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How to Ensure Compliance with Anti-Money Laundering (AML) and Know Your Customer (KYC) Regulations in Tokenization + BONUS: Top 5 KYC Providers!

Karolina

16 Jun 2023
How to Ensure Compliance with Anti-Money Laundering (AML) and Know Your Customer (KYC) Regulations in Tokenization + BONUS: Top 5 KYC Providers!

In recent years, tokenization - the act of turning real-world assets or rights into digital tokens on a blockchain - has garnered significant attention. Powered by blockchain technology, artificial intelligence, and cryptocurrencies, this innovative method has transformed industries like finance, real estate, supply chain, among others. Nevertheless, as tokenization becomes more widely adopted, adhering to Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations becomes increasingly important.

AML and KYC compliance within tokenization is imperative for tackling potential risks linked to financial crimes such as money laundering, terrorist financing, and fraud. Through the adoption of stringent compliance measures, businesses can showcase their dedication to upholding integrity, security, and transparency in the tokenization ecosystem.

This article delves into strategies and best practices for achieving AML and KYC compliance in tokenization. By abiding by these principles, companies active in the tokenization domain can protect their operations, stakeholders, and further solidify the industry's overall credibility and sustainability.

Table of Contents

Understanding Tokenization and Its Regulatory Landscape

Tokenization

Tokenization, a procedure involving the transformation of tangible and intangible assets or rights into digital tokens on a blockchain, plays an essential role in various domains such as financial securities, real estate properties, intellectual property, and even tangible assets like art or collectibles. By harnessing the advantages of blockchain technology – immutability, transparency, and decentralization – tokenization offers a secure and efficient way to represent and transfer assets.

The regulatory environment of tokenization and adherence to AML and KYC regulations

With increasing adoption of tokenization, global regulatory bodies actively evaluate its ramifications and devise frameworks to mitigate potential risks and ensure compliance. The regulations concerning tokenization differ across jurisdictions – some embrace innovation while others enforce strict rules.

Adhering to Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations is crucial in the realm of tokenization. AML regulations aim to block the integration of illicit funds into the financial system, while KYC regulations center on customer identity verification to prevent money laundering and terrorist financing activities. Complying with these guidelines allows businesses to reduce financial crime risks, uphold operational integrity, and instill trust among stakeholders.

What is KYC?

KYC is a requirement by which regulated entities must obtain personal information about a customer to ensure that their services are not misused and ensure that people applying for financial services are not on sanctions or PEP lists.

What is AML?

AML is a framework of laws and policies aiming to prevent and identify financial crime, including everything from terrorist financing to money laundering. For most institutions, AML will start with KYC — knowing your customers — and will then continue through monitoring financial activity and reporting suspicious behavior. 

Read more here

The importance of AML and KYC regulations in tackling financial crimes

AML and KYC regulations serve as vital tools in combating financial crimes such as money laundering, terrorist financing, and fraud. Money laundering concerns disguising illegal funds’ origins to make them appear legitimate, while terrorist financing entails funding terrorist activities.

Employing comprehensive AML and KYC procedures enables businesses to participate in the prevention, detection, and reporting of suspicious activities. Financial institutions and businesses engaged in tokenization must perform rigorous due diligence on customers, scrutinize transactions for unusual patterns, and inform the relevant authorities of any suspicious activities. Complying with AML and KYC regulations not only aids in thwarting financial crimes but also protects businesses' reputation and fosters a secure and reliable tokenization ecosystem.

Read more about Regulatory Landscape

Applying AML and KYC Compliance Measures to Tokenization

Comprehensive Customer Due Diligence (CDD) Execution

The significance of CDD for validating token holders' identities

  • In the tokenization process, customer due diligence (CDD) plays a crucial role in verifying and authenticating token holders' identities.
  • CDD assists in confirming customers' true identities, evaluating their risk profiles, and uncovering any potential participation in unlawful activities.
  • Thorough CDD helps companies adhere to KYC regulations, reduce the likelihood of money laundering, and improve the overall security of their tokenization platform.

