Data Privacy

Addressing Data Privacy Concerns with Face Match API

Financial institutions and organizations worldwide face an uphill battle regarding fraud prevention. With fraudsters’ ever-evolving tactics, traditional identification verification methods aren’t sufficient. The consequences of falling victim to fraud can be devastating for the institutions and their customers, who entrust them with sensitive personal information.

This is where Signzy’s Face-Match API steps in as a game-changer. By harnessing the power of facial recognition technology, we offer a robust solution to combat fraud effectively.

With our solution, financial institutions can perform identity verification effortlessly and accurately. By comparing a user’s live image with their stored reference image, any discrepancies or signs of fraudulent activity can be swiftly detected. This revolutionary tool provides an added layer of security that significantly reduces the risk associated with fraudulent transactions.

Our face-match technology goes beyond verifying identities; it also helps streamline customer onboarding processes by eliminating manual interventions and reducing human error. This enables organizations to enhance operational efficiency while maintaining stringent compliance standards.

However, it is understandable that users and businesses would be wary of how their data is handled. In this article, learn more about how Signzy protects data from falling into the wrong hands.

The ongoing concerns around data privacy

Data privacy is a pressing concern in today’s digital age, where personal information is constantly shared and stored online. Addressing these concerns becomes even more crucial with the increasing use of facial recognition technology and identity verification systems.

One major worry is the potential misuse or unauthorized access to sensitive data. As financial institutions and organizations collect vast amounts of personal information for fraud detection and compliance purposes, individuals are rightfully concerned about how their data will be protected.

Another concern revolves around consent management. Individuals want assurance that their consent is sought before their data is used. They also expect transparency regarding what type of data will be collected, how long it will be retained, and who will have access to it.

Signzy takes data privacy and compliance seriously. Addressing concerns around data privacy requires a comprehensive approach involving transparency in consent management practices and stringent security protocols. Only then can individuals feel confident in entrusting their personal information to organizations.

Is Signzy’s Face-Match API Secure?

Yes. Signzy takes data privacy and compliance seriously, ensuring our facial recognition technology is secure. We have implemented advanced security protocols to protect user data from unauthorized access and hacking. Our face-match technology is also verified and certified by leading security agencies.

Regarding the security of personal data, organizations and individuals alike have valid concerns. With the rise in fraudulent activities, financial institutions and organizations must implement robust measures to combat fraud effectively. Signzy’s Face-Match API offers a secure solution for identity verification through facial recognition technology. But what sets it apart from other solutions? The answer lies in its commitment to data privacy and compliance.

One primary concern surrounding facial recognition technology is the potential misuse of personal data. However, we address this concern by implementing stringent security protocols that ensure data protection at all process stages.

From capturing and storing images securely to encrypting sensitive information, Signzy goes above and beyond industry standards to safeguard user data. Additionally, our face-match algorithm uses advanced machine-learning techniques that are continually updated to stay ahead of evolving threats.

The need for transparency when it comes to data privacy

The need for transparency regarding data privacy is of utmost importance in today’s digital age. With the increasing amount of personal information being shared online, individuals and organizations are rightfully concerned about who has access to their data and how it is used.

In the context of facial recognition technology and identity verification, transparency becomes even more crucial. Users want to know that their biometric data is handled securely and responsibly. They want assurance that their face images are not stored or shared without consent.

At Signzy, we understand these concerns and prioritize data privacy above all else. We strive to be transparent with our users by clearly explaining how our Face-Match API works and what measures we have to protect their data.

We ensure transparency through clear communication about the purpose for which users’ facial images are collected. We always obtain explicit user consent before storing or processing any biometric data.

Additionally, we use advanced security protocols to safeguard the confidentiality and integrity of user data.

Security protocols used along with data and consent management

To safeguard user information, our Face-Match API employs industry-leading encryption algorithms. This ensures that all data transmitted between users and our platform is securely encrypted, making it nearly impossible for unauthorized individuals to access or manipulate it.

In addition to encryption, we also implement strict access controls. Only authorized personnel are granted access to user data; even then, they only have permission for specific purposes within their job responsibilities. This helps prevent any potential misuse or mishandling of sensitive information.

Furthermore, we regularly update and monitor our systems for any vulnerabilities or threats. Our dedicated team monitors and promptly addresses emerging security risks with necessary patches or updates.

By implementing these rigorous security protocols and comprehensive data and consent management practices, Signzy prioritizes safeguarding customer privacy throughout identity verification.

Signzy supports data protection and digital privacy

Data privacy is a fundamental right that every individual deserves. With increasing instances of online breaches and unauthorized access to personal information, it has become imperative for organizations to prioritize protecting sensitive data. Signzy recognizes this need and proactively safeguards user confidentiality through encryption techniques and strict access controls.

With technological advancements like Signzy’s Face-Match API and our unwavering commitment towards transparency and protection of user data privacy rights, financial institutions can rest easy knowing that client information remains safe.

Data Fabric To Weave Safer Financial Technology- How It Can Be Used To Improve Financial Services

The excellent offerings of fintech firms derive from the creativity of startup founders and the people they drive to work for their companies, who have changed the financial technology industry as we know it. These innovators see everything possible and let their imaginations run wild when crafting ways to enhance our digital interactions. As a result of this dynamism, some fintech startups have achieved incredible success.

