Under Section 16 of the Securities Exchange Act of 1934, senior executives, directors, and large-block shareholders are required to make ongoing filings about their company stock holdings to report any changes. These filings are made on Form 3, Form 4, and Form 5 and submitted to SECs Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system.

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team use quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, United Kingdom, Europe

The insider trades made by corporate executives, directors and officers includes the purchases, sales and ownership of securities at a company. The insider transactions data is reliable as it is sourced directly from SEC forms 3,4 and 5. Insider trades is a valuable tool in stock trading and investing. The data on insider transactions is automatically updated once disclosures and reports are made available on SEC. In case you want to learn more about Finnworlds Insider Transactions API, please, visit the website. https://finnworlds.com/insider-transactions-api/

By using this dataset, you agree to cite the Related Publication shown below. This dataset captures insider trading activity at publicly traded companies. The Securities and Exchange Commission has made these insider trading reports available on its web site in a structured format since mid-2003. However, most academic papers use proprietary commercial databases instead of regulatory filings directly, which makes replication challenging because the data manipulation and aggregation steps in commercial databases are opaque and historical records could be altered by the data provider over time. To overcome these limitations, the presented dataset is created from the original regulatory filings; it is updated daily and includes all information reported by insiders without alteration. Daily updates: https://dx.doi.org/10.34740/kaggle/ds/2973477

The Insider Threat Test Dataset is a collection of synthetic insider threat test datasets that provide both background and malicious actor synthetic data.The CERT Division, in partnership with ExactData, LLC, and under sponsorship from DARPA I2O, generated a collection of synthetic insider threat test datasets. These datasets provide both synthetic background data and data from synthetic malicious actors.For more background on this data, please see the paper, Bridging the Gap: A Pragmatic Approach to Generating Insider Threat Data.Datasets are organized according to the data generator release that created them. Most releases include multiple datasets (e.g., r3.1 and r3.2). Generally, later releases include a superset of the data generation functionality of earlier releases. Each dataset file contains a readme file that provides detailed notes about the features of that release.The answer key file answers.tar.bz2 contains the details of the malicious activity included in each dataset, including descriptions of the scenarios enacted and the identifiers of the synthetic users involved.

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team uses quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading Data, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, Africa

A 2022 survey found that a quarter of participants reported having experienced up to ten incidents of data leakage via insider. About 17 percent of the respondents had encountered 10 to 17 percent incidents of confidential data loss caused by an insider. A further 11 percent said they had seen more than 50 incidents involving insider threats.

The dataset consists of 644,643 corporate insider transactions between January 1986 and December 2013 that were filed to the Securities and Exchange Commission using Form 4 under Section 16 of the Securities Exchange Act of 1934. The original filings contain information on the identity of the trader, the role within the firm, the number of shares that were bought or sold, the transaction price, the total share position of the respective trader, the date of trade, and the date of reporting. The data on trades are merged with other characteristics of the insider or the firm. The dataset is used to investigate insider trading quantities and dollar profits to measure the benefits that insiders extract from their superior information. We describe and quantify the dollar profits, study the relation between trading returns and trading quantities and explore the determinants behind this relation.

In a 2023 survey, 44 percent of respondents among IT professionals worldwide found financial data to be the most susceptible to insider attacks. Customer data and employee data followed, with 41 percent and 37 percent of respondents, respectively. By contrast, only one-fourth of respondents considered intellectual property data to be the most susceptible to insider attacks

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Under Section 16 of the Securities Exchange Act of 1934, senior executives, directors, and large-block shareholders are required to make ongoing filings about their company stock holdings to report any changes. These filings are made on Form 3, Form 4, and Form 5 and submitted to SECs Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system.

Supplementary material

This documentation provides information on the files and folders contained in the supplementary material. Note that all .do and .R files in the supplementary material are meant to be run directly from the folder containing them.

1.contracts\

1.1.contracts\RegulationContractsModPas.do

Contains calculations for the results reported in section 3.2 and for Table 5 of the paper.

