As of June 2023, around ** percent of respondents in China had encountered prize or lottery-winning scams online. Other major cybersecurity issues included**********************, **************************, and *****************.

The Chinese Big Data market presents a compelling investment landscape, projected to experience robust growth. With a Compound Annual Growth Rate (CAGR) of 30% from 2019 to 2033, the market's value is expected to surge significantly. Several key drivers fuel this expansion. The burgeoning digital economy in China, coupled with increasing government initiatives promoting data-driven decision-making across sectors, is creating substantial demand for big data solutions. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) are inextricably linked to big data, fostering innovation and creating new applications across diverse industries, including BFSI, healthcare, retail, and manufacturing. The adoption of cloud-based big data solutions is accelerating, offering scalability and cost-effectiveness for businesses of all sizes. However, challenges remain, including data security concerns, a lack of skilled professionals, and the need for robust data governance frameworks. These restraints, while present, are not expected to significantly impede the overall market trajectory given the substantial opportunities and government support.
The market segmentation reveals diverse investment avenues. The cloud deployment model is projected to dominate due to its advantages, while the large enterprise segment presents the largest revenue pool. Within solutions, customer analytics, fraud detection, and predictive maintenance are currently high-growth areas, offering attractive ROI. Geographically, China itself represents a significant portion of the market, although international players are also gaining traction. Considering the robust CAGR and the diverse segments, strategic investments targeting cloud-based solutions, AI-powered analytics, and specific industry verticals (like BFSI and healthcare) hold significant promise for high returns. Careful consideration of regulatory landscapes and data privacy regulations is crucial for successful investment strategies within this dynamic market. Investment Opportunities of Big Data Technology in China This comprehensive report analyzes the burgeoning investment opportunities within China's Big Data Technology sector, offering a detailed forecast from 2019-2033. The report utilizes 2025 as its base and estimated year, covering the historical period (2019-2024) and forecasting market trends from 2025-2033. It delves into market dynamics, key players, and emerging trends shaping this rapidly expanding industry. This report is crucial for investors, businesses, and analysts seeking to understand and capitalize on the immense potential of China's big data market. Recent developments include: November 2022 - Alibaba announced the Innovative upgrade, and Greener 11.11 runs wholly on Alibaba Cloud, whereas Alibaba Cloud's dedicated processing unit powered 11.11 for the Apsara Cloud operating system. The upgraded infrastructure system significantly improved the efficiency of computing, storage, etc., October 2022 - Huawei Technologies Co.has unveiled its 4-in-1 hyper-converged enterprise gateway NetEngine AR5710, delved into the latest CloudCampus 3.0 + Simplified Solution, and launched a series of products for large enterprises and Small- and Medium-Sized Enterprises (SMEs). With these new offerings, Huawei aims to help enterprises simplify their campus networks and maximize digital productivity.. Key drivers for this market are: 6.1 Data Explosion: Unstructured, Semi-structured and Complex6.2 Improvement in Algorithm Development6.3 Need for Customer Analytics. Potential restraints include: 7.1 Lack of General Awareness And Expertise7.2 Data Security Concerns. Notable trends are: Need for Customer Analytics to Increase Exponentially Driving the Market Growth.

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Fraud Detection And Prevention Market Size 2025-2029

The fraud detection and prevention market size is forecast to increase by USD 122.65 billion, at a CAGR of 30.1% between 2024 and 2029.

The market is witnessing significant growth, driven by the increasing adoption of cloud-based services. Businesses are recognizing the benefits of cloud solutions, such as real-time fraud detection, scalability, and cost savings. Additionally, technological advancements in fraud detection and prevention solutions and services are enabling organizations to better protect their assets from sophisticated fraud schemes. However, the complex IT infrastructure of modern businesses poses a challenge in implementing and integrating these solutions effectively. The complexity of the IT infrastructure, which integrates cloud computing, big data, and mobile devices, creates a vast network of devices with insufficient security features.
To capitalize on market opportunities, companies must stay abreast of these trends and invest in advanced fraud detection technologies. Effective implementation and integration of these solutions, coupled with continuous innovation, will be crucial for businesses seeking to mitigate fraud risks and protect their reputation and financial stability. Furthermore, the constant evolution of fraud techniques necessitates continuous innovation and adaptation from solution providers. Encryption techniques and network security protocols form the foundation of robust cybersecurity defenses, while compliance regulations and penetration testing help identify vulnerabilities and strengthen security posture.

