Data Management 4.0 for Financial Service Authority (FSA): A Case Study in Indonesia

Legowo, Nilo; Wang, Gunawan; Hammam, Sabiq Adzhani; Wirianto,; Gunawan, Ali; Girsang, Harry

doi:10.1109/icimtech53080.2021.9535002

Cited by 1 publication

(1 citation statement)

References 6 publications

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“…Technology: RegTech solutions involve a wide set of technologies, such as big data, artificial intelligence, machine learning, deep learning, DLT, Blockchain and smart contracts, APIs (relevant in encouraging integration and interoperability between systems), biometrics, Internet of Things and cloud computing (Arner et al, 2017a;Battanta et al, 2020;Becker et al, 2020;Chao et al, 2022;Dashottar & Srivastava, 2021;Du & Wei, 2020;Goul, 2019;Legowo et al, 2021;Mogaji & Nguyen, 2021;Naheem, 2019;Omarova, 2020;Priem, 2022;Rahman et al, 2021;Singh & Lin, 2020;Singh et al, 2022;Yang et al, 2021), all enabled by suitable algorithms (Baxter, 2016).…”

Section: Dimension #1: Regulation and Technologymentioning

confidence: 99%

RegTech in public and private sectors: the nexus between data, technology and regulation

Grassi

Lanfranchi

2022

J. Ind. Bus. Econ.

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Higher regulatory compliance requirements, fast and continuous changes in regulations and high digital dynamics in the financial markets are powering RegTech (regulatory technology), defined as technology‐enabled innovation applied to the world of regulation, compliance, risk management, reporting and supervision. This work builds on a systematic literature review and a bibliometric analysis of the literature on RegTech, its influential papers and authors, its main areas of research, its past and its future. The resulting multi-dimensional framework bridges across four main dimensions, starting with regulation and technology, where one or more regulations, not necessarily financial ones, are addressed with the support of technologies (e.g. artificial intelligence, DLT, blockchain, smart contracts, API). Data play a central role, as sharing them enables data ecosystems, where additional value can be attained by each market participant, while data automation and machine-readable regulations empower regulators to pull data directly from the banks’ systems and combine these data with data obtained directly from customers or other external sources. Several applications emerge, both for regulated entities, covering matters of compliance, monitoring, risk management, reporting and operations, as well as for authorities, which can leverage on RegTech (SupTech) solutions to make policies, to undertake their authorising, supervising and enforcement operations, for monitoring and controlling purposes, and even to issue fines automatically. As a consequence, stakeholders can reap a series of benefits, such as higher efficiency and effectiveness, accuracy, transparency and lower compliance costs but also risks, such as cyber risk, algorithmic biases, and dehumanization.

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