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What is tokenization? | McKinsey

is tokenization? | McKinsey

Skip to main contentWhat is tokenization?March 6, 2024 | ArticleSharePrintDownloadSaveTokenization is the process of creating a digital representation of a real thing. Tokenization can be used to protect sensitive data or to efficiently process large amounts of data.A terracotta soldier figurine emerging from a digital tablet. The soldier looks digitized at it's base but becomes a solid form at it's top.

(6 pages)

Events of the last few years have made it clear: we’re hurtling toward the next era of the internet with ever-increasing speed. Barely a week goes by without an important new breakthrough in generative AI (gen AI). McKinsey estimates that gen AI could add up to $4.4 trillion annually to the global economy; by comparison, the United Kingdom’s GDP was about $3 trillion as of 2021.

Get to know and directly engage with senior McKinsey experts on tokenization

Prashanth Reddy is a senior partner in McKinsey’s New Jersey office, and Robert Byrne is a senior partner in the Bay Area office.

AI is a big story, but it’s not the only game in tech town. Web3 is said to offer the potential of a new, decentralized internet, controlled by participants via blockchains rather than a handful of corporations. Payments is also a field in flux: one in two consumers in 2021 used a fintech product, primarily peer-to-peer payment platforms and nonbank money transfers.

What do AI, Web3, and fintech all have in common? They all rely on a process called tokenization. And tokenization stands to revolutionize the way we exchange ideas, information, and money.

Let’s get specific: tokenization is the process of issuing a digital, unique, and anonymous representation of a real thing. Sometimes the token is used on a (typically private) blockchain, which allows the token to be used within specific protocols. Tokens can represent assets, including physical assets like real estate or art, financial assets like equities or bonds, intangible assets like intellectual property, or even identity and data. Tokenization also makes AI tools possible, by enabling large language models (LLMs) that use deep learning techniques to process, categorize, and link pieces of information—from whole sentences down to individual characters. And payment tokenization protects sensitive data by generating a temporary code that’s used in place of the original data.

Tokenization can create several types of tokens. From the financial-services industry, one example would be stablecoins, a type of cryptocurrency pegged to real-world money designed to be fungible, or replicable. Another type of token is an NFT—a nonfungible token, meaning a token that can’t be replicated—which is a digital proof of ownership people can buy and sell. Yet another example could simply be the word “cat”; an LLM would tokenize the word “cat” and use it to understand relationships between “cat” and other words.

Tokenization is potentially a big deal. Industry experts have forecast up to $5 trillion in tokenized digital-securities trade volume by 2030.

In this Explainer, we’ll drill down into how tokenization works and what it might mean for the future.

Learn more about McKinsey’s Financial Services Practice.

How does tokenization work in large language models?

Before answering this question, let’s get some basics down. Deep learning models trained on vast quantities of unstructured, unlabeled data are called foundation models. LLMs are foundation models that are trained on text. Trained via a process called fine-tuning, these models can not only process massive amounts of unstructured text but also learn the relationships between sentences, words, or even portions of words. This in turn enables them to generate natural language text, or perform summarization or other knowledge extraction tasks.

Here’s how tokenization makes this possible. When an LLM is fed input text, it breaks the text down into tokens. Each token is assigned a unique numerical identifier, which is fed back into the LLM for processing. The model learns the relationships between the tokens and generates responses based on the patterns it learns.

There are a number of tokenization techniques commonly used in LLMs:

Word tokenization splits text into individual words or word-like units, and each word becomes a separate token. Word tokenization might struggle with contractions or compound words.

Character tokenization makes each character in text its own separate token. This method works well when dealing with languages that don’t have clear word boundaries or with handwriting recognition.

Subword tokenization breaks down less frequently used words into units of frequently occurring sequences of characters. Subword tokens are bigger than individual characters but smaller than entire words. By breaking words into subword tokens, a model can better handle words that were not present in the training data. Byte pair encoding (BPE) is one subword tokenization algorithm. BPE starts with a vocabulary of characters or words and merges the tokens which most often appear together.

