Developing Reinforcement Learning Algorithms for RegTech Based on Artificial Neural Network

  • Hong, Seung Hun (Principal Investigator/Chief Investigator A)
  • Alazab, Mamoun (Co Investigator/Chief Investigator B)
  • HWANG , Ha (Principal Investigator/Chief Investigator A)
  • CHAE , Jonghun (Chief Investigator D)
  • CHOI, Hojin (Chief Investigator E)
  • PARK, Jungwon (Chief Investigator F)

    Project: Research

    Project Details


    This study aims to develop an artificial neural network-based reinforcement learning algorithm that interprets regulations written in legal terms and implements smart administrative services based on new technologies. Digital systems can help ordinary citizens and businesses understand and comply with regulations, but regulations are not written in language that digital systems can understand. Therefore, developing artificial neural network algorithms that convert regulations written in legal terms into language that digital systems can understand is key to providing artificial intelligence-based administrative services. This study will develop an artificial intelligence-based smart regulatory verification app that will make it easier to understand and interpret complex regulations and upgrade them through reinforcement learning. This leads to the transition of the regulatory paradigm from regulating technologies to regulation by technology and implements smart administrative services using RegTech.
    Effective start/end date1/07/2130/06/24


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