What will be the Size of the Fraud Detection And Prevention Market during the forecast period?

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The market continues to evolve, driven by the constant emergence of new threats and the need for advanced technologies to mitigate risks across various sectors. Real-time fraud alerts, anomaly detection systems, forensic accounting tools, and risk mitigation strategies are integrated into comprehensive solutions that adapt to the ever-changing fraud landscape. Entities rely on these tools to maintain regulatory compliance frameworks and incident response planning, ensuring access control management and vulnerability assessments are up-to-date. Machine learning algorithms and transaction monitoring tools enable the detection of suspicious activity, providing valuable insights into potential threats.

Intrusion detection systems and behavioral biometrics offer real-time protection against cyberattacks and payment fraud, while identity verification methods and risk scoring models help prevent account takeover and data loss. Cybersecurity threat intelligence and authentication protocols enhance the overall security strategy, providing a layered approach to fraud prevention. Fraud investigation techniques and loss prevention metrics enable entities to respond effectively to incidents and minimize the impact of data breaches. Social engineering countermeasures and payment fraud detection solutions further fortify the fraud prevention arsenal, ensuring continuous protection against evolving threats.

The ongoing dynamism of the market demands a proactive approach, with entities staying informed and agile to maintain a strong defense against fraudulent activities.

How is this Fraud Detection And Prevention Industry segmented?

The fraud detection and prevention industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Solutions
  Services


End-user

  Large enterprise
  SMEs


Application

  Transaction monitoring
  Compliance and risk management
  Identity verification
  Behavioral analytics
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    Russia
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Component Insights

The Solutions segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth due to escalating cyber threats, increasing regulatory compliance requirements, and the need to mitigate financial losses. Biometric authentication, encryption techniques, machine learning algorithms, and intrusion detection systems are among the key solutions driving market expansion. Regulatory frameworks, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), are mandating robust incident response planning, access control management, and data breach prevention strategies. Vulnerability as

According to the reports received by Tencent *** during 2021, around ** percent of victims of telemarketing and online scams reported in China were between 22 and 29 years old. Since the data were collected based on online reporting, many elderly victims might not be included. Over recent years, telemarketing and online scams are becoming increasingly professional and are always operated by larger organizations.

The dataset collected a total of 200,000 pieces of data from three Chinese Internet recruitment websites, 51job, Boss Zhipin and Liepin. The dataset uses a simple set of statistical rules to assign a fraud probability to each data piece, with a total of nine categories ranging from 0% to 80%. Note that the data set is heavily unbalanced because it is real data.

The Chinese big data technology market presents significant investment opportunities, fueled by a robust 30% CAGR and a substantial market size. Driven by government initiatives promoting digital transformation, rapid technological advancements, and the increasing adoption of cloud-based solutions across diverse sectors like BFSI, healthcare, and manufacturing, the market is poised for continued expansion. Key trends include the growing demand for advanced analytics, including predictive maintenance and fraud detection, coupled with the increasing deployment of big data solutions in the cloud. While data privacy regulations and a potential skills gap pose challenges, the immense potential of the Chinese market outweighs these restraints. The concentration of major technology players like Alibaba Cloud, Tencent, and Huawei within China, alongside established international companies like IBM and Microsoft, indicates a fiercely competitive yet lucrative landscape. Investment strategies should focus on companies offering cutting-edge analytics solutions, particularly those catering to the rapidly expanding cloud and mobile segments. Furthermore, investments in companies specializing in data security and compliance solutions will be crucial given the increasing focus on data privacy. The segmentation of the market offers diverse investment avenues. Large enterprises are likely to lead adoption, but the SME segment presents significant growth potential as more companies embrace data-driven decision-making. Within solutions, customer analytics and fraud detection will maintain high demand, while predictive maintenance and asset management in sectors like manufacturing and automotive will witness substantial growth. Geographical focus should consider the economic powerhouses within China, with Tier-1 cities expected to lead adoption rates, followed by a gradual expansion into Tier-2 and Tier-3 cities. The forecasted market growth for the next decade indicates a substantial return on investment for strategically positioned players. A detailed understanding of regulatory landscapes and the evolving technological landscape will prove critical for successful investment in this dynamic market. Recent developments include: November 2022 - Alibaba announced the Innovative upgrade, and Greener 11.11 runs wholly on Alibaba Cloud, whereas Alibaba Cloud's dedicated processing unit powered 11.11 for the Apsara Cloud operating system. The upgraded infrastructure system significantly improved the efficiency of computing, storage, etc., October 2022 - Huawei Technologies Co.has unveiled its 4-in-1 hyper-converged enterprise gateway NetEngine AR5710, delved into the latest CloudCampus 3.0 + Simplified Solution, and launched a series of products for large enterprises and Small- and Medium-Sized Enterprises (SMEs). With these new offerings, Huawei aims to help enterprises simplify their campus networks and maximize digital productivity.. Key drivers for this market are: 6.1 Data Explosion: Unstructured, Semi-structured and Complex6.2 Improvement in Algorithm Development6.3 Need for Customer Analytics. Potential restraints include: 6.1 Data Explosion: Unstructured, Semi-structured and Complex6.2 Improvement in Algorithm Development6.3 Need for Customer Analytics. Notable trends are: Need for Customer Analytics to Increase Exponentially Driving the Market Growth.