Morphological tokenization uses morphemes, which are individual words or parts of words that carry specific meanings or grammatical functions. The word “incompetence,” for example, can be broken down into three morphemes: “in-” (a prefix indicating negation), “competent” (the root), and “-ence” (a suffix indicating a state or quality). In morphological tokenization, each morpheme becomes a token, which enables LLMs to handle word variations, understand grammatical structures, and generate linguistically accurate text.

The type of tokenization used depends on what the model needs to accomplish. Different tokenization methods may also be combined to achieve the required results.

What technologies make Web3 possible?

As we’ve seen, Web3 is a new type of internet, built on new types of technology. Here are the three main types:

Blockchain. A blockchain is a digitally distributed, decentralized ledger that exists across a computer network and facilitates the recording of transactions. As new data are added to a network, a new block is created and appended permanently to the chain. All nodes on the blockchain are then updated to reflect the change. This means the system is not subject to a single point of control or failure.

Smart contracts. Smart contracts are software programs that are automatically executed when specified conditions are met, like terms agreed on by a buyer and seller. Smart contracts are established in code on a blockchain that can’t be altered.

Digital assets and tokens. These are items of value that only exist digitally. They can include cryptocurrencies, stablecoins, central bank digital currencies (CBDCs), and NFTs. They can also include tokenized versions of assets, including real things like art or concert tickets.

As we’ll see, these technologies come together to support a variety of breakthroughs related to tokenization.

What are the potential benefits of tokenization for financial-services providers?

Some industry leaders believe tokenization stands to transform the structure of financial services and capital markets because it lets asset holders reap the benefits of blockchain, such as 24/7 operations and data availability. Blockchain also offers faster transaction settlement and a higher degree of automation (via embedded code that only gets activated if certain conditions are met).

While yet to be tested at scale, tokenization’s potential benefits include the following:

Faster transaction settlement, fueled by 24/7 availability. At present, most financial settlements occur two business days after the trade is executed (or T+2; in theory, this is to give each party time to get their documents and funds in order). The instant settlements made possible by tokenization could translate to significant savings for financial firms in high-interest-rate environments.

Operational cost savings, delivered by 24/7 data availability and asset programmability. This is particularly useful for asset classes where servicing or issuing tends to be highly manual and hence error-prone, such as corporate bonds. Embedding operations such as interest calculation and coupon payment into the smart contract of the token would automate these functions and require less hands-on human effort.

Democratization of access. By streamlining operationally intensive manual processes, servicing smaller investors can become an economically attractive proposition for financial-services providers. However, before true democratization of access is realized, tokenized asset distribution will need to scale significantly.

Enhanced transparency powered by smart contracts. Smart contracts are sets of instructions coded into tokens issued on a blockchain that can self-execute under specific conditions. One example could be a smart contract for carbon credits, in which blockchain can provide an immutable and transparent record of credits, even as they’re traded.

Cheaper and more nimble infrastructure. Blockchains are open source, thus inherently cheaper and easier to iterate than traditional financial-services infrastructure.

There’s been hype around digital-asset tokenization for years, since its introduction back in 2017. But despite the big predictions, it hasn’t yet caught on in a meaningful way. We are, though, seeing some slow movement: US-based fintech infrastructure firm Broadridge now facilitates more than $1 trillion monthly on its distributed ledger platform.

Introducing McKinsey Explainers: Direct answers to complex questionsExplore the series

Learn more about McKinsey’s Financial Services Practice.

How does an asset get tokenized?

There are four typical steps involved in asset tokenization:

Asset sourcing. The first step of tokenization is figuring out how to tokenize the asset in question. Tokenizing a money market fund, for example, will be different from tokenizing a carbon credit. This process will require knowing whether the asset will be treated as a security or a commodity and which regulatory frameworks apply.

