Web 4.0: The Semantic Web

Imagine a time before Facebook (Meta) and Google, way back in the middle of the dot.com bubble. The real inventor of the World Wide Web, Tim Berners-Lee, coined the term Semantic Web in 1999. It represents a web of data being processed by machines, especially since the data is uniquely machine-readable. Stating in his book, Weaving the Web

I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A “Semantic Web,” which makes this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy, and our daily lives will be handled by machines talking to machines. The “intelligent agents” people have touted for ages will finally materialize.”

His vision was better outlined in a 2001 Scientific American article, where Berners-Lee described an evolution of the (then) current Web to a Semantic Web. The Semantic Web, or “Web 3.0,” is an extension of the World Wide Web with its standards by the W3C. Because the Metaverse has taken the moniker of Web 3.0, the Semantic Web has been relegated to Web 4.0. 

Critics continue to question Semantic Web’s feasibility. Proponents argue that several applications remain proven, and the original concept is valid. We shall discuss the current and future potential of the Semantic Web. 

What Is the Semantic Web?

So beyond “machine-readable,” what does the term mean? The definition of the Semantic Web differs significantly from person to person, but for our purposes, the Semantic Web is a virtual environment in which information and data are arranged so that they are processed automatically. 

The machines then read content. Meaning, they interpret data automatically. Artificial intelligence (AI) functionality derives itself from these automated machines, now enabling users to interact with them in a “human” way. 

The machines’ goal is to replicate the experience of engaging with another person. They interpret your data, your meaning, through bodily actions, words, or clicks. Two great examples here are Alexa and Siri, both programmed to record your preferences. 

The Semantic Web’s Ongoing Evolution

The foundation of this evolution depends upon data: sharing, discovery, integration, and reuse.

 One of its main components is the creation of ontologies.  The Web is a web: the components draw connections from each other and exist as a compilation of interlinked units.  Starting in 2006, “RDF” (Resources Description Framework) graphs were used to make data sharing organized.

Ontology: a set of concepts and categories in a subject area which shows their properties and their interrelations.


Graph courtesy of communications of the ACM

The Linked Open Data Cloud’s RDF graphs represent only a small portion of the 650,000 data documents being used in the ongoing research of ontologies.  

After combining ontologies, it was discovered that they possessed significant limitations. General interest in linked data waned as researchers discovered that utilizing data required much more of it. The result: knowledge graphs, presenting ready-to-share data efficiently. 


Image courtesy of Towards Data Science

From this moment, the inner workings of the Semantic Web grew to be increasingly complicated. It is not driven by certain methods inherent to the field, distinguishing it from other data-related areas such as machine learning–which is more focused and easier to improve. 

The Semantic Web is foremost a conceptual vision: that all components far and wide should speak to one another in the same language. Its broad mission but lack of specific focus means it is far less organized than more widely accepted innovations. 

What is Web 4.0?

A good analog is an umbrella. It must combine augmented reality with distributed tech with Big Data, or the major components of Web 3.0, in an overarching web, pun intended. This linking is the essence of Web 4.0. 

Users will have their own avatars, or digital alter egos, for interacting with AI or humans. AI digital assistants do not only respond to requests but remain proactive. 

Let’s take a simple example. You’re on the way to LaGuardia airport, and your driverless Uber is stuck in traffic. Your digital assistant will inform you that with the current traffic patterns, and you’re going to miss your booked flight. However, the assistant already pre-booked a different flight out of JFK airport and can automatically send you there. It changes the route of your Uber, while also informing your family that you will be home only 15 minutes later than expected. All this would be done after receiving your initial “okay.” 

Some may see this is great, while others find it a dystopian future where there is too much access and control over your information. 


Despite the advances going into 2022, the Semantic Web remains difficult to implement given current technology. Computers do not yet fully understand the nuances of human languages, such as tones, mannerisms, phrases, changing in pitch, and so on. 

Specific challenges the Semantic Web must contend with are deceit, inconsistency, uncertainty, vagueness, and vastness. Any system will need to effectively deal with all these issues simultaneously.

Deceit: when the information’s producer intentionally misleads its consumer. Cryptography does reduce this threat. However, additional processes supporting information integrity, or lack thereof, are required. 

