KYC

Our KYC service offers mobile SDKs to streamline customer identity verification, ensuring compliance and reducing fraud risks.

The problem

The wide range of regulatory requirements around customer identification, Anti-Money Laundering (AML), and Counter-Terrorism Financing (CTF) are becoming increasingly complex, and businesses face hefty fines for non-compliance. Keeping up with evolving global regulations is challenging for many organizations.Along with that, the traditional KYC processes often involve slow, manual verification steps, requiring large teams to check documents, cross-reference customer information, and assess risk profiles. This results in delays, poor customer onboarding experience, higher operational costs etc.

The solution

The solution automates document validation, facial recognition, and provides a fast, accurate, and secure onboarding process. It is highly adaptable, offering customizable workflows and design, to meet specific regulatory needs and branding requirements, and scale with business growth. Our solution detects low brightness, wrong angle, or inappropriate distance between the identification document and the camera. The system continuously learns from data, improving over time to stay ahead, while delivering a seamless experience for both businesses and customers.

Our team was responsible for

Identifying and gathering requirements
UI/UX
Implementing the web user interface
Integration with Machine Learning technologies

The client

Industries and organizations that require efficient, accurate, and compliant customer identity verification. Our clients could be banks, fintech companies, payment processors, insurance companies, lending and credit Institutions, different cryptocurrency exchanges and wallet providers etc.

Frontend technologies

web UI – Angular

How we used ML

Our system uses Machine Learning (ML) technologies to scan, process and validate a variety of identification documents during a video stream session. Neural networks identify key components from the stream like holograms, watermarks and other, no mаter of the used smartphone or the angle of the camera. Computer vision is used to recognize text from video (OCR) allowing the system to “read” the content effectively. We perform face comparison to guarantee that the person from the selfie is the same as the one from the ID document.