Digital-asset issuance and custody. If the digital asset has a physical counterpart, the latter must be moved to a secure facility that’s neutral to both parties. Then a token, a network, and compliance functions are selected—coming together to create a digital representation of the asset on a blockchain. Access to the digital asset is then stored pending distribution.

Distribution and trading. The investor will need to set up a digital wallet to store the digital asset. Depending on the asset, a secondary trading venue—an alternative to an official exchange that is more loosely regulated—may be created for the asset.

Asset servicing and data reconciliation. Once the asset has been distributed to the investor, it will require ongoing maintenance. This should include regulatory, tax, and accounting reporting; notice of corporate actions; and more.

Is the time finally right for tokenization to catch on?

Maybe. Financial-services players are already beginning to tokenize cash. At present, approximately $120 billion of tokenized cash is in circulation in the form of fully reserved stablecoins. As noted above, stablecoins are a type of cryptocurrency pegged to a physical currency (or commodity or other financial instrument) with the goal of maintaining value over time.

Financial-services players may be starting to play with tokenizing—theirs is the biggest use case to date—but it’s not yet happening on a scale that could be considered a tipping point.

That said, there are a few reasons that tokenizing might take off. For one thing, the higher interest rates of the current cycle—while a cause for complaint for many—are improving the economics for some tokenization use cases, particularly those dealing with short-term liquidity. (When interest rates are high, the difference between a one-hour and 24-hour transaction can equal a lot of money.)

What’s more, since tokenization debuted five years ago, many financial-services companies have significantly grown their digital-asset teams and capabilities. These teams are experimenting more and continually expanding their capabilities. As digital-asset teams mature, we may see tokenization increasingly used in financial transactions.

Learn more about McKinsey’s Financial Services Practice, and check out Web3-related job opportunities if you’re interested in working at McKinsey.

Articles referenced:

“Tokenization: A digital-asset déjà vu,” August 15, 2023, Anutosh Banerjee, Ian De Bode, Matthieu de Vergnes, Matt Higginson, and Julian Sevillano

“Tokenizing nontraditional assets: A conversation with Ascend Bit’s Brian Clark,” March 17, 2023, Andrew Roth

“Web3 beyond the hype,” September 26, 2022, Anutosh Banerjee, Robert Byrne, Ian De Bode, and Matt Higginson

“How can healthcare unlock the power of data connectivity?,” December 9, 2021, Prashanth Reddy

Want to know more about tokenization?Talk to usRelated ArticlesPodcastTokenizing nontraditional assets: A conversation with Ascend Bit’s Brian ClarkArticleTokenization: A digital-asset déjà vuArticleWhat is central bank digital currency (CBD

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Tokenization

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Data Security

What is Tokenization

Tokenization replaces a sensitive data element, for example, a bank account number, with a non-sensitive substitute, known as a token. The token is a randomized data string that has no essential or exploitable value or meaning. It is a unique identifier which retains all the pertinent information about the data without compromising its security.

A tokenization system links the original data to a token but does not provide any way to decipher the token and reveal the original data. This is in contrast to encryption systems, which allow data to be deciphered using a secret key.

How Data Tokenization Works

Tokenization, in relation to payment processing, demands the substitution of a credit card or account number with a token. The token has no use and is not connected to an account or individual.

The 16 digits primary account number (PAN) of the customer is substituted with a randomly-created, custom alphanumeric ID. The tokenization process removes any connection between the transaction and the sensitive data, which limits exposure to breaches, making it useful in credit card processing.

Tokenization of data safeguards credit card numbers and bank account numbers in a virtual vault, so organizations can transmit data via wireless networks safely. For tokenization to be effective, organizations must use a payment gateway to safely store sensitive data.

A payment gateway is a merchant service offered by an e-commerce application service provider that permits direct payments or credit card processing. This gateway stores credit card numbers securely and generates the random token.

