Risk Management 4.0: The Role of Big Data Analytics in the Bank Sector

Abstract

The need to query large volumes of heterogeneous data in differing formats from multiple sources, both internal and external and its centrality to the process of value creation is revolutionising traditional approaches to business models. Through the adoption of more sophisticated algorithms, it is possible to intercept and interpret any digital flow, particularly those coming from the Internet of Things or from the web. The vast amount of information, its governance and its global integration are used in all decision-making processes and they are, therefore, an element of strategic importance in the development process and in the survival of every company, thanks to the potential for transforming all information sources into knowledge and quantifying reality in all its elements (objects, places, phenomena, people and human behaviour). Having a large volume and a wide variety of information (i.e., Big Data) shared within an organisation is crucial for the interactive and multidirectional process of risk assessment and management. This process, on the one hand, contributes to safeguarding the integrity of corporate assets through increased efficiency and the effectiveness of the services provided and, on the other, reduces unexpected events and related losses while ensuring greater efficiency in the decision-making process. This is relevant especially in financial institutions in which risk management is pivotal to their survival and their success, assuming a strategic role. Through an analysis of the literature and a case study methodology, this paper investigates how small banks are facing technological challenges, showing the state of art about the actual use of the techniques of data collection and management (e.g., Big Data analytics [BDA]) in supporting the risk management process. Furthermore, the work tries to identify the skills required of the risk manager in the digital age. The paper contributes to the ongoing debate on the usefulness and use of digital innovations in the banking sector, discussing the future perspectives of risk management 4.0 and the role of BDA in risk management.

Smart contracts to enable sustainable business models. A case study

“…Among the emerging new smart technologies allowing companies to show and create knowledge and increase their competitiveness (Dicuonzo et al , 2019; Lombardi, 2019; Lombardi et al , 2020), blockchain is one of the most interesting ones (Dicuonzo et al , 2020; Massaro et al , 2020). According to Lee and Low (2017, p. XVIII), “The most powerful feature of decentralized technology with blockchain is the fractional ownership of digital assets that would lead to a more equitable and just society”.…”

دور تحليلات البيانات الضخمة في إدارة المخاطر في البنوك السعودية: دراسة استقصائية

“…Likewise [9] , aims to investigate how small banks are facing technological challenges, showing the state of art about the actual use of the techniques of big data analytics in supporting the risk management process. This study tries to identify the skills required of the risk management in the digital age for using the big data analytics.…”

Application of Artificial Intelligence-Based Risk Management in Banking

“…Di sisi lain, model dalam AI sendiri dapat dimanfaatkan pada manajemen risiko yang ada dalam industri perbankan (Bussmann et al, 2021). Hal ini dikarenakan, manajemen atas perusahaan memerlukan hal tersebut guna menerapan kebijakan dan program manajemen risiko yang memadai untuk menetapkan prinsip-prinsip penting dalam aspek tanggung jawab sosial serta menjaga kelangsungan bisnis (Dicuonzo et al, 2019). Manajemen risiko pada industri perbankan sendiri hadir karena adanya globalisasi, persaingan yang ketat, serta kondisi ekonomi dan politik yang tidak menentu (Sleimi, 2020).…”

“…Adapun risiko-risiko yang dihadapi oleh perbankan ialah risiko suku bunga, risiko pasar, risiko kredit, risiko off-balance-sheet, risiko teknologi dan operasional, risiko nilai tukar mata uang asing, risiko negara, risiko likuiditas, risiko likuiditas, dan risiko insolvensi (Leo et al, 2019). Berdasarkan penelitian (Dicuonzo et al, 2019), dinyatakan bahwa risiko-risiko di atas dapat diminimalisir dengan manajemen risiko 4.0 yang menggunakan big data, namun hal tersebut membutuhkan pengembangan pengetahuan dan keterampilan baru untuk mengkonversi data menjadi sumber daya strategis. Khalid & Amjad (2012) mengusulkan lima langkah untuk praktik manajemen risiko, yaitu pemahaman risiko dan manajemen risiko, identifikasi risiko, analisis dan penilaian risiko, pemantauan risiko, dan analisis risiko kredit.…”

“…Oleh karena itu, penerapan AI dalam dunia perbankan tidak dapat dianggap sebagai hal yang ringan, karena memiliki dampak yang dapat memberi beragam pengaruh positif (Kaya, 2019). Hal tersebut juga dapat dilihat bahwa AI menjadi elemen pada kepentingan strategis dalam proses pengembangan dan kelangsungan hidup industri terkait, seperti melalui penggunaan inovasi digital di sektor perbankan (Dicuonzo et al, 2019). Oleh karena itu, H1 dalam penelitian ini dapat diterima yang berarti bahwa artificial intelligence berpengaruh positif pada sektor perbankan.…”