Business Architecture (BA) plays a significant role in helping organizations understand enterprise structures and processes, and align them with strategic objectives. However, traditional BAs are represented in fixed structure with static model elements and fail to dynamically capture business insights based on interna…
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arXiv research
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.
168,657 papers · 148 categories
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48 results for “business data”
Bayesian model uses mobile data to assess business resilience after hurricanes.
problem Evaluating economic impact of extreme shocks on businesses.
method Bayesian structural time series model with mobile phone data.
result Estimates business resilience after hurricanes, revealing key characteristics.
Large corporate credit models may be adapted for small business risk assessment.
problem Limited data and lack of credit analysts for small businesses.
method Adapting large corporate credit risk models for small businesses.
result Adapted models can predict small business credit risk effectively.
The study uses CoDa to analyze family business financial ratios, highlighting methodological issues.
problem Asymmetry, non-normality, and non-linearity in financial ratios of family businesses.
method Compositional data analysis (CoDa) and classical analysis strategies.
result Results are sensitive to the methodology used, emphasizing the need for appropriate methodologies.
Study shows credit expansion in mortgage markets influenced U.S. business cycle.
problem Lack of causal evidence in cross-country business cycle studies.
method Unique research design combining cross-metropolitan U.S. data.
result Credit expansion caused stronger booms and busts in house-related industries.
At the initial stages of this research, the assumption was that the franchised businesses perhaps should not be affected much by recession as there are multiple cash pools available inherent to the franchised business model. However, after analyzing the available data, it indicated otherwise, the stock price performanc…
The Prescriptive Canvas improves business outcomes by directly prescribing actions based on predictions.
problem Sub-optimal performance in business projects due to a two-step approach of prediction and decision-making.
method The Prescriptive Canvas methodology for framing and communicating actions directly based on predictions.
result Improves framing and communication across stakeholders for successful business impact.
Business cycles tend to comove across countries. However, standard models that attribute comovement to propagation of exogenous shocks struggle to generate a level of comovement that is as high as in the data. In this paper, we consider models that produce business cycles endogenously, through some form of non-linear d…
The biggest problem with the methods of machine learning used today in business analytics is that they do not generalize well and often fail when applied to new data. One of the possible approaches to this problem is to enrich these methods (which are almost exclusively based on statistical algorithms) with some intrin…
This paper introduces TDA and TSI for better business analytics.
problem Nonlinear, multi-scale business datasets under-represented by traditional tools.
method Topological Data Analysis (TDA) and Topological Stability Index (TSI).
result TSI reveals structural variability in business data.
New method improves prediction accuracy in business process mining by handling concept drift.
problem Improving prediction quality in business process mining affected by concept drift.
method Systematically analyzed and compared different data selection strategies for retraining machine learning models.
result Improved accuracy from 0.5400 to 0.7010 with concept drift handling.
Private business schools in India face a common problem of selecting quality students for their MBA programs to achieve the desired placement percentage. Generally, such data sets are biased towards one class, i.e., imbalanced in nature. And learning from the imbalanced dataset is a difficult proposition. This paper pr…
The accurate characterization of the business cycles in the nonlinear dynamic financial and economic systems in the time of globalization represents a formidable research problem. The central banks and other financial institutions make their decisions on the minimum capital requirements, countercyclical capital buffer …
A microscopic model of aggregation and fragmentation is introduced to investigate the size distribution of businesses. In the model, businesses are constrained to comply with the market price, as expected by the customers, while customers can only buy at the prices offered by the businesses. We show numerically and ana…
Paper assesses risks of stablecoins, from lending to business-to-business.
problem Credit risks in decentralized stablecoin issuance.
method Examines mechanisms, risks, and mitigation strategies at each layer.
result Potential for scaling stablecoins while maintaining systemic health.