Inconsistency: when information from separate sources is combined, resulting in contradictions in logic, flow, or meaning. The deductive reasoning employed by computers fall apart when “anything follows from a contradiction.” Two techniques known to deal with this inconsistency are defeasible reasoning and paraconsistent reasoning. 

Uncertainty: computers don’t like precise concepts with uncertain values. Rather, one should be one, nor two or three too. For example, a medical patient might present symptoms belonging to a range of possible diagnoses. Uncertainties such as these can be addressed with probabilistic reasoning. 

Vagueness: imprecise questions such as, “how many grains of sand make up a pile?” or even concepts like tall and young are complex for a computer to deal with efficiently; everyone has their definition.  Matching query terms with different knowledge bases that provide overlapping but subtly different concepts help. Fuzzy logic is as an additional remedy for the issue of vagueness. 

Vastness: With billions of pages on the Web already, it’s difficult to determine what is specifically needed for certain contexts. SNOMED CT dictionary has 370,000 terms, a relatively small amount, yet the existing system has been unable to eliminate semantically duplicate terms. Future automated reasoning systems will have to deal with inputs on the level of billions or trillions.  

While this list does not cover all the issues in creating the Semantic Web, it demonstrates the most critical challenges to be solved first.  

The World Wide Web Consortium’s Incubator Group for Uncertainty (URW3-XG) lumps these problems all together in their report under a single heading, “uncertainty.”  The techniques of possible solutions will require an extension to the Web Ontology Language (OWL) to, for example, annotate conditional probabilities. This is an area of ongoing research which is yet to “solve” anything yet.

Feasibility of the Semantic Web

Companies which have historically invested in the Semantic Web for decades are still hurdles in bringing it to life. Recently, IBM sold off much of its Watson Health program. Sadly, many of the same problems affecting the Semantic Web 20 years ago remain. 

  • Scalability
  • Multilinguality
  • Reducing information overload with visualization
  • Semantic Web language stability

The Semantic Web’s promise virtually ensures mainstream adoption, but not without more efficient data management solutions. AI remains away from reaching the point of human comprehension and interaction. 


The potential of the Semantic Web is incredible. Semantics is a slow-moving field, and as new discoveries are made, even more pain points will be discovered. Yet we are making progress. Companies have spent fortunes on Semantic Web development and will continue to do so. It will eventually happen. There is a light at the end of the tunnel. We just don’t know the length of that tunnel.   

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

The Token Classification Framework

If you wish to either evaluate a token or develop one of your own, you should understand the differences between the types of tokens. New users join the blockchain world daily, including politicians, regulators, and other decision-makers who can significantly influence the future of this technology. 

They will need clear and relevant knowledge of blockchain’s innerworkings so to make informed decisions. The best tool we have found for evaluating and separating tokens into different categories was created by Untitled INC.

Image courtesy of Untitled INC

This framework has multiple uses. It incorporates all the current token types and enables readers to draw distinct lines between them. 

Its development is ongoing but free for all. It was released for free use under a Creative Commons BY-NC-SA license allowing anyone to share, copy, redistribute it in any format, and to remix, transform, and build upon the material.

It’s a living document. As the field expands, extra dimensions may be added to the framework.

Five Dimensions

Tokens can be divided into five dimensions. 

Image courtesy of Untitled INC

These five dimensions are: 

  1. Purpose. What is the token designed to do?  Misunderstanding the token’s purpose leads to incorrectly calling it a cryptocurrency. It can be used as a cryptocurrency, or it can aid a network’s growth (network token) or simply act as an avenue of investment (investment token). 
  2. Utility. There are four general categories: 
    1. Usage – provides network access or features
    2. Work – provides work to the host system or blockchain
    3. Hybrid – offers both a and b
    4. Useless – no utility
  3. Legal status. As more regulation occurs, this category will evolve, and the presiding jurisdiction may alter a token’s classification. If a token provides no network nor service features, or is not a pure cryptocurrency, then it’s usually classified by regulators as a security token. But some tokens will hover between the two. Current legal frameworks were developed before tokens, and they may have to be adapted. 
  4. Underlying value. Most tokens are created with underlying monetary values, but the sources of these values differ significantly. They can be IOUs for real assets or rather like stocks with commercial or equity links, values which fluctuate. We do find that the network’s value may determine the token’s value, making valuation more interesting relative to traditional investing. However, value is extremely difficult to determine.
  5. Technical layer. Implementation of tokens occurs on different layers of a blockchain-based network. Generally, there are three technical layers:
    1. Blockchain-native tokens – the chain’s native token
    2. Non-native protocol tokens – part of a crypto-economic protocol that sits on the blockchain
    3. DApp tokens – a token on the application level

These five dimensions are complementary, and tokens are not exclusive to only one. Most are assessed through all dimensions. We will see that when we look at the archetypes of tokens, there are strong correlations between them. 

