行動バイオメトリクスの世界市場-2023年～2030年

概要

世界の行動バイオメトリクス市場は、2022年に16億米ドルに達し、2023-2030年の予測期間中にCAGR 20.5％で成長し、2030年には74億米ドルに達すると予測されています。

サイバー攻撃の増加、詐欺、個人情報盗難の発生は日々増加しているため、認証技術が強化されています。パスワードや暗証番号のような従来のセキュリティ対策に加えて、行動バイオメトリクスはさらなる保護レベルを提供します。従来のアプローチと比較して、行動バイオメトリクスはよりスムーズでユーザーフレンドリーな認証体験を提供します。ユーザーは複雑なパスワードを覚える必要がなく、認証は受動的かつ継続的に行えるため、利便性が向上します。

機械学習アルゴリズムは行動バイオメトリクスの信頼性と精度を大幅に向上させ、これらのアルゴリズムは大規模なデータセットを分析し、ユーザー行動の微妙なパターンを検出することにつながります。欧州のGDPRやカリフォルニア州のCCPAのようなデータ・プライバシー規制は、組織に、より安全でプライバシーに配慮した認証方法の探求を促し、行動バイオメトリクスへの関心の高まりにつながっています。

アジア太平洋ではサイバー脅威や詐欺の試みが増加しており、行動バイオメトリクスは進化する脅威に適応する継続的なセキュリティ層を提供しています。人工知能と機械学習の進歩により、行動バイオメトリクス・システムの精度と有効性が向上しており、同地域の組織にとってより魅力的なものとなっています。

ダイナミクス

オンライン取引の世界の増加

世界の企業や個人は、ショッピング、バンキング、コミュニケーションなど、さまざまな活動においてデジタル・プラットフォームへの移行を加速させています。オンライン取引の利便性がオンライン取引の成長を後押ししており、行動バイオメトリクスのような安全な認証方法が重要となっています。サイバー攻撃、データ漏洩、オンライン詐欺の急増により、より強力な認証方法の必要性が高まっています。行動バイオメトリクスは、こうした脅威から保護するために、セキュリティのレイヤーを追加します。

例えば、2023年9月6日、雇用経歴審査サービスのスペシャリストであるファースト・アドバンテージ・コーポレーションは、ニューヨーク州ヒックスビルに本社を置くバイオメトリクスの新興企業、インフィニットIDを4,100万米ドルの全額現金取引で買収しました。インフィニットID社は、カスタムバイオメトリクス・ソリューションを提供し、指紋採取ソフトウェアに特化した子会社プリントスキャン社を所有しています。

両企業は、収益性の高いベンチャー企業であるInfinite IDは、年間1,000万米ドルを超える収益が見込まれると述べています。報告書によると、ITRCと関わった被害者の16％が、ID犯罪の被害に遭った後に自殺を考えたと報告しており、前年の10％から増加しています。ITRCの被害者の26％が10万米ドルを超える損失を報告しており、ID犯罪の経済的影響も深まっているようです。

多層的なセキュリティ・アプローチの必要性の高まり

フィッシング、マルウェア、ソーシャル・エンジニアリングなど、さまざまなサイバー攻撃は、脅威の拡大の一端を担っています。こうした攻撃を阻止するには、従来のセキュリティ対策では不十分なことが多いため、追加のセキュリティ層が必要になることが多いです。サイバー犯罪者はより複雑な攻撃手法を開発しているため、侵害を特定して阻止することはより困難になっています。多層的なセキュリティは攻撃者に複雑さを与え、その活動を検知する可能性を高める。

例えば、2023年10月2日、大手ハードウェアウォレットメーカーであるCoolWalletは、特にFriend.techやCoinbaseのイーサリアムレイヤー2チェーンであるBaseのようなプラットフォームを標的とした、Web3分野におけるフィッシング攻撃の脅威の高まりに対処しました。Base上に構築された分散型ソーシャルメディア・プラットフォームであるFriend.techは大きな成長を遂げているが、悪意のあるアクターからの不要な注目も集めています。

