세계의 행동 바이오메트릭스 시장(2023-2030년)

Overview

Global Behavioral Biometrics Market reached US$ 1.6 billion in 2022 and is expected to reach US$ 7.4 billion by 2030, growing with a CAGR of 20.5% during the forecast period 2023-2030.

Rising cyberattacks, fraud and incidences of identity theft increase day by day so there are enhanced authentication techniques. Beyond conventional security measures like passwords and PINs, behavioral biometrics provides an additional level of protection. In comparison to conventional approaches, behavioral biometrics offers a more smooth and user-friendly authentication experience. Users don't need to remember complex passwords and authentication can be passive and continuous, enhancing convenience.

Machine learning algorithms significantly improve the reliability and accuracy of behavioral biometrics and these algorithms lead to analyze large datasets and detect subtle patterns in user behaviors. Data privacy regulations like GDPR in Europe and CCPA in California have prompted organizations to explore more secure and privacy-friendly authentication methods, leading to increased interest in behavioral biometrics.

A growing number of cyber threats and fraud attempts in Asia-Pacific, where behavioral biometrics provides a continuous layer of security that adapts the evolving threats. Advancements in artificial intelligence and machine learning are improving the accuracy and effectiveness of behavioral biometrics systems, making them more appealing to organizations in the region.

Dynamics

Global Rise in Online Transaction

Businesses and individuals globally are increasingly transitioning to digital platforms for various activities, including shopping, banking and communication. The convenience of online transactions has driven their growth, making secure authentication methods like behavioral biometrics crucial. The escalating number of cyberattacks, data breaches and online fraud has heightened the need for stronger authentication methods. Behavioral biometrics adds an extra layer of security to protect against these threats.

For instance, on 6 September 2023, First Advantage Corporation, a specialist in employment background screening services, acquired Infinite ID, a biometrics startup headquartered in Hicksville, New York, in a US$41 million all-cash deal. Custom biometric solutions and owns the subsidiary PrintScan, focused on fingerprinting software.

Both companies have stated that Infinite ID, a profitable venture, is anticipated to generate annual revenues exceeding US$10 million. The report reveals that 16 percent of victims who engaged with the ITRC reported experiencing thoughts of suicide after falling victim to identity crimes, up from 10 percent the previous year. The financial impact of identity crime also appears to be deepening, with 26 percent of ITRC victims reporting losses exceeding US$100,000.

Rising Need for a Multi-Layered Security Approach

A variety of cyberattacks, including phishing, malware and social engineering are part of the growing threat landscape. Additional layers of security are frequently required because traditional security measures are frequently insufficient to thwart these assaults. Because cybercriminals are developing more complex attack techniques, it is more difficult to identify and stop breaches. Multi-layered security adds complexity for attackers and increases the chances of detecting their activities.

For instance, on 2 October 2023, CoolWallet, a leading hardware wallet manufacturer, addressed the growing threat of phishing attacks in the Web3 sector, particularly targeting platforms like Friend.tech and Coinbase's Ethereum layer-2 chain, Base. Friend.tech, a decentralized social media platform built on Base, has seen significant growth but is also attracting unwanted attention from malicious actors.

CoolWallet introduced the Web3 SmartScan as a defense against phishing attacks and this proactive transaction screener identifies malicious behavior and smart contract vulnerabilities before users become victims of theft. CoolWallet Pro, which integrates seamlessly with Friend.tech and Base, offers features such as an EAL6+ secure element, biometric verification and a tamper-proof design to enhance security.

Advancement in Behavioral Biometrics Technology

In order to study and interpret user behavior patterns, behavioral biometrics mainly relies on machine learning and artificial intelligence technologies. The precision and efficiency of behavioral biometrics systems increase as these technologies develop. The availability of high-performance computing resources and cloud infrastructure enables faster and more efficient analysis of behavioral data, making real-time authentication feasible.

For instance, on 12 September 2023, Caitlin Sinclair, Director of Proposition Development for Financial Crime at GIACT, an LSEG business, highlighted the vulnerabilities across the customer lifecycle for banks' customers, including consumers and enterprises, making them prime targets for fraud. Financial institutions, need to adopt multi-faceted approaches that go beyond traditional methods and this approach includes multi-factor authentication, one-time passwords and embracing technology that leverages alternative data for enhanced verification.

