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OSINT, or Open Source Intelligence, refers to “advanced searching in open-source information resources.” This concept involves the collection and analysis of information available from public and open sources, including newspapers, websites, media, and other public resources. This type of information can be utilized in various fields. Using OSINT helps in analyzing and interpreting information available in the open and public environment to enhance understanding and make appropriate decisions in different contexts. Although access to this information is free for everyone, obtaining accurate information at the right time and effectively utilizing it is not a simple task, but OSINT techniques make this possible.

Algorithmic trading, sometimes referred to as automated trading, uses computer software to generate orders with specific instructions. These trades are executed automatically by computers at high speeds, which is not feasible manually by humans.

A decade ago, Bailey et al. (2003) presented research opportunities in the field of internal auditing, which helped strengthen internal auditing by encouraging the academic internal auditing community. After ten years, this research provides an overview of what the relevant academic literature says about the effectiveness of internal auditing. Empirical studies based on self-assessment by internal auditors and empirical studies based on the perspectives of other stakeholders (outside-in evaluation) have been examined based on the “effectiveness” perspective. After identifying common areas, the main topics have been combined into a model consisting of macro and micro factors influencing internal auditing. Then, an updated set of research opportunities in internal auditing is presented. The valuable and innovative aspect of this research is the suggested pathways for future studies.