Token Archetypes

Generally, there are four token archetypes:

Cryptocurrencies.These have a use as a store of value (SOV) for wealth, are not controlled by a central authority, and can either be mined or pre-mined. There is no counterparty risk.

Tokenized assets. These provide access to assets such as gold, but also enable microtransactions. The issuing authority has control of the underlying asset, leading to counterparty risk since ownership is tied to one entity. 

Tokenized platform. A platform-like network that is not owned or operated by a central entity. Users start with limited roles, but now roles are available to all network participants. The token’s value, either financially or in terms of utility, moves with the network. 

Shared tokens. This is a tokenized financial instrument for investing in a company, with characteristics of a stock. The tokens improve on the traditional share model by being flexible, and having smart contract programmability. As regulatory frameworks develop, this is the most targeted and vulnerable of the token types.

Tokens As Part of a System for Valuation

Crypto tokens are only one component of a blockchain or distributed network. They are integral but should be evaluated in conjunction with the other two layers of a network: governance and technology.

Evaluating Matrices

It helps to look at some examples to see how the use of a framework aids in valuing any token.

Steem is an incentivized blockchain social media platform that uses three currencies: STEEM, Steam Power, and Steem$. STEEM is used as the currency of the publishing platform, measuring reputations and providing rewards to creators.

STEEM is its own blockchain. Therefore, it’s the native token. It’s used for keeping the network running and is therefore also a network token. Since its use is providing network features, it’s also a usage token, and because it provides a service (network), the legal status is deemed as a utility token.

Kin is both a token and an app inside an app ecosystem. Kin is used to pay for digital services inside several apps available on its network. In Germany, the Kin token could be regarded as a security and regulated as such.  

Kin is not just a cryptocurrency but has functionality and programmability contributing to the user experience. It’s a non-native token, and similar to STEEM, a network token doubling as a cryptocurrency as well. 

It’s also a network token and a usage token, but it differs from STEEM in that it can act as a cryptocurrency outside its system. Therefore, it can be regarded as a security token. 

The classification of tokens feels confusing to many, since they are relatively new and without a well-defined classification system. A good rule of thumb is this: any “crypto” can also be one or more types of “tokens.” 

Augur is a no-limit betting platform enabling gamblers to bet on sports, economics, world events, and more. Augur tokens are used to incentivize “Oracles” on the network who are essential to its function (Oracles bring off-chain data to the chain) as a decentralized prediction market. Oracles report events and receive a share of all network fees for their work. 

Since it was built on the Ethereum network, Augur is a non-native protocol token. Its primary use is to provide a reward for a needed function and is therefore a network token. And since the token is awarded as a result of work for the system, it’s a work token. An Augur token is not used outside the system, however, and so must be exchanged for external use. Thus, it’s also a utility token. 


The Token Classification Framework is a great system for defining cryptocurrencies or tokens. It requires users to think critically about their uses and identify their potential forms of regulation. 

As public sectors across the world dive into tokens, they should invest the time to define them according to their uses and subtypes rather than as part of the larger “crypto” buzzword. Yes, the presiding understanding of token classification remains limited, but the space is growing alongside the potential of blockchain. 

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees. This information should not be interpreted as an endorsement of cryptocurrency or any specific provider, service, or offering. It is not a recommendation to trade.

Solar Energy Is Now Energy on Demand

Researchers at the Chalmers University of Technology in Sweden devised a system that captures solar energy, stores it for up to 18 years, and then releases this energy in the form of either electricity or heat when needed. 

Solar energy could be available on cold, cloudy, or rainy days – when it is most needed. 

This system is called Molecular Solar Thermal (MOST) Energy Storage and is based on a specifically designed molecule. It changes its shape under sunlight and turns into an isomer that can be stored as a liquid. 

