DeFi – why finance needs decentralization?

Maciej Zieliński

04 Mar 2021
DeFi – why finance needs decentralization?

What is DeFi? In what ways is it better than traditional financial solutions?

DeFi stands for "decentralized finance". It is an umbrella term used to describe the various financial applications of Blockchain technology aimed at pushing financial intermediaries away. Blockchain allows multiple entities to store copies of transaction history, removing it from the control of one central source. This is what decentralization means. 

What is the difference in practice? When you pay by credit card for purchases, financial intermediaries such as your bank or Visa or Mastercard mediate in the transaction between you and the seller, having the right to stop it and register it in their private ledger. With DeFi these institutions disappear.

So what is the advantage of DeFi over traditional solutions?

Advantages of DeFi 

Blockchain = safety 

The use of Blockchain Solution technology provides a new level of transparency and security. In DeFi, every user can see where their digital assets are stored and how they are used. Transaction-securing smart contracts, once implemented, are permanently recorded and cannot be changed. In practice, this means that transactions are only executed if both parties comply with the terms of the contract. 

Exclusive control in the hands of users

Most banks are quickly adapting to the online world, tempting users with new applications or solutions to facilitate transactions such as the Polish Blik. However, the money on user accounts is still under the control of the bank. In this respect DeFi is far ahead. Only the owner has the private key to his decentralized wallet and only he has control over the funds stored there.

Democratization of development

Changes in traditional finance take up to decades, and all decisions from the user's perspective are made behind closed doors. In DeFi, innovations are made in real time, and the development itself reflects the idea of democratizing finance. In DeFi, there are no permissions specifying who can introduce new code to the network, so theoretically it is possible for anyone to do so. Moreover, users of the solutions are often involved in the process of voting on changes. 

DeFi – why finance needs decentralization?
Source: defipulse.com

High return on investment

Traditional banks for the public will continue to be the best place to deposit funds for a long time to come. But in fact, why? After all, interest rates are lowered more and more every year, and fees remain the same. 

In contrast, DeFi financially incentivizes users to bet or borrow assets. The interest that would have gone to the bank when borrowing the customer's money is paid directly to the lender. So with DeFi, the user earns interest that is usually retained by the bank.

DeFi Loans

In fact, in the beginning, all lending was peer-to-peer. People lent funds to each other based on more or less forced trust. For obvious reasons, this arrangement was high risk for the lender. Banks have solved the problems with credit trust, but have added additional costs and levels of regulation. 

Crypto lending allows for a return to a peer-to-peer model. They significantly reduce costs by removing intermediaries while providing complete transaction security. 

DeFi allows peer-to-peer lending to exist directly tailored to borrowers and lenders. Typically, a crypto loan is secured by a smart contract and cryptocurrency assets. The interest rate, on the other hand, is based on the value of the funds that the borrower uses as collateral. The loan can be made in both cryptocurrencies and fiat currencies. 

Support for small entrepreneurs

Lending to small and medium-sized entrepreneurs is one of the most important aspects of traditional finance that needs to change. They are the ones who most often struggle to get funding. Crypto loans are a way to make it significantly easier for them.

The key factor to obtaining such a loan is the amount of cryptocurrency funds that the borrower is able to put up as collateral.  Due to the volatility of cryptocurrencies, loans are very much collateral. In practice, this means that they require a collateral ratio of at least 150%, which provides lenders with some safeguards in managing risk. In contrast, traditional creditworthiness is not considered in the evaluation process.

An example of a solution that provides such support to entrepreneurs is Amplify, which additionally combines another plus of cryptocurrency lending: 24-hour availability. 

DeFi – why finance needs decentralization?
Source: duneanalytics.com

DeFi – what next?

Although DeFi has been on the market for only a short time, it is already a viable alternative to many financial services that have been out there for decades. The growing popularity of DeFi shows that users all over the world want to increase control over their finances and start defining the terms on which they use the services. 

Do you have an idea for a DeFi project? Get in touch with our experts who know exactly how to help you realize it.

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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

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!