Paper proposes a new method for learning business process representations.
problem Challenges in capturing all useful information in business process data.
method Combines Gramian Angular Fields and Convolutional Neural Networks for representation learning.
result Demonstrates effectiveness of the approach through visualization and multiple process prediction tasks.
We evaluate how modern outlier detection methods perform in identifying outliers in e-commerce conversion rate data. Based on the limitations identified, we then present a novel method to detect outliers in e-commerce conversion rate. This unsupervised method is made more business relevant by letting it automatically a…
DeFi TrustBoost uses blockchain and AI to assess small business loans.
problem Assessing small business loans from low-wealth households.
method Combines blockchain and Explainable AI to ensure confidentiality, compliance, and security.
result Tamper-proof auditing and on-chain/off-chain data storage for financial organizations.
We have created a framework for analyzing subscription based businesses in terms of a unified metric which we call SCV (single customer value). The major advance in this paper is to model customer churn as an exponential decay variable, which directly follows from experimental data relating to subscription based busine…
This review covers AI in finance, challenges, techniques, and opportunities.
problem Challenges and opportunities in AI applications in finance.
method Comprehensive categorization and overview of AI research in finance over decades.
result A dense roadmap of AI challenges, techniques, and opportunities in finance.
Deep learning faces adoption challenges in business analytics.
problem Adoption of deep learning in business analytics is hindered by various factors.
method Empirical study based on three industry use cases.
result Gradient boosting is recommended for structured datasets in business analytics.
Study evaluates sustainability of European banks using a new model.
problem Lack of a framework to evaluate sustainability of banking business models.
method Delphi-Analytic Hierarchy Process method to develop and assess the model.
result Norwegian and German banks have higher sustainability of their business models.
Business analytics refers to methods and practices that create value through data for individuals, firms, and organizations. This field is currently experiencing a radical shift due to the advent of deep learning: deep neural networks promise improvements in prediction performance as compared to models from traditional…
Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.
problem Optimizing business expansion under exposure constraints and opportunity costs.
method Formulated as a novel stochastic control problem combined with optimal stopping time, derived an explicit solution for exponential utility.
result Firms are incentivized to expand but may wait due to opportunity costs and other factors.
Machine learning predicts US and EuroZone business cycles with high accuracy.
problem Predicting the business cycle phases in US and EuroZone.
method Three machine learning approaches were compared: Multinomial Logistic Regression (MLR) achieved the best results.
result MLR achieved 65.25% accuracy for EuroZone and 75% for US in predicting business cycle phases.
We explore what causes business cycles by analyzing the Japanese industrial production data. The methods are spectral analysis and factor analysis. Using the random matrix theory, we show that two largest eigenvalues are significant. Taking advantage of the information revealed by disaggregated data, we identify the fi…
Generative AI agents improve ERP systems by automating complex financial tasks.
problem Static, rule-based workflows limit adaptability and intelligence in ERP systems.
method Introducing Generative Business Process AI Agents (GBPAs) that integrate generative AI with business process modeling and multi-agent orchestration.
result GBPAs achieve up to 40% reduction in processing time and 94% drop in error rate.
Study examines cyber losses across sectors, finds high severity and frequency.
problem Understanding the nature of cyber losses and their variability across sectors.
method Analysis of a leading industry dataset of cyber events, focusing on frequency and severity.
result Cyber risks are heavy-tailed, with high probability of extreme losses.
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…
Graph neural networks detect anomalies in object-centric business processes.
problem Detecting anomalies in graph-like business processes.
method Graph convolutional autoencoder architecture for anomaly detection.
result Promising performance in detecting anomalies at the activity type and attributes level.
The analysis of the theoretical material revealed the lack of consensus on defini-tion of the tax stimulation of innovation-active business entities within the re-gional taxation. The definition tax stimulation of innovation-active business en-tities is specified.