The Swedish research team recently collaborated with another team from China’s Shanghai Jiao Tong University that designed a generator to convert the stored energy into electricity. Since this generator is in the shape of an ultra-thin chip, a vital application of the MOST system is self-charging electronics – namely, smartphones, smartwatches, tablets, and laptops.

Source: https://www.chalmers.se/en/departments/chem/news/Pages/Converting-solar-energy-to-electricity-on-demand.aspx

AI Can Predict Earthquakes

Researchers at the Los Alamos National Laboratory used machine learning to identify sounds indicating that a fault will soon rupture.  

Earthquakes happen when blocks of earth near the junctions between tectonic plates suddenly slip along fractures. Built-up friction causes this dramatic “slipping,” and the energy is then released via seismic waves. 

The research team’s machine learning algorithm collected large quantities of data from previous earthquakes and identified a distinct sound pattern preceding earthquakes. 

Using the Lab to Save Lives

The team created “lab earthquakes” using steel blocks and rocky materials to recreate the “slipping” preceding seismic sounds. They trained a computer to analyze the seismic and acoustic signals emitted during movements along a fault.  

They undertook to determine whether the experimental fault’s seismic signal contained information about its current frictional state, leading to an understanding of when the quake might occur and at which magnitude. Using machine learning and AI to study the seismic data, they uncovered a quantitative link between the fault’s frictional state and the signal’s strength. 

This method is now being tested in real-world scenarios to ascertain whether the pattern follows for real earthquakes.  

Source: https://www.lanl.gov/discover/science-briefs/2018/March/0320-earthquake-fault-behavior.php

Smart Irrigation and AI

The future of this technology utilizes artificial intelligence (AI) and more advanced sensors to integrate every possible, measurable factor from the environment. Smart irrigation controllers will then cross-reference this information with botanical databases to determine each plant’s exact water needs in its current landscape.

Local or large-scale farmers alike now hold a clear path for AI-led management of their crops regardless of season, water, temperature, sunlight, one-off events, and more. The potential factors affecting crop yield are extensive. Thanks to machine learning, what would take a lifetime to master can now be understood in a single season.

AI is continuing to prove its use cases across industries. Automated irrigation expands the capacity of farmers worldwide, who may find themselves able to farm more crops across various environments with limited additional costs.

Intercontinental Quantum Cryptography Is Now Here to Stay

Yet a year later, it became part of the first satellite-to-ground quantum network. In 2018, it found itself part of the first intercontinental quantum cryptography service. This was achieved via a videoconference between China and Austria, which was secured by using the Advanced Encryption Standard (AES). 

This demonstrated secure communication on a global scale. It laid out the groundwork for a future quantum internet. 

As MIT Technology Review stresses, many organizations await the commercial availability of this type of secure communication. When will this happen? In the world of COVID-19, chances are sooner rather than later. 

Source: https://www.technologyreview.com/2018/01/30/3454/chinese-satellite-uses-quantum-cryptography-for-secure-video-conference-between-continents/

Recycled Glass, 3D Printing, and Sustainable Concrete

However, experiments show that concrete 3D printing is a significant way to reduce waste in building and manufacturing processes. 

Yet producers still use large amounts of natural sand to make concrete, costing the environment dearly. The good news: researchers have now found a way to replace that natural sand with recycled glass, opening a new worldwide avenue toward the sustainable economy.  

Karla Cuevas’s team from the Technische Universität in Berlin, Germany, developed a method to make 3D-printed lightweight structures using concrete, in which they replaced the sand with waste glass. The team incorporated expanded thermoplastic microspheres into the mixture. This reduced its density and lowered the thermal conductivity by up to 40 percent. 

The result: more robust and more flexible material. It flowed more smoothly in the printer, retained its shape, and hardened in less time. 

Using recycled glass instead of natural sand is easily achievable. Manufacturing now has a new demand for the millions of empty bottles and jars filling up landfills globally while contributing to the sustainable economy.

Source: https://www.sciencedirect.com/science/article/pii/S2352710221005763

Lithium-Sulfur (Li-S) Batteries Will Disrupt Electric Vehicles

However, challenges have slowed the development of Li-S technology, most notably – stability. A recent breakthrough in understanding its cathode chemistry provided a model way of overcoming these obstacles to commercializing Li-S batteries. 

