Protection of Data Privacy in The Era of Artificial Intelligence in The Financial Sector in Indonesia

Dewi, Sinta; Hidayat, Mohammad Wildan

doi:10.21098/jcli.v1i2.18

Cited by 3 publications

(4 citation statements)

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“…One of the principles of responsible AI is privacy [331]. It is the ability to prevent people from obtaining information about others without their permission [332]. In recent years, the importance of data protection has received a great deal of attention.…”

Section: Explainability It Determines How Ai Professionalsmentioning

confidence: 99%

Towards Risk-Free Trustworthy Artificial Intelligence: Significance and Requirements

Alzubaidi,

Al-Sabaawi,

Bai

et al. 2023

International Journal of Intelligent Systems

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Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic decision-making (DM), these systems have found wide-ranging applications across diverse fields, including education, business, healthcare industries, government, and justice sectors. While AI and DM offer significant benefits, they also carry the risk of unfavourable outcomes for users and society. As a result, ensuring the safety, reliability, and trustworthiness of these systems becomes crucial. This article aims to provide a comprehensive review of the synergy between AI and DM, focussing on the importance of trustworthiness. The review addresses the following four key questions, guiding readers towards a deeper understanding of this topic: (i) why do we need trustworthy AI? (ii) what are the requirements for trustworthy AI? In line with this second question, the key requirements that establish the trustworthiness of these systems have been explained, including explainability, accountability, robustness, fairness, acceptance of AI, privacy, accuracy, reproducibility, and human agency, and oversight. (iii) how can we have trustworthy data? and (iv) what are the priorities in terms of trustworthy requirements for challenging applications? Regarding this last question, six different applications have been discussed, including trustworthy AI in education, environmental science, 5G-based IoT networks, robotics for architecture, engineering and construction, financial technology, and healthcare. The review emphasises the need to address trustworthiness in AI systems before their deployment in order to achieve the AI goal for good. An example is provided that demonstrates how trustworthy AI can be employed to eliminate bias in human resources management systems. The insights and recommendations presented in this paper will serve as a valuable guide for AI researchers seeking to achieve trustworthiness in their applications.

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Section: Explainability It Determines How Ai Professionalsmentioning

confidence: 99%

Towards Risk-Free Trustworthy Artificial Intelligence: Significance and Requirements

Alzubaidi,

Al-Sabaawi,

Bai

et al. 2023

International Journal of Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…CL Sabharwal [1] looked into the robot counsellors in banking, while S Subudhi [3] talked about the valuable open doors and difficulties of Artificial intelligence in banking. SD Rosadi, S Yuniarti, and R. Fauzi [6] looked into information security issues of utilizing Artificial intelligence in the monetary area in Indonesia. MH Huang, RT Rust [2] talked about the job of Artificial intelligence.…”

Section: Writing Overviewmentioning

confidence: 99%

“…A few examination papers have featured the significance of information protection and security in the reception of artificial intelligence in banking. For instance, [6] The utilization of artificial intelligence in the public arena has raised a few security concerns, including the issue of client profiling. Profiling alludes to a computerized course of gathering and handling individual information that empowers organizations to store and examine data all the more.…”

Section: • Information Protection and Securitymentioning

confidence: 99%

Exploring the Rationale and Reasons for the Efficacious Applied Usage of the Artificial Intelligence Tools and Algorithms with a Focus on Banking Industry

Narang

2022

IJRST

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The banking industry is quickly embracing Artificial intelligence-advances to develop effectiveness further, reducing expenses, and improve client experience. The paper uses contextual analyses and information from different examination papers to break down the utilization of Artificial intelligence in various regions of the financial business. The article states that artificial intelligence-empowered advancements can be applied in different parts of the financial industry, with a critical potential for further developing navigation, lessening the gamble of misrepresentation, and upgrading client experience. The concentrate likewise gives models of Artificial intelligence executions in different financial areas, like gamble appraisal, credit endorsement process, speculation/portfolio of the executives, and others. The utilization of Artificial intelligence in extortion identification, customized monetary warning administrations, and computerized client support is talked about exhaustively, including models from major monetary foundations. Moreover, the paper examines how artificial intelligence can be utilized in claims the executives, abundance of the board, and credit to the executives. A few examination studies have been investigated that propose Artificial intelligencebased credit scoring models and advanced endorsing frameworks to upgrade the accuracy and proficiency of credit the board processes. Generally, this paper gives an exhaustive review of the fantastic open doors and difficulties related to using artificial intelligence in the financial business, featuring the potential to change how banks work and serve their clients.

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“…The ability of major technology industry to collect and analyse information has triggered complaints by consumers ranging from lack of digital trust to cyber-enabled criminal activities. 13 The journey to shape data protection law in Indonesia has been challenging. Prior to 2022, the legal development was only sectoral and not unified into omnibus or comprehensive legislation.…”

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confidence: 99%

Data Subject Access Request: What Indonesia Can Learn and Operationalise in 2024?

Algamar,

Ismail

2023

j. cent. bank. law and inst.

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The enactment of the Indonesian Personal Data Protection (PDP) Law is in line with the nation’s position as the most promising digital economy in Southeast Asia. The PDP Law, amongst others, introduces Data Subject Access Request (DSAR), a cornerstone mechanism to exercise data subject rights mirroring the European Union General Data Protection Regulation (GDPR). However, major causes of DSAR failure are predominantly triggered by resource constraint, lack of fundamental understanding, and technical gap when responding to such requests. In practice, DSAR management is time consuming and taxing since organisations shall manage numerous and complex requests within a tight timeline. By way of comparative analysis, we explore the concept of data subject rights, specifically the Rights to Access. Through observations and constructive responses by global data protection professionals, academics and non-lawyers, this paper alluded that similar failure scenario might occur in Indonesia when PDP Law grace period ended in 2024 – if the causes are not addressed and mitigated. Apropos, in safeguarding data subjects’ right, we assert that DSAR under the PDP law might bring disproportionate impracticality, hence there is demand for a robust consultation and holistic regulatory implementation. We also propose to consider a harmonized DSAR ASEAN framework for future proofing cross-border payment, in 2024 and beyond.

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Protection of Data Privacy in The Era of Artificial Intelligence in The Financial Sector in Indonesia

Cited by 3 publications

References 0 publications

Towards Risk-Free Trustworthy Artificial Intelligence: Significance and Requirements

Towards Risk-Free Trustworthy Artificial Intelligence: Significance and Requirements

Exploring the Rationale and Reasons for the Efficacious Applied Usage of the Artificial Intelligence Tools and Algorithms with a Focus on Banking Industry

Data Subject Access Request: What Indonesia Can Learn and Operationalise in 2024?

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