The automated fingerprint identification system market size is expected to see exponential growth in the next few years. It will grow to $30.02 billion in 2028 at a compound annual growth rate (CAGR) of 21.1%.  The growth in the forecast period can be attributed to rising security concerns, increasing adoption in civil applications, increasing adoption in emerging economies, and rising demand in e-commerce and retail. Major trends in the forecast period include mobile AFIS solutions, cloud-based AFIS, integration with edge computing, blockchain for secure fingerprint data management, IoT integration for smart access control.

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Segmentation & Regional Insights
The automated fingerprint identification system market covered in this report is segmented –
1) By Component: Hardware, Software, Services
2) By Identification: Latent Print Identification, Tenprint Identification
3) By End Use: Banking And Finance, Consumer Electronics, Defense And Security, Government, Healthcare, Transport Or Logistics, Other End Uses

North America was the largest region in the automated fingerprint identification system market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the automated fingerprint identification system market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

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Major Driver Impacting Market Growth
The increasing incidence of identity theft and fraud is expected to propel the growth of the automated fingerprint identification system market going forward. Identity theft and fraud is a criminal act where an individual's personal information, such as name, social security number, or financial account details, is unlawfully obtained and used by another person for fraud. The increase in theft and fraud is due to the widespread adoption of digital technologies and online platforms, the proliferation of dark web marketplaces, weak security practices, and inadequate cybersecurity measures. Automated fingerprint identification systems are critical in combating identity theft and fraud by providing secure biometric authentication methods and safeguarding against unauthorized access and fraudulent activities. For instance, according to reports published by Experian, an Ireland-based information services company, the number of consumer identity theft complaints in the U.S. rose 3.3% to just over 1.43 million in 2022 from about 1.39 million in 2020. Therefore, the rise of identity theft and fraud drives the growth of the automated fingerprint identification system market.

Key Industry Players
Major companies operating in the automated fingerprint identification system market are Facebook, Fujitsu Limited, Safran Group, Thales Group, Gemalto Cogent Inc., NEC Technologies India Private Limited, HID Global Corporation, secunet Security Networks AG, M2SYS Technology, Suprema Incorporation, Crossmatch, Dermalog Identification Systems GmbH, 3M Cogent Inc., Daon, AFIX Technologies Inc., Cognitec Systems GmbH, Papillon Systems, Aware Inc., Biometrics4ALL Inc., BIO-key International Inc., Precise Biometrics AB, East Shore Technologies, Fulcrum Biometrics LLC, Morpho SA, Sonda Technologies Ltd.

The automated fingerprint identification system market report table of contents includes:
1. Executive Summary
2. Automated Fingerprint Identification System Market Characteristics
3. Automated Fingerprint Identification System Market Trends And Strategies
4. Automated Fingerprint Identification System Market - Macro Economic Scenario
5. Global Automated Fingerprint Identification System Market Size and Growth
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31. Automated Fingerprint Identification System Market Other Major And Innovative Companies
32. Global Automated Fingerprint Identification System Market Competitive Benchmarking
33. Global Automated Fingerprint Identification System Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Automated Fingerprint Identification System Market
35. Automated Fingerprint Identification System Market Future Outlook and Potential Analysis

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