Tokenization in a nutshell

Payment Tokenization Example

When a merchant processes the credit card of a customer, the PAN is substituted with a token. 1234-4321-8765-5678 is replaced with, for example, 6f7%gf38hfUa.

The merchant can apply the token ID to retain records of the customer, for example, 6f7%gf38hfUa is connected to John Smith. The token is then transferred to the payment processor who de-tokenizes the ID and confirms the payment. 6f7%gf38hfUa becomes 1234-4321-8765-5678.

The payment processor is the only party who can read the token; it is meaningless to anyone else. Furthermore, the token is useful only with that single merchant.

Tokenization vs Encryption

The main difference between tokenization and encryption is that tokenization uses a ‘token’ whereas encryption uses a ‘secret key’ to safeguard the data.

Encryption

A core issue with data encryption is that it is reversible. Encrypted data is designed to be restored to its initial, unencrypted state. The safety of encryption is reliant on the algorithm used to protect the data. A more complex algorithm means safer encryption that is more challenging to decipher.

All encryption is, however, essentially breakable. The strength of your algorithm and the computational power available to the attacker will determine how easily an attacker can decipher the data. Encryption is thus better described as data obfuscation, rather than data protection. Encryption makes it more difficult to access the original information protected within the encrypted data, however not impossible.

The PCI Security Standards Council and similar compliance organizations treat encrypted data as sensitive data because it is reversible. Organizations are thus required to protect encrypted data.

Tokenization

Unlike encryption, tokenization of data cannot be reversed. Rather than using a breakable algorithm, a tokenization system substitutes sensitive data by mapping random data, thus the token cannot be decrypted. The token is a placeholder, with no essential value.

The true data is kept in a separate location, such as a secured offsite platform. The original data does not enter your IT environment. If an attacker penetrates your environment and accesses your tokens, they have gained nothing. Thus, tokens cannot be used for criminal undertakings.

The PCI and other security standards do not require organizations to safeguard tokenized data.

Benefits of Tokenization

Tokenization can provide several important benefits for securing sensitive customer data:

Enhanced customer assurance—tokenization offers an additional layer of security for eCommerce websites, increasing consumer trust.

Increased security and protection from breaches—by using tokenization, businesses do not have to capture sensitive information in their input terminals, keep it in internal databases, or transmit the data through their information systems. This safeguards businesses from security breaches.

Data tokenization improves patient security—organizations can use tokenization solutions for scenarios covered under HIPAA. By substituting electronically protected health information (ePHI) and non-public personal information (NPPI) with a tokenized value, healthcare organizations can better comply with HIPAA regulations.

Tokenization makes credit card payments more secure—the payment card industry needs to comply with extensive standards and regulations. Tokenization solutions provide a way to protect cardholder data, such as magnetic swipe data, primary account number, and cardholder information. Companies can comply with industry standards more easily, and better protect client information.

PCI Tokenization: Easing Compliance with Tokenization

The Payment Card Industry Data Security Standard (PCI DSS) ensures PAN data is protected by all organizations that accept, transmit, or store cardholder data. Failure to comply may result in fines and loss of brand authority.

Tokenization helps companies achieve PCI DSS compliance by reducing the amount of PAN data stored in-house. Instead of storing sensitive cardholder data, the organization only handles tokens, making for a smaller data footprint. Less sensitive data translates into fewer compliance requirements to comply with, which may lead to faster audits.

See how Imperva Data Masking can help you with data protection.

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How Imperva Leverages Tokenization for Security and Compliance

Imperva’s security solution uses data masking and encryption to obfuscates core data, so it would be worthless to a threat actor, even if somehow obtained.

We offer a holistic security solution that protects your data wherever it lives—on-premises, in the cloud, and in hybrid environments. We help security and IT teams by providing visibility into how data is accessed, used, and moved across the organization.