The primary components of CDD, including customer identity verification, risk profile assessment, and transaction activity monitoring

  • Customer identity verification: Implement strong identity verification methods to authenticate token holders. This could entail gathering government-issued ID documents, performing biometric verification, or using digital identity solutions.
  • Risk profile assessment: Determine each customer's risk by considering factors such as occupation, jurisdiction, transaction history, and funding source. Allocate risk scores or categories to effectively prioritize monitoring efforts.
  • Transaction activity monitoring: Create mechanisms to track token transactions in real-time. Employ transaction monitoring systems that can detect suspicious patterns like large transactions, frequent transfers, or interactions with high-risk jurisdictions.

Strengthened Transaction Monitoring

The need for real-time token transaction monitoring to identify suspicious actions

  • It is vital to monitor token transactions in real-time to detect and prevent potential money laundering or fraudulent activities.
  • Prompt detection and response to suspicious patterns, such as multiple high-value transactions or rapid fund transfers, are made possible by real-time monitoring.

Blockchain analytics tools' role in tracking and analyzing transaction patterns

  • Blockchain analytics tools take advantage of blockchain technology's transparency to monitor and examine token transactions.
  • These tools allow businesses to trace fund flows, pinpoint addresses connected to suspicious activities, and gain insights into transaction patterns that may signal potential money laundering or other illicit actions.

Establishing Solid AML and KYC Policies and Procedures

The significance of creating well-defined AML and KYC policies specifically designed for tokenization:

  • For companies engaged in tokenization, it is vital to establish detailed AML and KYC policies that address tokenized assets' unique features and risks.
  • These policies should take into account regulatory requirements, industry best practices, and the specific nature of tokenized transactions to ensure compliance efficacy.

Collaborative Efforts with Regulatory Authorities and Compliance Specialists

By actively collaborating with regulatory authorities, businesses can remain informed about current regulatory progress and foresee any alterations that may affect their AML and KYC compliance obligations due to tokenization.

Collaborating with experienced compliance advisors who have deep knowledge of AML, KYC, and tokenization regulations is critical for creating and executing effective compliance structures for tokenization ventures.

These professionals can offer guidance on crafting strong AML and KYC policies, carrying out risk evaluations, and enforcing industry-standard and regulator-approved compliance processes.

TOP 5 KYC Providers

  1. Fractal

Fractal offers user onboarding for compliance use cases like KYC and KYB. It covers all kinds of KYC levels all in one price. Projects can also make use of its liveness solution which guarantees unique users for e.g. airdrops or crypto games without ever revealing the identity of the user.

  1. SolidProof

SolidProof is a German-based KYC provider with a simple, efficient, and smooth process that adheres to the highest security standards. In addition, the company’s services are affordable, have no hidden costs, and offer a free audit for every project.

  1. Identity.com

Another popular KYC solution is Identity.com. The project focuses on decentralized identity verification and offers a marketplace and gateway protocol. The company does not trade personal information, which increases security and privacy. The project also focuses on decentralization.

  1. Elliptic

Elliptic is another excellent solution for KYC and compliance needs for traditional financial institutions and crypto and NFT projects. They offer various services, including wallet screening, transaction monitoring, VASP screening, and enhanced due diligence.

  1. Blockpass

Blockpass is famous for its quick, easy signup process and automated KYC solution. Blockpass offers a full-service, comprehensive solution for all onboarding needs – including AML watchlist checks. So if you’re looking for a fast, simple, and easy-to-integrate solution, Blockpass is worth considering.

Conclusion

Complying with Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations is essential in tokenization to combat financial crimes, ensure the integrity of operations, and foster trust within the tokenization ecosystem. By implementing robust AML and KYC compliance measures, businesses involved in tokenization can mitigate the risks of money laundering, terrorist financing, and fraud.

The implementation of thorough customer due diligence (CDD), enhanced transaction monitoring, and the development of comprehensive AML and KYC policies tailored to tokenization are vital steps in ensuring compliance. Leveraging technologies such as artificial intelligence (AI) and blockchain analytics tools enhances the efficiency and accuracy of compliance efforts.

Are you interested in tokenization? Contact us!
Start fundraising for your project with Nextrope Launchpad Platform

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?
Table of Contents

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

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