In 2021, the number of online fraud cases in China declined by over ** percent, with fraudulent loans account for ** percent of cases. It was the first time in the observed period that fraud in cyberspace decreased. According to the People's Supreme Court, fraud was the most prevalent internet crime in China in 2021, accounting for around ********* of all cases. In the same year, the number of fraud cybercrime cases in China reached *** thousand recorded cases.

The dataset includes the results of food fraud vulnerability assessments (on spice/ginger and wine) of various companies based in China and Europe. The data form part of WP3 (Task 3.2): Implementation of innovations in food authenticity. The data is generated to better understand the food fraud vulnerability within selected food chains. The data is useful for anyone working in the field of food authentication.

The data is sourced from the CSMAR database, covering violation records of companies listed on the Shanghai and Shenzhen stock exchanges from 2015 to 2020, focusing on five types of financial fraud: fictitious profits, inflated assets, false records, material omissions, and inaccurate disclosures. After excluding financial firms, the fraud sample set includes 2,652 violation records from 1,226 companies. Additionally, 2,652 high-quality companies without fraud were selected from the CNRDS ESG rating database to form the non-fraud sample set. The dataset consists of two parts: 1) Structured data: The file "financial fraud dataset (structured data).xlsx" contains 5,304 records covering 43 fields, such as basic company information, financial indicators, structural indicators, and linguistic features of annual report texts. Field names are listed in Table 1. 2) Annual report text data: The folder named "Annual report text data" includes 2,652 fraud samples (file names formatted as Symbol-Year.txt) and 2,652 non-fraud samples (same format). The files contain the MD&A sections of listed companies' annual reports.

ScamGen: A Comprehensive Dataset of Chinese Telephone Scams

This dataset, created using the ScamGen technique, focuses on capturing the psychological dynamics between scammers and victims in Chinese telephone scams. It is derived from a multi-source data collection framework and is expanded through a template-based data augmentation method, generating diverse and realistic scam scenarios. The dataset emphasizes the interactions between scammers and victims, using sentence- and word-level perturbations to ensure a wide variety of scam types and techniques.

This rich dataset covers various scam strategies, such as urgency, impersonation, and emotional manipulation, designed to simulate the real-life psychological tactics employed by scammers. It has been rigorously evaluated and proven to outperform large language models in generating diverse and high-quality scam-related data.

Alongside this dataset, five deep learning models for intent detection were developed, with BERT achieving a precision of 86.68%. This dataset is a valuable resource for researchers and practitioners in the fields of cybersecurity and fraud detection, enabling a deeper understanding of telephone scammer tactics and aiding in the development of more effective detection systems.

This dataset explores EU consumer perceptions (n=574 from Germany/UK) of processed Chinese garlic. It investigates if the provision of traceability and authenticity information can enhance consumer trust in the food chain, as well as add value and increase sales.

An online panel provider recruited the participants and hosted the online data collection during April 2021.

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Healthcare Fraud Detection Market Size 2025-2029

The healthcare fraud detection market size is forecast to increase by USD 1.09 billion at a CAGR of 11.8% between 2024 and 2029.

The market is experiencing significant growth due to the increasing number of patients seeking health insurance and the emergence of social media's influence on the healthcare industry. The rise in healthcare fraud cases, driven by the influx of insurance claims, necessitates robust fraud detection solutions. Social media's impact on healthcare extends to fraudulent activities, with fake claims and identity theft posing challenges. However, the deployment of healthcare fraud detection systems remains a time-consuming process, and the need for frequent upgrades to keep up with evolving fraud schemes adds complexity.
Additionally, collaborating with regulatory bodies and industry associations can help stay informed of the latest fraud trends and best practices. Overall, the market presents opportunities for innovation and growth, as the demand for effective solutions to combat fraudulent activities continues to rise. Companies must navigate these challenges by investing in advanced technologies, such as machine learning and artificial intelligence, to streamline deployment and enhance fraud detection capabilities.

