Validation and identity verification with Machine Learning

In general, the identity verification guarantees that the person behind a process is who they claim to be, avoiding fraud and identity theft. Its importance has grown significantly in recent years. In Mexico, for example, an estimated 20% of banking organizations has identity validation methods automated systems and a 60% is on the way to implement it.

Additionally, it is expected that its global market size go from $ 7.6 billion in 2020 to $ 15.8 billion in 2025.

Why has the importance of validating identity grown? 

The main factors driving this interest are the digitization of the economy and the increase in fraudulent activities and identity theft. The latter crime is the fastest growing in Mexico and the world; Only in 2019 caused financial service users losses of 2,965 million pesos, according to Condusef data

Of course, count on identity validation methods brings additional benefits to your business, such as competitive positioning, regulatory compliance, improved user experience and increased brand image and trust.

Fortunately, technology advances by leaps and bounds and today you have at your disposal Machine Learning to develop this process.

How Identity Verification Works With Machine Learning

 Machine Learning  is a branch of AI The objective of which is to equip applications or machines with intelligence through algorithms trained to identify patterns among huge amounts of data, allowing them to learn and improve as time goes by. 

In the field of identity verification, It has been possible to take advantage of this technology to capture and identify biometric patterns and compare them with samples or data previously collected and stored in the system. Thus, you find:   

  • Voice biometrics.
  • Fingerprint registration.
  • Facial biometry.
  • Iris.

Among all these, facial recognition solutions for identity validation are one of the best alternatives. 

This is based on mathematical models, which are the algorithms that are generated based on some starting data. Thus, the system performs an analysis and comparison of the face patterns identified in real time, with those collected in a photograph taken in advance in a registration process or with that of a document that proves that the individual is who he claims to be. , like RUN. 

This analysis compares in a matter of seconds multiple patterns that make a face unique and unrepeatable, such as the distance between the ears, the size of the nose, the width of the chin, etc.   

From this examination, the system concludes that there is a certain percentage of coincidence between the individual of the selfie or of the video in real time and the one that appears in the photograph of the document or previously registered. 

Of course, if the identity verification is carried out remotely using the photograph of a document, it is necessary that the system also carry out a validation, using technologies such as optical recognition that analyzes the elements that compose it to determine if it is false or original. .

Validate identity using images is reliable. However, to enhance the results you can complement it with another biometric technique and / or with other methods such as two-factor authentication.

In Codster, a leading firm in the development of artificial intelligence applications, you can create technological solutions for identity verification tailored to your needs. If you want to know more, do not hesitate to contact. 

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