Engineers at Drexel University utilized a carbon nanofiber mesh confining sulfur and vapor dispositions so to prevent adverse chemical reactions. The result is crystallized sulfur unreactive to carbonate electrolytes, mitigating their harmful product – polysulfide. 

They demonstrated that the cathode in their prototype Li-S battery remained stable for 4,000 charge-discharge cycles, or 10 years of regular use. This Li-S battery also provided more than three times the capacity of its lithium-ion counterpart. 

Even though they are trying to fully understand the fine print behind their discovery of monoclinic sulfur at room temperature, this breakthrough helps pave the way to commercialized Li-S batteries for electric vehicles worldwide. 

Source: https://drexel.edu/news/archive/2022/february/lithium-sulfur-cathode-carbonate-electrolyte

Applications of NFTs in Commerce and Reality

However, the presiding thought is that these digital representations will only have limited shelf lives. In a few years, the same “Apes” which collectors are paying hundreds of thousands for will wane in popularity and eventually be worth nothing. Billions of dollars may indeed be earned or lost.  

Yet many have asked if NFTs have practical applications beyond these two worlds. Are they helpful in real life? 

While it’s difficult to think of NFTs beyond their 2D or 3D images, they do have several practical applications. At their core, NFTs represent either digital or physical content or even intangible property. Let’s review some of these applications. 


During World War II, much of Europe’s most prized masterpieces were taken by force. In other words, their chain of custody was lost. “Fakes” replaced some of these works, while some remained lost for decades or forever. 

With NFTs, the original artworks are tagged to their masters; they are tracked. Originality is ensured. One of the most traditional of settings, an auction house, has the most to gain from this new technology. 

Also, physical artworks can be converted into NFTs (such as with Banksy), and vice versa. Ownership of art is thus being fractionalized (if desired by the seller), so now you can own 1/10,000 of a Banksy as well.  


Gaming uses NFTs with in-game items available for purchase, trade, and reward. NFTs can be used across platforms, allowing for longer shelf lives even if interest in a particular game decrease. This facilitates consistent revenue streams for brands or game developers. 

In-game trading becomes easier between players, increasing demand, and the values of NFTs themselves. With ownership and transaction tracking, players need no longer worry on the possibility of a scam, since the trading itself is near-instantaneous.

Real Estate

Real estate and NFTs function perfectly together. NFTs can be the digital representations of deeds that prove ownership. Title searches become obsolete since the NFT owners are the landowners, potentially cutting expenses for land transfers. Further, NFT’s timestamping capability tracks the changes in any property’s value, providing for simplified taxation. 

NFTs accelerate property transfers, through the option of selling without intermediaries who often charge excessive fees.  

The use of smart contracts could even facilitate decentralized rental services for various properties, automating payments and other administrative processes. 

Supply Chains

Many products throughout the world have issues identifying their origins, particularly in the food and beverage industry. Improper tracking facilitates the risk of E. coli.

Any product in theory could have an attached NFT indicating a specific identifier and accompanying information, which would be immutable and public. Supply chains are already making us of several applications

Medical Records

NFTs are capable of storing medical records, but they don’t have to compromise patient confidentiality or risk malicious manipulation by unqualified sources because, as they are blockchain-based, they are validated by multiple nodes first. 

Hospitals, insurance companies, and other medical organizations are exploring narrowly defined NFT use cases for improving operations, including patient verification and medical procedure recording. Confidentiality is ensured. 

For example, NFT Birth Certificates are issued to newborns at delivery so to provide a lifelong and effective way of identifying the child and their linked adults. This is the evolution of the paper birth certificate. 

Event, Travel, and Other Tickets

Tickets will be in NFT form, including entry and parking passes programmed to have uniquely assigned IDs and driving rights. This reduces the risks of counterfeiting, fraud, and identity theft. 

An owner will require only one token rather than multiple tickets or cards, or even cash. Transportation will be facilitated through longer journeys having multiple checkpoints. 

Academic Credentials

NFTs can indicate attendance records, degrees earned, and other important information, all of which must remain immutable. 