2.globals\

Contains data potentially used in analysis.

3.infodata\

Contains data potentially used in analysis.

4.predictions\

4.1.Predictions\Regulation_predictions.do

Contains calculations for Tables 2-4 of the paper.

4.2.Predictions\Regulation_predictions_DetectionProb.do

Contains calculations for the results reported in section 3.1 of the paper.

5.subjects\

Contains data potentially used in analysis.

6.timelog\

6.1.timelog\Regulation_timelog.do

Contains calculations for Figure 4 and Figure A1 of the paper.

7.z-Tree\

This folder contains the experimental software.

7.1.z-Tree\*.zdata

Parameter files for group assignment, market assignment, subject identifiers etc. used in the experimental software.

7.2.z-Tree\z-Tree_Documentation.pdf

Documentation of all variables used in the z-Tree experimental software.

8.DetectionProbability.xlsx

Contains data for Table 2 in the paper. Based on 4.1 Predictions\Regulation_predictions.do, section stata02.

9.groups.zdata

Overview of group IDs. Used In some analyses.

10.Insider_regulation_data.do

Stata .do file which processes the raw z-Tree output data (see section 12 of this document) in preparation for all analyses.

11.PowerAnalysis.R

Contains all post-hoc power analyses reported in sections 3.1 and 3.2 of the paper.

12.PUN*_C*.xls

Original z-Tree output files containing all experimental results. These are processed into Stata format in Insider_regulation_data.do.

13.ResultsWithReferences.pdf

The file “ResultsWithReferences.pdf” contains the results section of the paper, including (in blue) references to the analysis scripts described in the present document.

Insider Threat Protection Market Outlook

The global insider threat protection market size was estimated to be approximately USD 3.6 billion in 2023 and is projected to reach USD 8.1 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.5% over the forecast period. This growth is driven by the increasing frequency of insider threats, rising awareness regarding data protection, and stringent regulations that mandate robust security measures.

One of the primary growth factors for the insider threat protection market is the escalating number of insider threats, including both malicious and negligent insiders. With the increasing adoption of digital transformation across industries, the potential for insider threats has surged due to the wider access to sensitive information. Organizations are becoming more aware of the severe repercussions of data breaches, leading to a heightened focus on implementing robust insider threat protection solutions. Moreover, the integration of advanced technologies like machine learning and artificial intelligence in security systems is enabling more effective monitoring and detection of insider threats, further contributing to market growth.

Another significant growth driver is the stringent regulatory landscape. Governments and regulatory bodies worldwide are increasingly imposing regulations to ensure data protection and privacy. Compliance with regulations such as the General Data Protection Regulation (GDPR) in Europe, the Health Insurance Portability and Accountability Act (HIPAA) in the United States, and other national data protection laws necessitates the deployment of sophisticated insider threat protection solutions. Organizations are investing heavily in security measures to avoid hefty fines and reputational damage associated with non-compliance, thereby boosting market demand.

Moreover, the rise in remote working trends, especially post the COVID-19 pandemic, has accentuated the need for robust insider threat protection mechanisms. With a significant portion of the workforce continuing to operate remotely, the risks associated with insider threats have multiplied. Remote work environments often lack the stringent security controls present in office settings, making it crucial for organizations to deploy comprehensive insider threat protection solutions to safeguard their critical assets and data.

Regionally, North America currently holds the largest share of the insider threat protection market, driven by the presence of major market players and the early adoption of advanced security technologies. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by the rapid digitization of economies, increasing cyber threats, and growing investments in cybersecurity infrastructure. Europe also presents significant growth opportunities due to stringent regulatory frameworks and increasing awareness regarding data protection across industries.

Component Analysis

In the insider threat protection market, the component segment is divided into solutions and services. The solutions component encompasses various software and hardware tools designed to detect, analyze, and mitigate insider threats. This segment includes user activity monitoring software, data loss prevention solutions, and behavioral analytics tools, among others. The services component, on the other hand, involves managed security services, consulting, training, and support services that help organizations effectively implement and manage insider threat protection strategies.