CoolWalletはフィッシング攻撃に対する防御としてWeb3 SmartScanを導入し、このプロアクティブ・トランザクション・スクリーナーは、ユーザーが盗難の犠牲になる前に悪意のある行動やスマート・コントラクトの脆弱性を特定します。Friend.techやBaseとシームレスに統合するCoolWallet Proは、EAL6+セキュアエレメント、生体認証、改ざん防止デザインなどの機能を提供し、セキュリティを強化します。

行動バイオメトリクス技術の進歩

ユーザーの行動パターンを研究・解釈するために、行動バイオメトリクスは主に機械学習と人工知能技術に依存しています。これらの技術が発展するにつれて、行動バイオメトリクス・システムの精度と効率は向上しています。高性能なコンピューティング・リソースとクラウド・インフラが利用可能になることで、行動データをより迅速かつ効率的に分析できるようになり、リアルタイムの認証が実現可能になります。

例えば、2023年9月12日、LSEGの事業であるGIACTの金融犯罪のための提案開発ディレクターであるケイトリン・シンクレアは、消費者や企業を含む銀行の顧客の顧客ライフサイクル全体にわたる脆弱性を強調し、詐欺の格好の標的になっていると指摘しました。金融機関は、従来の方法を超える多面的なアプローチを採用する必要があり、このアプローチには、多要素認証、ワンタイムパスワード、検証強化のための代替データを活用する技術の採用などが含まれます。

プライバシーの懸念と不正確なデータ

行動バイオメトリクスを使用するシステムは、常に完全に正確であるとは限らないです。偽陽性または偽陰性は、ユーザのバリエーション、環境、および取得されたデータの品質などの要素によって生じる可能性があります。行動が大きく変化するユーザや障害を持つユーザは、これらのシステムの精度に課題をもたらす可能性があります。行動バイオメトリクスは受動的なデータ収集に依存することが多いが、ユーザーの参加も必要です。データを収集するためには、利用者は特定の行動（タイピングやスワイプなど）をとらなければならないです。

行動バイオメトリクスは、ユーザーの行動や振る舞いを継続的に監視するため、ユーザーによっては押しつけがましいと感じるかもしれないです。特に、システムが明確な同意や制御メカニズムなしに機密データを収集する場合、プライバシーに関する懸念が生じる可能性があります。行動バイオメトリクス・データは通常、テンプレートの形で保存され、適切に保護されない場合、盗難や漏洩の恐れがあります。これらのテンプレートを保護することは、不正アクセスや悪用を防ぐために極めて重要です。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

• 影響要因
  • 促進要因
    • オンライン取引の世界の増加
    • 多層的なセキュリティ・アプローチへのニーズの高まり
    • 行動バイオメトリクス技術の進歩
  • 抑制要因
    • プライバシーへの懸念と不正確なデータ
  • 影響分析

第5章 産業分析

• ポーターのファイブフォース分析
• サプライチェーン分析
• 価格分析
• 規制分析
• ロシア・ウクライナ戦争の影響分析
• DMI意見

第6章 COVID-19分析

第7章 タイプ別

• シグネチャー分析
• キーストローク動態
• 音声認識
• 歩行分析

第8章 導入形態別

• オンプレミス
• クラウド

第9章 アプリケーション別

• アイデンティティ証明
• 継続的認証
• リスクとコンプライアンス
• 不正検知と防止

第10章 エンドユーザー別

• BFSI
• 小売・商業
• ヘルスケア
• 政府・公共機関
• その他

第11章 地域別

• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • イタリア
  • ロシア
  • その他欧州
• 南米
  • ブラジル
  • アルゼンチン
  • その他南米
• アジア太平洋
  • 中国
  • インド
  • 日本
  • オーストラリア
  • その他アジア太平洋地域
• 中東・アフリカ

第12章 競合情勢

• 競合シナリオ
• 市況/シェア分析
• M&A分析

第13章 企業プロファイル

• BioCatch Ltd.
  • 会社概要
  • 製品ポートフォリオと説明
  • 財務概要
  • 主な発展
• Nuance Communications, Inc.
• LexisNexis Risk Solutions
• Ping Identity
• Zighra Inc.
• IKS TN S.r.l.
• Fair Isaac Corporation
• Mastercard International Incorporated
• ThreatMark
• Plurilock Security Inc.

第14章 付録

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