Privacy Concerns and Inaccurate Data

Systems using behavioral biometrics might not always be completely accurate. False positives or negatives may result from elements including user variation, the environment and the quality of the data that was obtained. Users with significant behavioral changes or those with disabilities may pose challenges to the accuracy of these systems. Although behavioral biometrics often rely on passive data collection, some user participation is still necessary. Users must take specific actions (such as typing or swiping) in order for data to be collected.

Some users may find behavioral biometrics intrusive, as it continuously monitors their actions and behaviors. Privacy concerns can arise, particularly when the system collects sensitive data without clear consent or control mechanisms. Behavioral biometric data is typically stored in the form of templates, which can be vulnerable to theft or compromise if not properly secured. Protecting these templates is crucial to prevent unauthorized access and misuse.

Segment Analysis

The global behavioral biometrics market is segmented based on type, deployment, application, end-user and region.

Significant Advancement in Signature Analysis Boosts the Market

Machine learning algorithms have made a significant advancement in recent years, allowing for more accurate and reliable analysis of behavioral biometric data and this has contributed to the feasibility and effectiveness of integrating behavioral biometrics into signature analysis. Security is paramount organizations also strive to provide a seamless user experience. Behavioral biometrics can enhance user convenience by enabling frictionless authentication based on natural behaviors, such as how a person signs their name.

According to the paper published in Transactions on Engineering and Computer Science, in September 2021, the significance of handwritten signatures as a widely accepted behavioral trait in biometric security systems. Signatures contain various dynamic and innate behavioral traits that can provide insights into a person's soft characteristics, including age, gender, personality and handedness. The paper presents a personality prediction system that determines different characteristics of a person's personality based on offline handwritten signature images.

Geographical Penetration

Digital Transformation in North America

North America has seen the implementation of stringent data privacy regulations, such as the California Consumer Privacy Act and the General Data Protection Regulation for businesses dealing with European customers. Behavioral biometrics aligns with these regulations as it often doesn't require the storage of sensitive biometric data. Organizations in North America are undergoing digital transformation initiatives, with a focus on providing digital services to customers.

For instance, on 7 August 2023, BioCatch Ltd. unveiled "BioCatch Ltd. Connect," a revamped anti-fraud platform powered by behavioral biometrics technology and this platform utilizes artificial intelligence (AI) to analyze data from various sources, including applications, devices and networks, enabling it to assess user behavior within specific contexts. foundational element continuously collects thousands of data signals from various sources through a lightweight mobile and web software development kit (SDK).

Competitive Landscape

The major global players in the market include BioCatch Ltd., Nuance Communications, Inc., LexisNexis Risk Solutions, Ping Identity, Zighra Inc., IKS TN S.r.l., Fair Isaac Corporation, Mastercard International Incorporated, ThreatMark and Plurilock Security Inc.

COVID-19 Impact Analysis

With lockdowns and social distancing measures in place, people have turned to digital channels for work, education, shopping and entertainment and this increased digital activity has generated more behavioral data, providing a plenty of information for behavioral biometrics systems to analyze. The pandemic has led to significant changes in user behavior. Remote work and online learning have altered typing patterns, mouse movements and other digital interactions. Behavioral biometrics systems have needed to adapt to these new patterns and recognize them as legitimate.

The need for secure remote access to systems and services has surged. Behavioral biometrics has played a crucial role in providing frictionless authentication for remote workers, reducing the reliance on traditional authentication methods like passwords. The pandemic has brought about an increase in cyberattacks and fraud attempts. Behavioral biometrics has been leveraged to detect fraudulent activities, such as account takeovers and phishing attacks, by analyzing user behavior for anomalies or suspicious patterns.

Some organizations have explored the use of behavioral biometrics for health monitoring during the pandemic. For example, monitoring typing patterns or voice characteristics to detect signs of stress or fatigue in remote workers. The collection and analysis of behavioral data for authentication and monitoring have raised privacy concerns. Users may be more sensitive to the handling of their personal data, leading to increased scrutiny of behavioral biometrics practices.

AI Impact

AI algorithms can analyze and interpret behavioral biometric data with high accuracy. Machine learning and deep learning techniques enable systems to recognize subtle patterns and variations in user behavior, reducing false positives and false negatives. AI enables real-time analysis of behavioral biometric data and this means that user authentication and fraud detection can occur instantaneously, providing immediate security responses when anomalies or suspicious activities are detected.