The solutions segment holds a significant share in the market, driven by the increasing adoption of advanced technologies to detect and prevent insider threats. User activity monitoring software is particularly in high demand, as it enables organizations to track and analyze user behavior patterns to identify potential threats. Behavioral analytics tools are also gaining traction, leveraging machine learning algorithms to detect anomalies and suspicious activities that may indicate insider threats. The integration of these solutions with existing security infrastructure enhances their effectiveness, further driving market growth.

The services segment is also experiencing substantial growth, as organizations increasingly seek external expertise to manage their insider threat protection initiatives. Managed security services providers (MSSPs) offer comprehensive solutions that include continuous monitoring, threat detection, and incident response, allowing organizations to focus on their core busi

Eight data sets that differ in whether they are used to predict investor trading in the same or subsequent periods with observations about the trading of neighbors in the social network. The periods are either daily or weekly windows. Moreover, we investigate separately investor influence over purchase and sale transactions. These three differences lead to eight distinct data sets. The size of the data sets ranges from just below 2,400 to almost 22 thousand observations. The labels are positive (set equal to 1) if an investor on a given day traded specific security in the same direction as at least one of his neighbors and negative (set equal to 0) otherwise. We use a sliding window with the size corresponding to the prediction window. In each window, for each ego investor, we create observations of instances of social influence in the neighborhood, given that at least one of the neighbors is active. An ego investor can be understood as a tippee and her neighbors as tippers. We record the specific behavior of investors in their neighborhood and, depending on the prediction period, the ego investors' behavior in the same or subsequent period. Initially, the data sets were highly imbalanced in terms of labels and, for this reason, were re-sampled to achieve a 1:3 label balance ratio.

Get real-time insider trading data, Form 4 & Form 144 filings, and analytics from The Washington Service. Stay informed with expert insights.

Smart Insider monitors new director changes at listed companies, allowing our clients to view the compositions of boardrooms and monitor changes as they occur for the stocks that matter to them.

We track internal movement in company for director changes as they move positions within a firm or transition to a new one as well as monitor key dates and biographical information. Insights derived from aggregated share transactions across multiple boards can expose patterns and activity that might otherwise remain below the radar.

In addition to key dates for director and board changes, our people profiles go beyond by including biographies and pictures. This comprehensive visual profile provides clients with a holistic understanding of the characteristics of directors and senior officers.

We provide tailored data delivery to meet client needs, including scheduled desktop reports, nightly updates via FTP, API or Snowflake.

Investor Relations and HR departments can receive concise boardroom personnel changes across peer companies. Fund managers can get portfolio/watchlist updates and sector-specific information.

Sample dataset can be provided upon request.

Tags: Corporate Actions Data, Management Changes, Director Insights, Internal Movement in Companies, Board Changes, Stock Holdings Data, Salary Data, Insider Score.

A 2020 study found that data exfiltration was the most common type of insider threat, followed by privilege misuse. Data exfiltration accounted for 62 percent of insider threats caused by employees and contractors. The loss of sensitive data can cost a business millions of dollars and severely damage its reputations.