Our security approach relies on multiple layers of protection, including:

Database firewall—prevents SQL injection and similar threats, while assessing for known vulnerabilities.

User rights management—tracks the data movements and access of privileged users to identify excessive and unused privileges.

Data loss prevention (DLP)—monitors and tracks data in motion, at rest, in cloud storage, or on endpoint devices.

User behavior analytics—creates a baseline of data access behavior and uses machine learning to isolate and alert on abnormal and potentially dangerous activity.

Data discovery and classification—discloses the volume, location, and context of data on-premises and in the cloud.

Database activity monitoring—monitors relational databases, data warehouses, big data, and mainframes to produce real-time alerts on violations of policy.

Alert prioritization—Imperva uses AI and machine learning technology to examine the stream of security events and prioritize the most important events.

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How Does Tokenization Work? Explained with Examples - Spiceworks

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Data Security

What is Tokenization? Definition, Working, and Applications

Tokenization hides and secures a dataset by replacing sensitive elements with random, non-sensitive ones.

Chiradeep BasuMallick

Technical Writer

March 28, 2023

Tokenization is the process of hiding the contents of a dataset by replacing sensitive or private elements with a series of non-sensitive, randomly generated elements (called a token).

Tokenization is gaining popularity for data security purposes in business intelligence, fintech, and ecommerce sectors, among others.

Throughout the process, the link between the token and real values cannot be reverse-engineered. This article explains the meaning of tokenization and its uses.

Table of Contents

What Is Tokenization?

How Does Tokenization Work?

Tokenization vs. Encryption

Uses of Tokenization

What Is Tokenization?

Tokenization is defined as the process of hiding the contents of a dataset by replacing sensitive or private elements with a series of non-sensitive, randomly generated elements (called a token) such that the link between the token values and real values cannot be reverse-engineered.

Tokenization has flourished from the beginning of early financial systems, wherein coin tokens replaced real coins or banknotes. Since they function as money substitutes, subway tokens or casino tokens are instances of this. This is an example of tangible tokenization, but the purpose is identical to digital tokenization: to serve as a proxy for a more valued object.

The usage of digital tokenization dates back to the 1970s. It was utilized in the data archives of the time to isolate sensitive information from other recorded data.

Recently, tokenization has found applications in the credit and debit card industry to protect critical cardholder data and comply with industry norms. In 2001, TrustCommerce was attributed to developing tokenization to safeguard payment card data.

Tokenization substitutes confidential material with unique identifiers that maintain all critical information without jeopardizing security. It aims to reduce the data a company must keep on hand.

Consequently, it has become a popular method for small and medium-sized enterprises to increase the safety of card information and e-commerce transactions. In addition, it reduces the expense and difficulty of complying with industry best practices and government regulations.

Interestingly, the technology is not limited to financial data. Theoretically, one could apply tokenization technologies to all types of sensitive data, such as financial transactions, health records, criminal histories, vehicle driver details, loan documents, stock trading, and voter registration. Tokenization may improve any system a surrogate employs as a substitute for confidential material.

Types of tokenization

Tokens and tokenization can be of various types:

Vaultless tokenization: Vaultless tokenization employs protected cryptographic hardware with specified algorithms based on conversion standards to facilitate the exchange of sensitive information into non-sensitive assets in a secure way. One may store these tokens without a database. We will discuss this further in the following section.

Vault tokenization: This is the type of tokenization used for conventional payment processing, which requires organizations to keep a confidential database. This secure repository is known as a vault, whose purpose is to hold sensitive and non-sensitive information.

Tokenization in NLP: The field of natural language processing (NLP) comprises tokenization as one of its most fundamental operations. In this sense, tokenization splits a text down into smaller units called tokens so that bots can comprehend natural language properly.

Blockchain-based tokenization: This strategy distributes the ownership of a particular asset into several tokens. Non-fungible tokens (NFTs) that function as “shares” may be used for tokenization on a blockchain. However, tokenization could also encompass fungible tokens with an asset-specific value.