If utilized, NFTs streamline multiple administrative processes within academic institutions while championing the original essence of blockchain—permanent, verified, and immutable. Paper certificates would become only ceremonial. 


Since the rampant claims of voter fraud in the USA’s 2020 election, there have been multiple calls for required IDs to be shown before voting. However, mandating IDs risks disenfranchising those who lack copies of their identification or voter registration. 

Voting issues such as these can be solved by integrating NFTs. NFTs can provide identity and residence verification without physical documentation. They drastically reduce voter fraud as well. 

Product Authenticity

Buyers can now be confident that their purchases are authentic.  Because a blockchain permanently stores product information, confirming rarity and authenticity is always possible.

NFTs store information about harvesting, manufacturing, and fair trade. Yet this does not stop at the commercial level: several companies are using NFTs at the design and prototyping levels.  

Fake drugs and medicines can be prevented with NFT tracking. For example, you scan a bottle of a drug or supplement purchased online and verify its entire journey and use-by date. Sellers who claim legitimate products but are selling counterfeits will be exposed through NFT’s inherent transparency. 

Intellectual Property (IP)

Patents are well suited for NFTs because they allow users to provide proof of ownership of nearly anything, which is not possible with traditional IP tools such as trademarks and copyrights.  

The chain of history from the time of creation through every generation of ownership can be distinguished with timestamps. The immutable nature of a blockchain forever defines the original creator of an IP and makes infringement claims impossible. Any blockchain is a public ledger.  


Nearly everything in the Metaverse will be in NFT form, including the virtual representation of individuals, or “avatars.” Products will be paid for with fungible tokens, but products or items themselves will be in NFT form. 

NFTs will effectively be tied to your avatar, as will its reputation. You could potentially sell or rent your avatar out. 


Blockchain is still young at 13 years old, and NFTs are younger still. They not only represent new explorations of art but all collectibles or things, not currency. 

Likely, we will see NFTs become integral parts of our lives given their incredible security, transparency, and utility. Their potential use cases include almost anything, from intellectual property to medicine to real estate. As the Metaverse expands, this will become more and more apparent. 

The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

Smart Contracts in the Insurance Industry

The ultimate challenge concerning technology adoption is deciding where to begin. For many businesses, it’s critical to start with savings. 

So in the case of insurance companies, savings equates to fraud prevention. Why? The insurance business deals with false claims and similar charades totaling billions of dollars yearly. The Coalition Against Insurance Fraud estimates that insurance fraud costs the United States $80 billion a year.

Notwithstanding, insurance providers remain slow to adapt to emerging technologies such as smart contracts and blockchain. These two technologies carry the potential to eliminate insurance fraud by creating a transparent method of tracking transactions throughout the insurance value chain.

Why Blockchain?

It’s more important to understand how blockchain works, as opposed to the technology behind it. Blockchain is similar to Google Docs. It’s a ledger enabling multiple people to view and edit simultaneously. Satoshi Nakamoto founded it in 2008 to manage bitcoin transactions in a transparent and incorruptible manner. Over time, enthusiasts and followers applied the bitcoin platform to other applications in the financial services and insurance industries.

According to key blockchain industry statistics, it’s rapidly being integrated into the global financial sector, particularly banking. Banks in Japan, the United States, Belarus, Switzerland, and a few other countries are already accepting cryptocurrency transactions as part of their ecosystems, and more will follow suit soon.

In the insurance industry, three general applications are expected to take root:

  1. Smart contracts for insurance policy execution will increase underwriting and claims processing efficiencies. Smart contracts are self-executing contracts in which the terms of the agreement are directly written into lines of code. The code and agreements contained within will eventually exist across a distributed, decentralized blockchain network.
  2. Firms using a ledger-based mechanism will better manage risk and eliminate sources of fraud in insurance claims.
  3. The automated flow of information will reduce laggards in the processes between insurers and reinsurers. 

In its recent publication: Global Smart Contracts Market, Market Research Future projects that the global smart contracts market will reach approximately $300 million by the end of 2023, or by a 32% CAGR from 2017 to 2023.

Smart Contracts for Insurance

Smart contracts on the blockchain solve many of the insurance industry’s current problems. Overburdened with numerous uncertainties and longstanding issues, it desperately needs to regain the public’s trust.  

