beverages.
This study proposes a new model for predicting financial distress in SMEs using machine learning.
The paper shows supply chain features improve cyber risk prediction.
Analyzes 6M Python notebooks and 2M enterprise DS pipelines to guide investments in data science.
Chebyshev polynomials analyze Czech enterprises' stock dynamics.
SmallML predicts customer churn for SMEs with small data, improving accuracy by 24.2 points.
AI-driven framework improves enterprise financial audits and risk identification.
To assure cyber security of an enterprise, typically SIEM (Security Information and Event Management) system is in place to normalize security event from different preventive technologies and flag alerts. Analysts in the security operation center (SOC) investigate the alerts to decide if it is truly malicious or not. H…
Being one of the most important factors of economic growth of the country, innovations became one of the key vectors in Russian economic policy. In this field technology parks are one of the most effective instruments which can provide growth of innovative activity in sectors, regions and economies. In this paper, we m…
Investigates how FDI and R&D affect host countries' growth.
Generative AI agents improve ERP systems by automating complex financial tasks.
Paper proposes a semi-supervised learning approach for automated topic detection in support and feedback data.
The basic financial purpose of an enterprise is maximization of its value. Trade credit management should also contribute to realization of this fundamental aim. Many of the current asset management models that are found in financial management literature assume book profit maximization as the basic financial purpose. …
FinanceBench benchmarks LLMs on financial QA, revealing limitations.
Financial institutions face new model risks with AI, requiring enhanced model risk management.
In recent years, the interest in Big Data sources has been steadily growing within the Official Statistic community. The Italian National Institute of Statistics (Istat) is currently carrying out several Big Data pilot studies. One of these studies, the ICT Big Data pilot, aims at exploiting massive amounts of textual …
National statistical systems are the enterprises tasked with collecting, validating and reporting societal attributes. These data serve many purposes - they allow governments to improve services, economic actors to traverse markets, and academics to assess social theories. National statistical systems vary in quality, …
In the early phases of the product life cycle, the costs controls became a major decision tool in the competitiveness of the companies due to the world competition. After defining the problems related to this control difficulties, we will present an approach using a concept of cost entity related to the design and real…
Intel's system identifies and categorizes businesses for sales opportunities.
Study on insurance risk management and sustainable development.
Concurrent engineering taking into account product life-cycle factors seems to be one of the industrial challenges of the next years. Cost estimation and management are two main strategic tasks that imply the possibility of managing costs at the earliest stages of product development. This is why it is indispensable to…
Designed to compete with fiat currencies, bitcoin proposes it is a crypto-currency alternative. Bitcoin makes a number of false claims, including: solving the double-spending problem is a good thing; bitcoin can be a reserve currency for banking; hoarding equals saving, and that we should believe bitcoin can expand by …
This paper develops a federated approach to learn Granger causality in interdependent industrial clients.
Digital transformation boosts corporate financial asset allocation, especially short-term.
Paper presents a new method for better financial market forecasting.
Most of the existing solutions to enterprise threat management are preventive approaches prescribing means to prevent policy violations with varying degrees of success. In this paper we consider the complementary scenario where a number of security violations have already occurred, or security threats, or vulnerabiliti…
In this paper, we develop a new sequential regression modeling approach for data streams. Data streams are commonly found around us, e.g in a retail enterprise sales data is continuously collected every day. A demand forecasting model is an important outcome from the data that needs to be continuously updated with the …
The boom of deep learning induced many industries and academies to introduce machine learning based approaches into their concern, competitively. However, existing machine learning frameworks are limited to sufficiently fulfill the collaboration and management for both data and models. We proposed NSML, a machine learn…
New framework uses MABs for better WLAN performance.
Develops a deep learning framework to predict future tech directions for high-tech companies.
The basic financial purpose of a firm is to maximize its value. An inventory management system should also contribute to realization of this basic aim. Many current asset management models currently found in financial management literature were constructed with the assumption of book profit maximization as basic aim. H…
China integrates ESG into corporate strategy for sustainable growth.
We develop a real-time anomaly detection algorithm for directed activity on large, sparse networks. We model the propensity for future activity using a dynamic logistic model with interaction terms for sender- and receiver-specific latent factors in addition to sender- and receiver-specific popularity scores; deviation…
Emerging economies frequently show a large component of their Gross Domestic Product to be dependant on the economic activity of small and medium enterprises. Nevertheless, e-business solutions are more likely designed for large companies. SMEs seem to follow a classical family-based management, used to traditional act…
A method for sharing synthetic data without revealing actual data or model parameters.