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All Journal Journal of Economic, Bussines and Accounting (COSTING) Journal of Artificial Intelligence and Digital Business
Panggabean, Bungaran
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Digital Transformation in HR and Employee Capability as Determinants of Financial Innovation: Evidence from Bank Central Asia Wattilete, Litha Clara; Rakhmat, Rakhmat; Panggabean, Bungaran; Halik, Maria Yessica
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.1437

Abstract

This study examines the influence of digital transformation in human resources (HR) and employee capability on financial innovation at Bank Central Asia (BCA). Employing a quantitative approach, data were collected through a structured survey of 120 employees across key divisions. Multiple regression analysis revealed that employee capability has a significant positive effect on financial innovation, underscoring the importance of digital literacy, adaptability, and problem-solving skills in fostering new financial products and services. Conversely, digital transformation in HR was found to have no direct significant impact on financial innovation when assessed individually. However, together, both factors significantly influence financial innovation, highlighting the synergistic relationship between advanced digital HR systems and competent employees. These findings emphasize the necessity of integrating HR digitalization with robust capability-building initiatives to fully leverage technological investments. The study contributes to the literature by providing empirical evidence from Indonesia’s banking sector and offers practical insights for organizations aiming to strengthen innovation through a balanced focus on technology and human capital.
ADOPTION OF AI IN RECRUITMENT: IMPLICATIONS FOR BIAS, EFFICIENCY, AND CANDIDATE EXPERIENCE Panggabean, Bungaran; Raldianingrat, Welis; Baharudin, Baharudin; Natsir K, Irham
Journal of Economic, Bussines and Accounting (COSTING) Vol. 8 No. 4 (2025): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/m386pt53

Abstract

However, while the integration of AI into recruitment practices offers numerous potential benefits, it also raises critical concerns regarding fairness, transparency, and candidate experience. A central issue is the risk of algorithmic bias. The purpose of this study is to analyze the adoption of Artificial Intelligence (AI) in the recruitment process: its implications for bias, efficiency, and candidate experience. This study employs a literature review methodology to systematically analyze and synthesize existing research on the adoption of Artificial Intelligence (AI) in recruitment, with a particular focus on three interrelated aspects: bias, efficiency, and candidate experience. This literature review explored the multifaceted implications of Artificial Intelligence (AI) adoption in recruitment, focusing on three key dimensions: bias, efficiency, and candidate experience. The findings reveal that while AI technologies offer substantial benefits in terms of operational speed and cost reduction, they also introduce significant ethical, social, and psychological challenges.
Co-Authors Baharudin Baharudin Maria Yessica Halik Natsir K, Irham Rakhmat, Rakhmat Wattilete, Litha Clara Welis Raldianingrat, Welis