## 3 Fundamental Technologies for RegTech
### Tools  
RegTech solutions, which have the above features, are typically composed of independently developed software and hardware tools. RegTech focuses on leveraging technology to improve compliance processes, reduce costs, and enhance the overall effectiveness of regulatory compliance by utilizing a range of technologies to automate, streamline, and enhance compliance processes. It may be noted that the technologies used in RegTech are extremely _mature_ and have been in use for decades. This helps the developers integrate such software and hardware to meet the requirements. Some of the key technologies used in RegTech include:  
* _AI and Machine Learning_: AI is an advanced technology that can perform tasks in areas that require human intelligence with the implementation and development of computer systems, including a broad range of techniques, algorithms, and methodologies that enable computers to mimic or simulate human intelligence. It involves creating intelligent machines that can perceive, reason, learn, and problem-solve in ways similar to or surpassing human capabilities [35]. For example, the AI-based scoring system is more objective in making credit decisions more precise and reasonable without bias and with brilliant fraud detection, no matter how sophisticated or complex the regulations are [36]. In addition, AI plays an incredible role in complying with the General Data Protection Regulation (GDPR) [37; 38], the European Data Protection Law that aims to protect personal information. For instance, _Aigine_ offers a tool based on AI to detect personal data from various sources, including structured or unstructured files such as emails or notes, to handle the challenge of unstructured personal data through four stages: filtering, highlighting, assessing, and documenting [16]. Machine learning is a subset of AI that focuses on algorithms and models that enable computers to learn from and make predictions or decisions based on data. It involves training computer systems to automatically improve performance on a specific task through experience and without explicit programming.
* _Blockchain_: Blockchain technology can improve transparency and traceability in compliance processes. For example, it can be used to create tamper-proof records of transactions and improve the audit trail [39; 40; 41]. Blockchain technology has several potential applications in RegTech, primarily due to its ability to provide an immutable and transparent record of transactions.
* _Natural Language Processing_: NLP can analyze unstructured data, such as text documents, to identify and flag potential compliance issues [42].
* _Big Data Analytics_: RegTech relies on analyzing large amounts of data to identify patterns, trends, and anomalies that may indicate compliance risks [2; 43].
* _Cloud Computing_: Cloud computing can be used to store and process large amounts of data in a cost-effective and scalable way [44; 45; 46].
* _Robotic Process Automation_ (RPA): RPA can be used to automate routine compliance tasks, such as data entry and reconciliation, to improve efficiency and reduce errors [47; 48; 49].  
* _Internet of Things_: IoT devices can be used to collect data from physical assets and locations, such as factories or supply-chain nodes [50; 51; 52], to monitor compliance and identify potential risks. Adopting these technologies can automate compliance processes, such as monitoring and reporting, by analyzing large volumes of data in real-time [46; 47]. They are constantly evolving as new solutions are developed to meet the specific needs of different industries and regulatory requirements.