Conventional banks are catching up with newer fintech companies by providing fintech-like experiences and innovative new products. Perhaps these banks are inspired or threatened by what they see in the fintech industry. But, regardless of their drive and motivations, they are increasingly willing to up their game to the plate and compete with novel fintech offerings. This is because fintech and multiple banks — at least those that want to be around in the future — clearly understand that state-of-the-art technology is vital to remain competitive in the sector.

Thus, banks, other financial institutions, and fintech companies deploy new technology to meet their implied promise to customers that if the customers come to them, they will get better services, offerings, and products. This is how AI-artificial intelligence, machine learning, deep learning, big data, and data science have entered the finance industry. Therefore, financial institutions should obtain as much data as possible to use this technology and provide a competitive service and good user experience without compromising data privacy.

The Fundamental Requirement In Financial Technology

This fundamentally requires financial institutions(FIs) to consider the regulatory constraints on data access and use. A further challenge is that, while many companies might be great at collecting mass and personal data, they may actually have difficulties uncovering actionable insights that could help them provide better banking offerings and customer experiences. It certainly does not help that more extensive and older financial companies deal with data silos, legacy systems, and unstructured data. And then, there is the big baddie of cyber security, which leads many executives to hold back when developing new strategies for collecting and using customer data.

Data is the new oil. It’s precious, but they can not use it if it is unrefined. It has to be transformed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity, so all data(even personal data) must be broken down and analyzed to generate value.

Many would agree with this analogy. But unfortunately, companies have difficulty truly managing the vast amount of data and information available in our technologically networking world. This data is stored in various formats and places, making it challenging to fully utilize its power and potential. In addition, this data is increasing exponentially due to the digital footprint that all the customers leave on all the available online services they use.

Data Fabric- Handling The Issue Of Mass And Personal Data In Financial Technology

The problem is that we have too much data. This is precisely where data fabric will help companies. The data fabric’s value is that it enables improved insights because it provides access to more data from an extensive pool of varied and distributed data sources. This is on-premises or in public clouds that businesses usually use and identifies the specific relationships between data to provide better context. In addition, the data fabric ensures proper data governance, which is vital when scaling the utilization of data for analytics and AI.

This ensures proper data governance and allows companies to implement a winning technology strategy. In addition, a data fabric architecture will enable companies to utilize a hybrid and a mixture of multiple clouds, allowing portability in data storage and applications. For instance, IBM’s definition of a hybrid cloud includes on-prem data stores and applications, not necessarily just an on-prem private cloud.

Despite the challenges and hurdles posed by an excess of data, numerous players in the financial technology sphere are moving in the right direction, seeking to overcome the significant obstacles that come with the increased implementation of artificial intelligence and customer demands for personalization. Data fabric addresses multiple issues companies face in their attempts to better and update their technology strategies. Furthermore, it helps institutions comply with strict privacy regulations while using customer data.

Taking It A Step Further

In financial technology services, tech-savvy users long for personalized offerings that consider their financial history and present financial situation to give solutions based on the current requirements and anticipate future needs. To meet this requirement, companies need many data points to make sense of the vast amount of data collected from their customers and give them comprehensive solutions.

If a company knows its customers better and designs solutions based on this knowledge, there will be benefits for the customer and the company.

Many would wish financial companies to take their sophisticated pasts and presents into account to provide them with a more “humanized” banking experience, regardless of the growing use of technology required to reach this.

Faster extraction of the insights is a value of a data fabric; the embedded capability of governance ensures that appropriate data privacy and security is maintained — this is especially critical in the FSS industry. Also, data does not have to be moved and can stay secure at its source per the comment above is essential for highly regulated industries such as Financial Services.

Suppose a company is not up to speed with the better, richer insights gained from properly implementing a data fabric architecture. In that case, it will likely lose out to its competitors. The primary reason is that the customers may move to newer banking providers whose financial solutions are better matched to their current life situation and seamlessly adapt to their future needs.

Racing The Race With Data Fabric

The race is becoming increasingly tense — within the crowded space of new financial competitors, ranging from fintech startups and banks to non-financial companies taking advantage of this embedded-finance trend.

For the future victors in the financial sphere, the right data fabric strategy is not merely an option but a necessity. 

Any such form of revamping or upgrading in any organization, done alone, is not smart. It’s always better to see how experienced experts can help you out. Signzy holds a plethora of resources that can improve your processes to a greater extent. With our AI-driven products and services, you can make things better.

About Signzy

Signzy is a market-leading platform that is redefining the speed, accuracy, and experience of how financial institutions are onboarding customers and businesses – using the digital medium. The company’s award-winning no-code GO platform delivers seamless, end-to-end, and multi-channel onboarding journeys while offering totally customizable workflows. It gives these players access to an aggregated marketplace of 240+ bespoke APIs that can be easily added to any workflow with simple widgets.

Signzy is enabling ten million+ end customer and business onboarding every month at a success rate of 99% while reducing the speed to market from 6 months to 3-4 weeks. It works with over 240+ FIs globally, including the 4 largest banks in India, a Top 3 acquiring Bank in the US, and has a robust global partnership with Mastercard and Microsoft. The company’s product team is based out of Bengaluru, and it has a strong presence in Mumbai, New York, and Dubai.

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