AI-powered behavioral biometrics systems can continuously learn and adapt to evolving user behavior and they can identify changes or deviations from established patterns, making them effective in detecting fraudulent activities that may change over time. AI algorithms excel at detecting anomalies in user behavior, they can identify unusual or unexpected actions that may indicate fraudulent access or compromised accounts, providing an additional layer of security.

For instance, on 26 September 2023, Amazon introduced new AI capabilities for its Alexa products, powered by a large language model called AlexaLLM and this technology aims to make Alexa more personalized and capable of retaining context during conversations. However, it was revealed that Amazon plans to use some user voice interactions with Alexa to train its AI model.

Amazon reassured users that they will maintain control over their Alexa experience through privacy controls and indicators, such as a glowing blue light and optional audible tones when Alexa is listening. However, the introduction of features like "Alexa, let's chat" with Visual ID, which allows activation without cue words, raises questions about privacy.

Russia-Ukraine War Impact

During times of geopolitical conflict, there is often an increase in cyberattacks and cyber threats. Adversarial nations or cybercriminal groups may target critical infrastructure organizations or individuals. By examining user behavior for indications of harmful activity, behavioral biometrics can be extremely useful in identifying and reducing such risks. Conflict-affected areas typically have more awareness of security issues and the value of safeguarding confidential information.

The disruption caused by conflict and security concerns may result in more people working remotely and conducting digital transactions. Behavioral biometrics can facilitate secure remote access and online transactions by providing continuous authentication without the need for physical tokens or passwords. In regions directly affected by conflict or political instability, there may be concerns about government surveillance and the privacy of individuals' digital activities.

By Type

• Signature Analysis
• Keystroke Dynamics
• Voice Recognition
• Gait Analysis

By Deployment

• On-Premise
• Cloud

By Application

• Identity Proofing
• Continuous Authentication
• Risk and Compliance
• Fraud Detection and Prevention

By End-User

• BFSI
• Retail and Commerce
• Healthcare
• Government and Public Sector
• Others

By Region

• North America
  • U.S.
  • Canada
  • Mexico

• Europe
  • Germany
  • UK
  • France
  • Italy
  • Russia
  • Rest of Europe

• South America
  • Brazil
  • Argentina
  • Rest of South America

• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific

• Middle East and Africa

Key Developments

• In April 2023, Onbe, a leading financial technology company specializing in disbursements, introduced OnbeGuard, an enhancement to its suite of fraud prevention tools. OnbeGuard now incorporates behavioral biometrics from BioCatch Ltd., a renowned fraud detection leader and this advanced solution combines historical spending patterns, BioCatch Ltd.'s behavioral biometrics and channel data to predict and combat payment fraud while reducing false positives at checkout, account login and ATMs.
• In May 2022, the Commonwealth Bank of Australia (CBA) is enhancing its fraud detection capabilities by incorporating additional behavioral biometrics into its security features. The bank will utilize behavioral biometrics to analyze customer computer configurations and individual behavior patterns, strengthening its real-time fraud detection capabilities across digital channels.
• In May 2022, LexisNexis Risk Solutions (LNRS) acquired LexisNexis Risk Solutions, a behavioral biometric technology provider, to enhance its anti-fraud solutions and this integration will enable merchants to strengthen identity verification and prevent fraud by utilizing a layered defense approach. Behavioral biometrics analyze how trusted users interact with their mobile devices and use this information for authentication during subsequent transactions.

Why Purchase the Report?

• To visualize the global behavioral biometrics market segmentation based on type, deployment, application, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of behavioral biometrics market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global behavioral biometrics market report would provide approximately 69 tables, 70 figures and 205 Pages.