What will be the Size of the Healthcare Fraud Detection Market during the forecast period?

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The market encompasses various solutions and services designed to mitigate fraudulent activities in Medicaid services and health insurance. Data analytics plays a pivotal role in this domain, with statistical methods and data science techniques used to identify fraudulent healthcare activities. Prescriptive analytics and machine learning algorithms enable the prediction of potential fraudulent claims and billing schemes. Medical services, including pharmacy billing fraud and prescription fraud, are prime targets for offenders. Identity theft and social media are also significant contributors to healthcare fraud costs. Payment integrity is crucial for insurers to minimize financial losses, making fraud detection a priority.

On-premise and cloud-based solutions offer analytics capabilities to combat fraud. Descriptive analytics provides insights into historical data, while predictive analytics and prescriptive analytics offer proactive fraud detection. Despite the advancements in fraud detection, data limitations pose challenges. The use of artificial intelligence and machine learning in fraud detection is increasing, providing more accurate and efficient solutions. Insurance claims review is a critical component of fraud detection, with fraudulent claims costing billions annually. Fraudsters continue to evolve their tactics, necessitating the need for advanced fraud detection solutions.

How is this Healthcare Fraud Detection Industry segmented?

The healthcare fraud detection industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Descriptive analytics
  Predictive analytics
  Prescriptive analytics


End-user

  Private insurance payers
  Third-party administrators (TPAs)
  Government agencies
  Hospitals and healthcare providers


Delivery Mode

  Cloud-based
  On-premises


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The Descriptive analytics segment is estimated to witness significant growth during the forecast period. In the dynamic landscape of healthcare, Anomalies Detection and Healthcare Fraud Analytics play a pivotal role in safeguarding Financial Resources from Fraudulent Healthcare Activities. Descriptive analytics, a foundational type of analytics, forms the backbone of this industry. With its ability to aggregate and examine vast healthcare data, descriptive analytics identifies trends and operational performance insights. It is widely used in various departments, from Healthcare IT adoption to Urgent care, and supports Insurance Claims Review processes. Cloud-Based Solutions and On-Premises Solutions are two delivery models that cater to diverse organizational needs. Machine Learning and Statistical Methods are integral to advanced analytics, including Prescriptive analytics and Predictive analytics, which uncover intricate patterns and prevent Fraudulent Claims.

Social Media and Data Analytics offer valuable insights into potential Fraudulent Activities, while Real-Time Analytics ensure Payment Integrity in Healthca

Caution! This dataset contains explicit language and fraud information. Use at your own risk!

For AutoTrain use: please select Text Classification (Binary) as Task.

  What is included

conversations in chinese under tag 0 spam conversations under tag1

  Where does the data come from

part of the data came from conversations in Chinese Telegram groups part of them are from logging channels of anti-spam bots

  How many data is included

A total of 9.9k… See the full description on the dataset page: https://huggingface.co/datasets/paulkm/chinese_conversation_and_spam.

In 2021, the number of online fraud cases in China declined by over ** percent. It was the first time in the observed period that fraud in cyberspace decreased. According to the People's Supreme Court, fraud was the most prevalent internet crime in China in 2021, accounting for around ********* of all cases. In the same year, the number of fraud cybercrime cases in China reached *** thousand recorded cases.

The statistic shows the total loss amount caused by telecommunication and network fraud in China in 2016, broken down by type of fraud. That year, the financial loss due to phone scam in China reached *** billion yuan.

In 2021, the share of online fraud cases that included identity theft amounted to *** percent. According to the People's Supreme Court, fraud was the most prevalent internet crime in China in 2021, accounting for around one-third of all cases. In the same year, the number of fraud cybercrime cases in China reached *** thousand recorded cases.

In 2023, there were around **** million theft crimes registered by the police in China. While the number of theft cases has decreased considerably in recent years, fraud crimes have fluctuated.

10,000 Images of damaged car for AI, Machine Learning & Computer Vision model. The dataset is annotated in Classification (9 Car Damage label) and Instant segmentation

Focus group discussions: Emergent themes supporting evidence and researcher interpretations of the data.

Descriptive statistics and correlation analysis for the model constructs.