Aims and Scope

Aims

The Journal of Intelligent Financial Systems and Autonomous Management is an international, peer-reviewed, open-access scholarly journal that publishes original research, systematic and methodological reviews, and short communications at the intersection of artificial intelligence and finance. The Journal serves as a platform for interdisciplinary, applied, and theoretically grounded scholarship that addresses the design, deployment, governance, and consequences of intelligent and autonomous systems in financial markets, institutions, and management practice.

The Journal aims to publish work that demonstrates originality, methodological rigor, reproducibility, and clearly articulated contributions to theory, practice, or policy. It welcomes both single-discipline studies of high methodological quality and interdisciplinary work that draws on computer science, finance, economics, operations, and management together.

Scope

The Journal's scope is organized around three subject domains. The areas listed below are indicative rather than exhaustive; submissions outside these examples but within the broad subject domains are welcome.

Intelligent Financial Systems

The Journal welcomes research on the application of artificial intelligence and data-driven methods to financial systems, including:

  • Algorithmic, high-frequency, and automated trading systems
  • AI-driven market, credit, liquidity, and operational risk analytics
  • Portfolio optimization, asset allocation, and robo-advisory systems
  • Machine learning for fraud detection, anti-money-laundering, and financial crime analytics
  • Regulatory technology (RegTech) and supervisory technology (SupTech)
  • Credit scoring, alternative-data lending, and automated underwriting
  • Decentralized finance (DeFi), blockchain, distributed ledger technology, and smart contracts for financial infrastructure
  • Payment systems, digital currencies, and central bank digital currencies
  • Financial forecasting, time-series modeling, and predictive analytics
  • Natural language processing for financial text, sentiment, and disclosure analysis

Autonomous Management and Decision Systems

The Journal welcomes research on autonomous and AI-supported decision-making in financial and organizational settings, including:

  • Autonomous and semi-autonomous decision-making in financial and management contexts
  • Agent-based and multi-agent modeling of markets and institutions
  • Reinforcement learning for trading, allocation, and operational control
  • Intelligent automation of treasury, compliance, and back-office functions
  • Decision-support and recommendation systems for management
  • Human-AI collaboration and oversight in financial decision processes
  • Intelligent workflow, process automation, and operational resilience
  • Strategic, operational, and enterprise risk management informed by AI methods

Foundations, Methods, and Governance

The Journal welcomes research that provides the theoretical, computational, and governance foundations for intelligent financial systems, including:

  • Financial machine learning, deep learning, and generative models
  • Econometrics, computational finance, and quantitative methods
  • Optimization simulation and stochastic modeling for finance
  • Explainability, interpretability, and robustness of financial AI
  • Data engineering, financial data quality, and feature engineering
  • Ethics, accountability, fairness, and bias in autonomous financial systems
  • Governance, regulation, and policy for artificial intelligence in finance
  • Privacy, security, and trust in intelligent financial infrastructure

Examples of in-scope work

The following examples illustrate the range of work the Journal publishes:

  • A reinforcement learning framework for adaptive portfolio rebalancing under shifting market regimes
  • An explainable machine learning model for credit default prediction using alternative data
  • A multi-agent simulation of liquidity dynamics in decentralized exchanges
  • A deep learning approach to real-time fraud detection in high-volume payment networks
  • A governance framework for human oversight of autonomous trading systems
  • A natural language processing pipeline for extracting risk signals from regulatory filings
  • A stress-testing methodology for AI-driven credit portfolios under macroeconomic shocks
  • A systematic review of explainability methods in financial risk modeling

Out-of-scope and editorial discrimination

The Journal applies rigorous initial screening for scope-fit, methodological adequacy, and originality before sending manuscripts to peer review. The following categories of work are typically declined at desk-screen:

  • Pure finance or economics theory with no computational, algorithmic, or autonomous-systems dimension
  • General machine learning or artificial intelligence method papers with no clear financial or management application
  • Descriptive FinTech market reports, product announcements, or feasibility notes without a research contribution
  • Qualitative organizational studies without an analytical, empirical, or computational component
  • Trading strategy disclosures or back-tests without methodological rigor, reproducibility, or a generalizable contribution
  • Speculative commentary on cryptocurrencies or markets without a research method
  • Manuscripts where the contribution is primarily a literature summary without methodological synthesis or original empirical work

Authors uncertain about scope-fit are encouraged to send a short pre-submission inquiry through the Contact page before preparing a full manuscript.

Article types

The Journal publishes the following article types. Detailed length, structure, and review expectations are described on the Author Guidelines page.

  • Original Research Article: full-length empirical, methodological, or theoretical contribution with original findings
  • Systematic or Methodological Review: structured synthesis following PRISMA, scientometric, bibliometric, or comparable established methodology
  • Short Communication: concise report of a focused finding, including thematic syntheses, brief methodological notes, and timely findings of immediate interest
  • Editorial: by invitation only, authored by members of the Editorial Team or invited contributors

Particularly welcomed contributions

While the Journal accepts submissions across the full breadth of its subject domains, contributions in the following named sub-disciplines are particularly welcomed and align closely with the Journal's editorial expertise: financial machine learning, algorithmic trading and market microstructure, AI-driven risk analytics, autonomous decision systems, agent-based financial modeling, explainable and responsible AI in finance, and regulatory technology.