Platform tokenization: The tokenization of a blockchain enables decentralized application development. Also known as platform tokenization, this is a process in which the blockchain network offers transactional security and support as its foundation.

NFT tokenization: Blockchain NFTs are among the most prominent tokenizations nowadays. Non-fungible tokens contain digital information representing specialized and high-value assets.

Governance tokenization: This form of tokenization is designed for blockchain-based voting systems. Governance tokenization enables a more efficient decision-making process using decentralized protocols since all stakeholders can vote, debate, and participate equitably on-chain.

Utility tokenization: Using a particular protocol, utility tokens provide access to different services. There isn’t any direct investment token production using utility tokens, and their platform activity is beneficial to the economic growth of the system.

Reversible vs. irreversible tokenization

The tokenization process might be irreversible or reversible. Detokenization allows reversible tokens to be transformed to their original value. In terms of privacy, this is known as pseudonymization. These tokens could also be classified as cryptographic or non-cryptographic.

In cryptographic encryption, the cleartext data element(s) aren’t retained; it only preserves only the encryption key. This type of tokenization uses the NIST-standard FF1-mode AES algorithm.

Originally, non-cryptographic tokenization meant that tokens were generated by randomly creating a value and keeping the cleartext and associated token in a database, as was the practice with the initial TrustCommerce service.

Modern non-cryptographic tokenization emphasizes “stateless” or “vaultless” systems, using randomly generated data, safely concatenated to construct tokens. Unlike database-backed tokenization, these systems may function independently of one another and expand almost indefinitely since they need no synchronization beyond replicating the original data.

It is not possible to transfer irreversible tokens back to their initial value. In terms of privacy, this is known as anonymization. Thanks to a one-way function, these tokens are generated, enabling the usage of anonymized data bits or fragments for third-party analysis, operational data in reduced settings, etc.

See More: Data Privacy Day: Top Four Common Privacy Myths Debunked

How Does Tokenization Work?

Tokenization replaces sensitive information with non-sensitive equivalents. The replacement information is referred to as a token. This may utilize any of these processes:

With a key, a theoretically reversible cryptographic function.

A function that cannot be reversed, like a hash function.

An index function or a number produced at random.

Consequently, the token will become the exposed information, while the sensitive data that the token represents is securely held on a centralized server called the token vault. Only in the token vault can the original information be mapped back to its appropriate token.

In payment processing, tokenization requires replacing a credit or debit card or one’s account details with a token. Tokens, in themselves, have no use — and aren’t associated with any account or person.

The customer’s 16-digit main account number (PAN) is replaced with a randomly-generated, bespoke alphanumeric ID. This process eliminates any link between the transactions and the confidential material, reducing the risk of security breaches and making it ideal for credit card transactions. Tokenization of data preserves credit card and bank account details in a virtualized vault, allowing enterprises to transmit data securely via computer networks.

Some tokenization, however, is vaultless, as we mentioned before. Instead of keeping confidential data in a safe vault, vaultless tokens use an algorithm to store the information. The original sensitive data is not typically stored in a vault if the token is changeable or reversible. This method is rarely used due to its weaker security levels.

Understanding the working of tokenization with an example

When a retailer or merchant processes a customer’s credit card, the PAN is replaced with a token. 1111-2222-3333-4444 is substituted by alternatives such as Gb&t23d%kl0U.

The merchant may use the token ID to maintain client records; for example, Gb&t23:%kl0U is associated with Jane Doe. The token subsequently goes to the payment processor, who de-tokenizes the ID and verifies the payment. The notation for Gb&t23d%kl0U is 1111-2222-3333-4444.

The token is solely readable by the payment processor; it has no value to anybody else. Additionally, the token may only be used with that specific merchant.

In this case, the tokenization procedure will happen as follows:

Jane Doe enters her payment information at the point-of-sale (POS) terminal or digital checkout page.