Business taxonomies are indispensable tools for investors to do equity research and make professional decisions. However, to identify the structure of industry sectors in an emerging market is challenging for two reasons. First, existing taxonomies are designed for mature markets, which may not be the appropriate class…
Adaptive Stress Testing detects financial fraud by simulating potential failures.
problem Detecting and mitigating vulnerabilities in financial systems.
method Developed a simplified model using historical data and reinforcement learning.
result Identified the most likely path to system failure and improved fraud detection.
Kaggle competitions offer valuable insights for business forecasting.
problem Lack of attention to Kaggle competitions in academic forecasting studies.
method Review of results from six Kaggle competitions featuring real-life business forecasting tasks.
result Global ensemble models outperform local single models in Kaggle competitions.
FinTech uses data science and AI to transform finance.
problem Transforming finance with data science and AI.
method DSAI techniques including complex system methods, quantitative methods, etc.
result DSAI enables smart FinTech for various financial sectors.
Examines international taxation's impact on Georgian businesses.
problem Impact of international taxation on Georgian business entities.
method Analyzes types, features, and approaches of international taxation.
result Provides recommendations to correct current taxation issues.
CONDA-PM framework helps analyze concept drift in business processes.
problem Analyzing changes in business processes over time.
method Systematic Literature Review and framework development.
result Highlights areas needing research to complement existing efforts.
Study examines how business units can benefit from group cohesion under regulatory constraints.
problem Regulatory constraints limit business units' ability to form a single cohesive group.
method Defined and analyzed cohesive risk measures to minimize capital costs.
result Cohesive risk measures allow groups to achieve minimal capital costs without altering individual liabilities.
This paper studies business cycle patterns in UK sectoral output. It analyzes the distinction between white noise processes and their non-white noise counterparts in the frequency domain and further examines the associated features and patterns for the process where white noise conditions are violated. The characterist…
Predicting the completion time of business process instances would be a very helpful aid when managing processes under service level agreement constraints. The ability to know in advance the trend of running process instances would allow business managers to react in time, in order to prevent delays or undesirable situ…
Development of efficient business process models and determination of their characteristic properties are subject of intense interdisciplinary research. Here, we consider a business process model as a directed graph. Its nodes correspond to the units identified by the modeler and the link direction indicates the causal…
The major study by Bordo and Helbing (2003) analyses the business cycle in Western economies 1881-2001. They examine four distinct periods in economic history, and conclude that there is a secular trend towards greater synchronisation for much of the 20th century. Their analysis, in common with the standard economic li…
New approach optimizes sales process for B2B businesses.
problem Optimizing the sales process for B2B businesses.
method Causal Predictive Optimization and Generation with three layers: prediction, optimization, and serving.
result Significant wins over legacy systems in LinkedIn implementation.
Company2Vec creates embeddings from company websites for fine-grained business analytics.
problem Lack of fine-grained company labels for analytics.
method Word2Vec and dimensionality reduction on company website data.
result Semantic company embeddings for various applications.
Business-cycles and Cash-on-Market: Pre-money Startup Valuation in the Macroeconomic Environmentq-fin.GN
Business cycles affect startup valuations, both directly and indirectly.
problem How do business cycles impact startup valuations?
method Structural Equation Model approach using a dataset of 1,089 venture capital investments.
result Business cycles impact startup valuations both directly and indirectly.
The aim of process discovery, originating from the area of process mining, is to discover a process model based on business process execution data. A majority of process discovery techniques relies on an event log as an input. An event log is a static source of historical data capturing the execution of a business proc…
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approachcs.CL
The study detects deceptive language in business communication using AI.
problem Deceptive language in business communication.
method Combining classical rhetoric, communication psychology, and linguistic theory with computational textual analysis and transformer models.
result Detection accuracies of over 99% achieved in controlled settings.
We propose a dynamical model for business cycle based on an optimal DI model. In the model there exists a conserved quantity, which corresponds to the total energy in a dynamical system. We found that the business cycle with the period 6 or 7 years is nicely reproduced, since the model predicts a periodic motion in the…