Decoding Data Tokenisation: Its Vital Role and Relevance
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For 83% of companies, it’s not if a data breach will happen but when. As per an, data breaches cost a whopping $4.35M on average globally in 2022. These breaches take various forms, including phishing attacks, business email compromises, third-party software vulnerabilities, credential theft, and malicious insiders. The consequences of such incidents can be catastrophic.
Having said that, businesses have to transfer sensitive data like credit card numbers, health records, and customer information daily. But one pressing concern is how can they protect that data from falling into the wrong hands.
British mathematician said in 2006, “Data is the new oil.” Companies must ensure that their consumer data must remain safe with them. However, businesses are left exposed to the dangers of data breaches and compliance fines.
Enter data tokenisation – an innovative technology proving itself as a game-changer when it comes to enhancing data security levels. In this article, we'll dive deep into the concept of data tokenisation and explore its significance in various industries. Specifically, we'll look at how Scallop, an industry-trusted company, leverages this technology to safeguard its banking and card users' information.
Tokenisation replaces a sensitive data element, such as a credit card number or bank account number, with a non-sensitive substitute called a "token.". This token is essentially a randomised data string that has no intrinsic or exploitable value. It serves as a unique identifier, retaining all the essential information about the data without compromising its security.
Unlike encryption systems that use secret keys to decipher data, data tokenisation maintains a connection between the original data and the token but offers no way to reverse-engineer the token to reveal the original data.
In the context of payment processing, data tokenisation involves substituting sensitive information like credit card numbers with randomly generated tokens. For instance, a customer’s IBAN is replaced with a custom alphanumeric ID. Since there is no link between the token and the sensitive data, it wouldn't reveal meaningful information in case of a data breach or hacking.
A survey of data professionals found that 75% of organisations collect and store sensitive data, which they currently use or plan to use. Tokenisation protects that data by replacing it with tokens that act as surrogates for the actual information. For example, a customer's 16-digit credit card number might be replaced with a random string of numbers, letters, or symbols. This tokenisation process would make it impossible for a potential attacker to exploit the customer's credit card number, thus making any online payments more secure.
Data tokenisation has emerged as a highly effective approach for enhancing data security in modern times. It replaces confidential information with tokens, data tokenisation minimises the probability of data breaches, identity theft, fraud, and other cyber threats.
Additionally, tokens are linked with the original data through a secure mapping system that ensures the original data is protected even if the tokens get compromised.
Organisations that operate globally must follow strict data protection regulations. Tokenisation provides them with a reliable solution to secure sensitive information and reduces non-compliance chances. By tokenising data, it is considered non-sensitive, simplifying data management and streamlining the complexity of security audits.
Data tokenisation offers a secure platform for sharing data across departments, vendors, and partners while preventing any security breaches. Through tokenisation, sensitive information is hidden from third-party access, allowing organisations to control who can access their data.
Scallop, harnesses the power of data tokenisation to secure our banking and card users. By doing so, we comply with data privacy regulations while maintaining the trust of our customers. Their approach also allows them to extract valuable insights from user data without putting sensitive information at risk.