The details, or data such as PAN, are replaced by a completely random token (or Gb&t23d%kl0U), which is often produced by the merchant’s payment gateway.

The tokenized data is subsequently transferred to a payment processor securely. The actual confidential payment information is kept in a token vault within the merchant’s payment gateway. This is the sole location to map a token and its value.

Before sending the information for final verification, the payment processor re-encrypts the tokenized data.

See More: What Is Cloud Encryption? Definition, Importance, Methods, and Best Practices

Tokenization vs. Encryption

Digital tokenization and encryption are two distinct data-security-related cryptographic techniques. The primary distinction between tokenization and encryption is that the former does not alter the extent or category of the protected data, while encryption modifies the length and type.

This makes encryption illegible without the key, even if the encrypted message is exposed. Tokenization does not employ a key in this manner; it cannot be mathematically reversed using a decryption key. Tokenization utilizes data that cannot be decrypted to symbolize or represent sensitive data. Encryption may be decrypted with a key.

Encryption has been the preferred data protection technique for decades, but tokenization has recently emerged as the most cost-effective and secure solution. However, encryption and tokenization can be used in tandem.

Before we explore how tokenization is used, here is an overview of the critical differences between tokenization and encryption:

1. The process of data masking

Through an encryption algorithm and a key, encryption mathematically converts plaintext into ciphertext. In contrast, tokenization creates token values randomly for plain text and maintains the mappings in a data repository. This database can also be a blockchain.

2. Ability to scale

Using a small encryption key to decode data, this technique can be used for massive data volumes. However, it is difficult to scale tokenization and safely maintain data quality and accuracy — as the database grows. For this reason, it is primarily used by large organizations and governments.

3. Type of data secured

Encryption is employed for unstructured and structured data, including entire files. Tokenization’s primary objective is safeguarding structured data fields, such as credit card information and Social Security numbers. That is why one can also use tokenized data for data analytics.

4. Third-party access

Encryption is excellent for communicating confidential information with other parties that possess the encryption key. It isn’t as secure, but more appropriate for transferring data. In contrast, tokenization makes information interchange harder since it requires full access to a token repository that maps token values.

5. Data format preservation

The vulnerability of format-preserving encryption systems is a tradeoff. With tokenization, however, the form may be preserved without compromising the level of security. This makes it a more no-compromise method of data security.

6. Location of data

When information is encrypted, the unencrypted source document will leave the organization. Tokenization is distinct because the original data is never transferred beyond the organization. This assists in satisfying specific regulatory criteria — particularly in industries like healthcare, financial services, etc.

7. Prerequisites

Tokenization works only via web services, and network connectivity is an essential prerequisite when tokenizing data. In contrast, encryption can be applied both locally (i.e., through a locally installed encryption tool) or as an online service. An internet connection is not a prerequisite for encryption.

See More: What Is Encryption? Definition, Working, and Types

Uses of Tokenization

Tokenization of data is helpful in the following scenarios:

Advantages of Using Zip Files

1. Protecting against data breaches

Criminals target organizations that accept debit and credit cards because payment information contains many insights about the card user. Hackers target vulnerable systems containing this information, then sell or use the stolen data to make fraudulent transactions.

Tokenization protects enterprises from the detrimental financial impact of data theft. Even in a data breach, crucial personal information will not be available for theft. Tokenization cannot safeguard your organization from a data breach but may mitigate the financial repercussions.

2. Complying with data protection laws

Given that tokens substitute data irreversibly, data tokenization software helps businesses to minimize the amount of data subject to compliance obligations. For instance, substituting Primary Account Number (PAN) data maintained inside an organization’s IT infrastructure with tokenized data reduces the data footprint, making Payment Card Industry Data Security Standard (PCI DSS) compliance more straightforward.