According to YouGov polls, people in the United States hold mixed feelings about insurance companies. 47% of Americans believe in or trust them, while 43% do not.

Source: https://www.propertycasualty360.com/2020/01/24/how-blockchain-and-smart-contracts-will-disrupt-insurance/

Even though customers believe that an insurer’s ultimate goal is to pay as little as possible, insurance companies are not without their own aches and pains. Very often, policyholders cheat and file false claims to receive payouts. As a result, the lack of trust is mutual. 

Smart contracts carry the potential to restore confidence and render intermediaries obsolete. Smart insurance code contains software algorithms able to remove administrative barriers, predetermine all insurance payout scenarios, and automatically execute contract terms, leaving no room for manipulation on either side.

The Benefits of Smart Contracts

There are several benefits to deploying smart contracts with insurance. 

Transparency Reduces Fraud

The decentralized and open nature of blockchains provides immediate transparency. Everybody sees the transactions logged into blockchain databases because they have no owners. If changes are made, all parties are notified—meaning, no inconsistencies can be hidden. 

Automating Tasks

All smart contract-related processes remain automatic and secure within the blockchain. The main advantage of smart contract insurance: It eliminates mediators and human intervention. This reduces the possibility of manipulation by third-party participants. Furthermore, when used for smart contract insurance, blockchain enables businesses to review their procedures and processes easily.

Claim Verification

In insurance, blockchain smart contracts completely replace claims processes. There are no additional documents required: only predefined rules are required to settle claims. Ultimately, we have faster processes and lower costs for insurers. 

Policy Documents

Insurance companies store policy documents on multiple ledgers, making them virtually impossible to lose. Smart contracts similarly prevent data loss and damage due to their technical characteristics.

Assessing Risk

Using blockchains, insurance companies may now include cutting-edge risk assessment models into their smart contracts. 

IDs are quickly confirmed and reinforced with fresh data, obviating the need for time-consuming ID verification processes. A smart contract scans all of an individual’s information and automatically assesses risk, saving time and effort over any pre-existing, manual process. 

Stages of a Smart Contract’s Lifecycle

There are four stages to a smart contract’s lifecycle, as illustrated by the graphic below.

Source: https://www.researchgate.net/figure/Smart-Contracts-LifeCycle-1-Creation-of-smart-contracts-Several-involved-parties-first_fig1_340376424


The parties have reached an agreement on the terms and objectives of the contract. Following that, the agreement is transformed into code through the development processes indicated above.


When a smart contract is added to the blockchain, it becomes public and can be accessed via the public ledger. At this point, both contractors must meet all the contract’s requirements, and pay a fee or send an asset in order for this “block” to be added. Further, transfers made to the smart contract’s wallet address are halted until all preconditions are met.


After a smart contract is executed, new transactions follow, which in turn are put on the same public ledger. The consensus mechanism inherent to blockchain verifies the legitimacy of these transactions.  


After all, assets are unfrozen and all transactions confirmed, a smart contract is deemed complete. 

Barriers Facing Smart Insurance Contracts

Despite tremendous excitement, the public still widely misunderstands the concept that is blockchain. The same holds true for deciphering how to make smart contracts the watertight universal solution for companies. Here are some of the concerns preventing smart contracts from becoming more widely used.

  • The scope of the contract is limited. Things that are simple to do on paper can be challenging to translate into code. Especially, since most businesses begin developing smart contracts with basic models, based on the classical formula, if X occurs, then Y follows.
  • The technology is complex. Building a sophisticated smart contract in insurance necessitates a certain level of programming expertise. To begin with, only Ethereum experts can create a well-functioning contract. Naturally, it’s a difficult task because the technology is complex, new, and requires a thorough understanding of software development.
  • Poor coding leads to contractual errors. Smart contracts are difficult to understand. Because they are carried out sequentially, the contract will not be carried out even if one critical component is missing. Despite the fact that eliminating human input is one of the primary benefits of smart contracts in insurance, smart contracts still require human involvement during the development stage.
  • Legal regulations remain limited. Despite the keen interest of public institutions, smart contracts appear largely unregulated. 


Even though smart contracts are not yet mature, they have already had an impact on custom insurance applications. Using smart contracts, insurers cut administrative and claims costs, boost transparency, and avoid fraud by automating their policies and services. 

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.

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