Target Audience 2023

• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies

Table of Contents

1. Methodology and Scope

• 1.1. Research Methodology
• 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

• 3.1. Snippet by Type
• 3.2. Snippet by Deployment
• 3.3. Snippet by Application
• 3.4. Snippet by End-User
• 3.5. Snippet by Region

4. Dynamics

• 4.1. Impacting Factors
  • 4.1.1. Drivers
    • 4.1.1.1. Global Rise in Online Transaction
    • 4.1.1.2. Rising Need for a Multi-Layered Security Approach
    • 4.1.1.3. Advancement in Behavioral Biometrics Technology
  • 4.1.2. Restraints
    • 4.1.2.1. Privacy Concerns and Inaccurate Data
  • 4.1.3. Impact Analysis

5. Industry Analysis

• 5.1. Porter's Five Force Analysis
• 5.2. Supply Chain Analysis
• 5.3. Pricing Analysis
• 5.4. Regulatory Analysis
• 5.5. Russia-Ukraine War Impact Analysis
• 5.6. DMI Opinion

6. COVID-19 Analysis

• 6.1. Analysis of COVID-19
  • 6.1.1. Scenario Before COVID
  • 6.1.2. Scenario During COVID
  • 6.1.3. Scenario Post COVID
• 6.2. Pricing Dynamics Amid COVID-19
• 6.3. Demand-Supply Spectrum
• 6.4. Government Initiatives Related to the Market During Pandemic
• 6.5. Manufacturers Strategic Initiatives
• 6.6. Conclusion

7. By Type

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
  • 7.1.2. Market Attractiveness Index, By Type
• 7.2. Signature Analysis*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Keystroke Dynamics
• 7.4. Voice Recognition
• 7.5. Gait Analysis

8. By Deployment

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 8.1.2. Market Attractiveness Index, By Deployment
• 8.2. On-Premise*
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. Cloud

9. By Application

• 9.1. Introduction
  • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 9.1.2. Market Attractiveness Index, By Application
• 9.2. Identity Proofing*
  • 9.2.1. Introduction
  • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 9.3. Continuous Authentication
• 9.4. Risk and Compliance
• 9.5. Fraud Detection and Prevention

10. By End-User

• 10.1. Introduction
  • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 10.1.2. Market Attractiveness Index, By End-User
• 10.2. BFSI*
  • 10.2.1. Introduction
  • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 10.3. Retail and Commerce
• 10.4. Healthcare
• 10.5. Government and Public Sector
• 10.6. Others

11. By Region

• 11.1. Introduction
  • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
  • 11.1.2. Market Attractiveness Index, By Region
• 11.2. North America
  • 11.2.1. Introduction
  • 11.2.2. Key Region-Specific Dynamics
  • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
  • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.2.7.1. U.S.
    • 11.2.7.2. Canada
    • 11.2.7.3. Mexico
• 11.3. Europe
  • 11.3.1. Introduction
  • 11.3.2. Key Region-Specific Dynamics
  • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
  • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.3.7.1. Germany
    • 11.3.7.2. UK
    • 11.3.7.3. France
    • 11.3.7.4. Italy
    • 11.3.7.5. Russia
    • 11.3.7.6. Rest of Europe
• 11.4. South America
  • 11.4.1. Introduction
  • 11.4.2. Key Region-Specific Dynamics
  • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
  • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.4.7.1. Brazil
    • 11.4.7.2. Argentina
    • 11.4.7.3. Rest of South America
• 11.5. Asia-Pacific
  • 11.5.1. Introduction
  • 11.5.2. Key Region-Specific Dynamics
  • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
  • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
    • 11.5.7.1. China
    • 11.5.7.2. India
    • 11.5.7.3. Japan
    • 11.5.7.4. Australia
    • 11.5.7.5. Rest of Asia-Pacific
• 11.6. Middle East and Africa
  • 11.6.1. Introduction
  • 11.6.2. Key Region-Specific Dynamics
  • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
  • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
  • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

• 12.1. Competitive Scenario
• 12.2. Market Positioning/Share Analysis
• 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

• 13.1. BioCatch Ltd.*
  • 13.1.1. Company Overview
  • 13.1.2. Product Portfolio and Description
  • 13.1.3. Financial Overview
  • 13.1.4. Key Developments
• 13.2. Nuance Communications, Inc.
• 13.3. LexisNexis Risk Solutions
• 13.4. Ping Identity
• 13.5. Zighra Inc.
• 13.6. IKS TN S.r.l.
• 13.7. Fair Isaac Corporation
• 13.8. Mastercard International Incorporated
• 13.9. ThreatMark
• 13.10. Plurilock Security Inc.

LIST NOT EXHAUSTIVE

14. Appendix

• 14.1. About Us and Services
• 14.2. Contact Us