Real-world Assets in DeFi

Karolina

12 Sep 2023
Real-world Assets in DeFi

In the ever-changing world of finance, Decentralized Finance, or DeFi, is quickly gaining popularity. With over $44 billion secured within its system, DeFi signifies not just numbers but an evolutionary shift in how cryptocurrency investors manage and grow their assets. This groundbreaking approach has introduced crypto enthusiasts to unique ways of increasing their wealth. However, although DeFi has made a significant impact in the crypto world, its presence remains relatively small within the broader global financial sector. For DeFi to fully realize its potential, it must establish a bridge to the traditional financial system, tapping into the immense opportunities presented by institutional investors and established businesses. Integrating real-world assets, specifically tokenized versions of well-established financial instruments, can pave the way for increased stability in DeFi.

DeFi's Present State

Accomplishments

The significance of DeFi's rapid ascent in the world of cryptocurrency cannot be downplayed. It serves as a shining example of success, providing crypto holders with chances to generate passive income through creative methods like yield farming. In contrast, borrowers are granted quick access to loans with favorable terms that outshine offerings from even the most experienced traditional financial institutions.

Challenges

However, DeFi isn't without its challenges. Although it represents a substantial presence in the crypto sphere, it faces numerous internal struggles that put its foundation at risk. One particularly problematic issue is over-collateralization, which results from strict requirements imposed on borrowers. To counter price instability, they're often mandated to provide collateral well above the loan's value. For instance, MakerDAO - a stablecoin issuer - demands a shocking $1,500 deposit as collateral for borrowing only $1,000. Should the collateral's worth fall below this amount, harsh liquidation penalties follow. This situation not only presents considerable risks for borrowers but also hinders DeFi's fundamental mission of democratizing financial access. As a result, numerous global businesses remain constrained and unable to utilize DeFi for funding due to the inflexible crypto-only collateral requirement.

Further exacerbating these issues is the problem of liquidity. The initial excitement that pushed DeFi's total value locked (TVL) to a record $236 billion in November 2021 didn't last. The following 'crypto winter' caused a steep decline, dragging TVL down to just $40 billion by mid-2022. This sharp drop significantly impacted most DeFi tokens, diminishing their value by a staggering 80%-90%. Such turmoil severely disrupted DeFi's incentive model, as yields – dependent on deposited funds and paid out in DeFi tokens – suffered a substantial depreciation.

While the DeFi landscape holds great potential, it is also riddled with these daunting obstacles. To fully unlock its possibilities, a strategic integration with traditional finance is necessary.

Uniting Traditional Finance with Decentralized Finance

The Prospects of Tokenizing Physical Assets

As decentralized finance (DeFi) continues to experience growing pains, the answer may lie in tapping into the strengths of traditional finance. Integrating real-world assets, specifically tokenized versions of well-established financial instruments, can pave the way for increased stability in DeFi. Envision tokenized bonds, equities, debt, and physical assets such as gold, real estate, and art incorporated into the DeFi realm. The inclusion of these more stable assets can serve as a protective barrier for user investments and broaden the reach of DeFi protocols.

What does this integration process entail? Tokenization revolves around creating digital replicas of physical assets on a transparent public blockchain. This revolutionary procedure ensures not only transparent transactions but also removes intermediaries from the equation. As a result, transactions become faster and more streamlined, with costs significantly lower than traditional methods.

DeFi Drawing Attention from Institutions

DeFi's potential has captured not only its supporters' interest but also that of major players within traditional finance. The increase in institutional engagement serves as evidence of this trend. Consider BlackRock's recent submission to the U.S. Securities Exchange Commission (SEC) for approval of a bitcoin exchange-traded fund (ETF). They're not alone – Fidelity, Invesco, Wisdom Tree, and Valkyrie have also filed ETF applications, demonstrating the growing institutional appetite for DeFi exposure. This interest extends beyond ETFs; Banco Santander's efforts to educate its user base on digital assets and the launch of EDX Exchange by giants like Charles Schwab, Fidelity, and Citadel Securities exemplify the strengthening relationship between DeFi and traditional finance.

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Integrating Real-world Assets into DeFi

Perks for Conventional Financial Institutions

Traditional financial institutions are undoubtedly drawn to DeFi. Introducing tokenized versions of traditional stocks, commodities, bonds, art, and real estate can revolutionize financial transactions. Present-day markets heavily rely on intermediaries like stockbrokers, who take a cut of the profits with each transaction. However, DeFi has the potential to change that scenario. Enter smart contracts: these self-executing agreements with coded terms automatically complete transactions as soon as pre-defined conditions are met. Faster transactions, decreased administrative expenses, and unparalleled transparency become realistic expectations under DeFi – a transparent, public ledger accessible to everyone fosters a more accountable financial future.

Advantages for DeFi Protocols

Incorporating real-world assets may be the key to resolving DeFi's issues. These assets are generally more stable than the often volatile DeFi tokens, allowing protocols to aspire toward reduced volatility. Decreased liquidations, minimized fluctuations, and overall ecosystem stability become achievable goals. The real game-changer? DeFi becomes accessible to businesses worldwide. Picture a company tokenizing outstanding invoices for quick credit access or assets like art and real estate becoming fractionalized among numerous investors. Such tokenization efforts introduce exclusive DeFi services like staking and yield farming, revolutionizing market accessibility.

Traditional Finance and DeFi Synergy

Mutual Advantages

Traditional finance and DeFi are not in a rivalry for replacement, but instead, they work together to address deficiencies and capitalize on their distinct strengths. Conventionally, the financial markets demonstrate resilience and consistent growth despite global economic uncertainties, while DeFi brings the potential of democratization, transparency, and efficiency which tend to be insufficient in the traditional system.

During the 'crypto winter,' the DeFi market experienced downturns that revealed its susceptibility to volatility. Nonetheless, with extensive expertise, diverse portfolios, and established risk management approaches, traditional markets offer a stabilizing influence against such drastic fluctuations for DeFi.

Integrated Financial Ecosystem

Merging DeFi and TradFi entails developing a financial ecosystem where assets, digital or physical, circulate seamlessly without the existing cumbersome obstacles. This amalgamation may facilitate the creation of hybrid financial products combining the best features of both domains. Envision a situation where traditional real estate investment, backed by tangible property, is effortlessly tokenized, segmented, and traded on a DeFi platform. Alternatively, consider a conventional bank adopting DeFi protocols for immediate loan approvals with fluctuating interest rates determined by real-time market data.

Conclusion

DeFi's progression from its early stages to its present-day prominence signifies its potential for transformation. To genuinely alter the global financial landscape, it must establish a balanced relationship with traditional finance. By incorporating real-world assets and adopting time-tested methods of conventional finance without sacrificing its fundamental principles of decentralization and transparency, DeFi can pave a way towards an innovative, stable, and inclusive future. This partnership doesn't only signify evolution but also indicates a potential revolution that lays groundwork for a financial world with indistinct boundaries, democratized opportunities, and collectively embraced growth.

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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?

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