Biometrics Middleware Market: Surge in Sales Motivated by Innovation Across Product Offerings through 2027 | Key Players are Daon Inc., Imageware Systems Inc., Centrify Corporation, etc.
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Biometrics-as-a-service model has been a key focus area among biometric service providers to cater evolving requirements of end-users in BFSI sector. High upfront capital investment continues to challenge the adoption of biometrics in the BFSI sector. Biometric service providers are focusing on subscription-based and predictable model offerings to the BFSI industry, in order to increase their market penetration. Faster installation and execution of the BaaS model compared to traditional models has further, and maintenance and infrastructure costs covered by the providers is further expected to drive demand for biometrics-as-a-service in the BFSI sector. Although BaaS is gaining popularity as a feasible model, higher risk of cyberthreats are associated with it. Key vendors are putting efforts to improve their security apparatus, to mitigate challenges linked with the BaaS model. Demand for biometrics middleware will ride the coattails of rising adoption of BaaS model in the near future.
The trend of digitalization has created a lucrative revenue stream for the biometrics middleware market, where data privacy, security, and access continues to be a key agenda among all digitally-driven businesses. These businesses are in constant search for convenient yet intelligent security solutions for avoiding fraudulent activities, market reputation and financial losses, as password security becomes more and more vulnerable to breaches. Various biometric technologies that range from signature to fingerprint verification continue to witness widespread acceptance across industries, in light of their cost-efficiency, reliability and accuracy. Biometrics middleware will witness high demand with growing reliance of enterprises on the biometric technologies for security.
The need for data processing has been increasing significantly, as data monitoring services become more vulnerable to data concentration risks, devoid of location where data is stored – on cloud or remote server. Biometrics middleware providers have been developing peer-to-peer self-monitoring middleware solutions, for enabling real-time data management and processing. Growing demand for end-to-end solutions has created the requirement for integration of different middleware and software services. Leading biometric devices manufacturers are collaborating with middleware providers for establishing an integrated supply chain to deliver end-to-end solutions.
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Reliance on biometric technologies has increased among enterprises in various industrial domains, which in turn has underpinned demand for multimodal biometric system. Multimodal biometric systems have now become ubiquitous, despite comparatively greater requirement for resources and time than monomodal systems. Additional modalities of the multimodal biometric systems enhance the de-duplication process, which in turn delivers greater accuracy. In light of the rising incorporation of multimodal biometric systems, the marketplace is booming with biometrics middleware vendors that deliver convenient multimodal middleware architectures unconstrained to single-core technology deployment.
Biometrics middleware developers continue to tap opportunities created by adoption of biometrics in the government sector. Increasing emphasis on security alludes rapid adoption of biometric systems at airports, along with growing reliance of institutions such as Transportation Security Administration, and Customs and Border Protection Agency, on the biometrics for revving up their security. Biometrics middleware will also witness high demand as adoption of biometrics gains ground in military and law enforcement sectors. With advancements in the facial recognition technology that provides more efficient policing, biometric authentication is expected to gain high traction in the near future, thereby creating demand for biometrics middleware.
Artificial intelligence, machine learning and deep learning are likened to hand-in-glove in the area of biometrics. AI-driven biometrics has been primarily employed for fraud prevention in the financial services sector. Massive data breaches and requirement for enabling risk-based payment app authentication has extended the application of AI in biometrics to identity proofing for providing a new dimension to the online applications’ validity.
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