The Insider Threat Management (ITM) tools market is experiencing robust growth, driven by the increasing frequency and sophistication of insider threats and the rising adoption of cloud-based solutions. The market's expansion is fueled by several factors, including the growing volume of sensitive data, heightened regulatory compliance requirements (like GDPR and CCPA), and the increasing reliance on remote work environments, which expands the attack surface. Organizations across various sectors, including finance, healthcare, and technology, are prioritizing ITM solutions to mitigate risks associated with malicious or negligent insiders. The market is segmented by deployment type (cloud-based and on-premises) and user type (large enterprises and SMEs), with cloud-based solutions gaining significant traction due to their scalability, cost-effectiveness, and ease of deployment. North America currently holds a dominant market share, owing to early adoption and a well-established IT infrastructure. However, other regions, particularly Asia-Pacific, are witnessing rapid growth, fueled by increasing digitalization and government initiatives to improve cybersecurity. The competitive landscape is characterized by both established players and emerging vendors, leading to innovation and diversification of solutions. Future growth will likely be driven by advancements in artificial intelligence (AI) and machine learning (ML) for enhanced threat detection and response capabilities, as well as increased integration with other security solutions to create a holistic security posture. While the precise market size figures are unavailable, considering the rapid growth in cybersecurity and the criticality of insider threat protection, we can reasonably estimate a 2025 market size of approximately $5 billion, based on industry reports of other related cybersecurity segments and their growth rates. A conservative Compound Annual Growth Rate (CAGR) of 15% over the forecast period (2025-2033) is projected, given the continued demand and technological advancements. This growth will likely be influenced by factors like the increasing adoption of ITM solutions by SMEs, expansion into emerging markets, and the continuous development of more sophisticated threat detection technologies. However, factors like high initial investment costs and the complexity of implementing and managing ITM solutions could potentially restrain market growth to some extent.

The Insider Threat Management Software market is experiencing robust growth, driven by the increasing frequency and sophistication of insider threats and the rising adoption of cloud-based solutions. The market size in 2025 is estimated at $2.5 billion, reflecting a Compound Annual Growth Rate (CAGR) of 15% from 2019 to 2025. This growth is fueled by several key factors. Firstly, organizations are increasingly recognizing the vulnerability posed by malicious or negligent insiders, leading to greater investment in preventative and detective measures. Secondly, the shift toward hybrid and cloud-based work models has expanded the attack surface, necessitating robust insider threat management solutions. Thirdly, advancements in machine learning and artificial intelligence are enhancing the capabilities of these solutions, enabling more accurate threat detection and response. Key trends include the integration of User and Entity Behavior Analytics (UEBA) with Security Information and Event Management (SIEM) systems, the rise of automated threat response capabilities, and a growing focus on data loss prevention (DLP). However, the market faces certain restraints. The high cost of implementation and maintenance of these solutions can be a barrier for smaller organizations. Furthermore, the complexity of these systems and the need for specialized expertise can pose challenges for deployment and management. Despite these hurdles, the significant financial and reputational risks associated with insider threats are compelling organizations of all sizes to invest in robust insider threat management solutions. The forecast period (2025-2033) anticipates continued market expansion, driven by ongoing technological advancements and increasing awareness of the insider threat problem. The projected CAGR for this period is estimated to be 12%, placing the market size at approximately $8 billion by 2033. This growth trajectory reflects the enduring need for robust security measures in an increasingly interconnected and data-driven world.

The Insider Threat Management (ITM) Software market is experiencing robust growth, driven by the increasing frequency and sophistication of insider threats and the rising adoption of cloud-based and hybrid work models. The market size in 2025 is estimated at $2.5 billion, demonstrating significant expansion from its historical period. Assuming a conservative Compound Annual Growth Rate (CAGR) of 15% based on industry trends and considering the escalating need for robust security solutions in a digitally transformed world, the market is projected to reach approximately $6.5 billion by 2033. This growth is fueled by several key factors. Organizations are increasingly recognizing the devastating consequences of insider breaches, leading to a greater investment in preventative measures. Furthermore, the adoption of advanced analytics and machine learning within ITM solutions is enhancing detection capabilities and reducing response times. The rise of remote work and the expansion of cloud infrastructure have also significantly contributed to market growth, as organizations require solutions that can effectively monitor and manage user activity across diverse environments. Despite the positive outlook, challenges remain for the ITM market. Concerns about data privacy and the potential for false positives continue to hinder widespread adoption. The complexity of integrating ITM solutions with existing security infrastructures can also pose a barrier for some organizations. However, ongoing advancements in technology, including the development of more sophisticated threat detection algorithms and improved user experience, are expected to mitigate these challenges and drive further market expansion. The competitive landscape is marked by a diverse range of vendors, each offering unique features and capabilities, leading to increased innovation and market evolution. The presence of both established players and emerging startups fosters a dynamic and competitive market, driving constant improvements in ITM solutions.