3. Strengthening e-commerce security

Even before the global pandemic, e-commerce payments steadily increased. Now, we are seeing a significant shift toward online shopping accompanied by an exponential increase in sales. While transitioning to a virtual environment is inevitable, this phenomenon has introduced new security concerns.

Tokenization is being rapidly used to combat e-commerce fraud and convert account numbers into digital products to limit their theft and misuse. The tokenization of credit or debit cards and account information increases data security and protects it from external and internal threats. Since the token does not represent the customer’s actual information, it cannot be utilized outside of a single transaction with a given merchant.

4. Enabling secure but convenient identification

Banks, hospitals, and government entities often seek the final four digits of a social security number to verify an individual’s identification. The token may show these values while covering the other figures with an “X” or an asterisk.

5. Building customer trust

Customers appreciate a deep commitment to safeguarding client information. In addition to preventing the worst-case eventuality of a data leak, sophisticated security measures such as tokenization build client confidence. Customers do not want their financial information to fall into the hands of criminals or other threat actors. They are reassured by tokenization, as it is a demonstrated and easy-to-understand security measure that customers can also appreciate (unlike backend measures).

See More: Top 10 Customer Identity Management Solutions in 2021

6. Add another layer to role-based access controls

Tokenization enables you to strengthen role-based access restrictions to sensitive information by preventing detokenization by users without the required credentials. Tokenization helps ensure that only authorized data users may detokenize confidential material when kept in a centralized database, like a data warehouse or data lake.

7. Driving fintech development

Tokenization’s underlying technology is integral to many of our current purchasing and selling practices, which depend heavily on fintech innovations such as digital payments.

Tokenization may facilitate the increased popularity of in-store mobile payments using your customers’ mobile devices. When consumers pay using a mobile wallet like Apple Pay or Google Pay, a tokenized version of their credit card information is saved on their phones. Tokenization is vital to accepting fintech since it makes payments safer and improves user experiences, whether digital, on smartphones, or in-app.

8. Reducing the compliance and security burden of data lakes and warehouses

Centralized data repositories, such as data lakes or data warehouses, hold structured and unstructured information from various sources. This makes it more difficult to establish data protection controls from a compliance perspective. Tokenization lets you store original personally identifiable information (PII) away from data lakes or warehouses when feeding sensitive information into the repository. This reduces compliance and security implications, even before data has reached storage systems.

9. Supporting disparate technologies

Compared to previous systems in which credit card details were stored in databases and widely shared across networks, tokenization makes it harder for hackers to obtain cardholder data. However, it is interoperable with many historical and modern technologies. Encryption is not as compatible with outdated systems as tokenization. Additionally, it supports emerging technologies such as mobile wallets, one-click payments, and cryptocurrencies.

10. Masking data used for business intelligence

Business intelligence and other categories of analytical tasks are vital to just about any business unit, and analyzing sensitive data is often essential. By tokenizing this material, businesses may safeguard sensitive information while enabling other apps and processes to perform analytics. For instance, it is beneficial in healthcare analytics (like demographic studies) when individual patients must remain anonymous. For this reason, business intelligence analysts must be familiar with tokenization.

11. Mitigating vendor-related risk

Today, many organizations collaborate with third-party software, suppliers, and service providers requiring access to sensitive data. Tokenization decreases the likelihood of a data breach triggered by external entities by removing sensitive information from their environment. Data tokenization ultimately contributes to a more robust cybersecurity posture by shielding sensitive data from hostile intruders and other intermediaries. It also prohibits unintentional exposure within the organization.

See More: What Is Data Governance? Definition, Importance, and Best Practices

Takeaway

Tokenization is fast becoming a staple in digital payments and data transfers. A 2023 study by Meticulous Research found that the tokenization market will be worth over $13 billion by 2030. This is due to widespread adoption by leading industry players, including Bluefin and Visa. This technology allows organizations to transfer and process user data securely, with implications for business intelligence, fintech, research, and other fields.

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What is Tokenization? A Complete Guide - Blockchain Council

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