Institutional databases

An institutional database is a systematic and centralized collection of digital information, records, and resources particular to an organization that allows for effective data administration and retrieval.

Before the arrival of the internet and its revolutionary influence in the mid-1990s, governments, corporations, and banks were the entities that owned and regulated digital identity databases to access and analyze the accumulated data on companies, employers, citizens, and customers. Think of how the consumer credit history in the mid-1960s used to shift to electronic storage by credit reporting agencies.

Traditional identity management systems rely heavily on institutional databases. In addition to serving as centralized repositories of personal information, these databases support identity-related processes and services offered by government agencies, financial institutions, and healthcare providers. The purpose of this chapter is to explore the characteristics, advantages, and challenges of institutional databases, which are commonly used for traditional identity management.

Characteristics of institutional databases

Traditional identity management institutions use institutional databases that possess several key characteristics:

• Centralized storage: The databases store a vast amount of personal data, including names, addresses, social security numbers, and other identification details. Data relating to identity can be accessed and managed easily through this centralization.
• Scalability: Data storage and processing can be handled by institutional databases on a large scale. As identity-related transactions and individuals increase, databases can scale up to accommodate the increase.
• Security measures: To secure the confidentiality, integrity, and availability of the stored data, strong security measures are put in place. Access restrictions, encryption, firewalls, intrusion detection systems, and regular security audits are examples of such safeguards.
• Data integration: Data from many sources and departments within an organization is frequently combined in institutional databases. This integration provides a full view of an individual’s identity and makes identity verification processes more efficient.

Now, let’s look at the merits and demerits of institutional databases.

Advantages of institutional databases

In the sphere of traditional identity management, institutional databases offer various advantages:

• Streamlined processes: Organizations can use centralized databases to simplify identification-related activities such as identity verification, document authentication, and identity credential issuance. As a result, service delivery is faster and more efficient.
• Improved accuracy: Organizations can limit the likelihood of duplicate or incorrect entries by keeping a centralized store of identification data. This increases the accuracy and dependability of identity-related data.
• Enhanced fraud detection: Organizations can use institutional databases to create sophisticated fraud detection systems. Organizations can discover suspected fraudulent activity and take the necessary action by analyzing trends and anomalies in recorded data.
• Interoperability: Interoperability across various systems and organizations can be facilitated through institutional databases. For example, government organizations may securely communicate identity information with other authorized organizations, supporting seamless service delivery across many sectors.

Disadvantages of institutional databases

While institutional databases provide several benefits, they also create issues that must be addressed:

• Data privacy concerns: Concerns regarding data privacy and the possibility of unauthorized access or exploitation arise when sensitive personal information is stored in centralized systems. To prevent these risks, organizations must develop comprehensive data protection procedures and comply with appropriate privacy rules.
• Data breaches: Because of their centralized character, institutional databases are appealing targets for hackers. Identity theft, financial fraud, and other criminal behaviors can result from data breaches. Organizations must invest in comprehensive cybersecurity measures to successfully prevent and respond to possible intrusions.
• Data accuracy and quality: It might be difficult to ensure the accuracy and quality of data that’s kept in institutional databases. Incorrect or outdated information might cause problems during identity verification processes and impede service delivery. To solve these difficulties, regular data maintenance and quality control techniques are required.
• System integration: Integrating disparate systems and information inside and across organizations may be difficult. To allow smooth data sharing and interoperability, organizations must invest in comprehensive integration frameworks and standards.

Traditional identity management systems rely on institutional databases as a crucial infrastructure. They offer centralized storage, scalability, security measures, and data integration capabilities, all of which help to expedite identity-related procedures and improve service delivery. However, concerns relating to data privacy, breaches, accuracy, and system integration must be addressed to guarantee that these databases operate effectively and securely. As technology advances, new techniques to address some of these difficulties, such as decentralized identification systems and blockchain-based solutions, are being developed, providing alternatives to established institutional databases.

Up next, we will look at access control lists (ACLs).