scholarly journals Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications

2021 ◽  
Vol 3 (3) ◽  
pp. 235-249
Author(s):  
Subarna Shakya ◽  
S Smys
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Data Analytics ◽  
Financial Institution ◽  
Big Data Analytics ◽  
Regulatory Compliance ◽  
Internet Banking ◽  
Digital Convergence ◽  
Data Volume ◽  
Asset Quality

While the phrase Big Data analytics is not only applicable for a certain realm of technology, diverse business segments like banking also benefit from the use of advanced mathematical and statistical models like predictive analysis, artificial intelligence, and data mining. If it is a query that is data volume generated in a bank or any financial institution is huge, it is absolutely a yes. As per the recent survey, it is observed that banks worldwide aren't just concentrating on improving the asset quality and fulfilling regulatory compliance but on the lookout for a digital convergence strategy to reach customers effectively in delivering services and products. As most of the data generated in internet banking and ATM transactions are unstructured accounting around for 2.5 quintillion bytes useful for fraud detection, risk management, and customer satisfaction, the use of trending Big Data Analytics methodology can be used to tackle the challenges and competition among banks. There are surplus advantages of Big Data strategy in the banking field and in this paper, we have made an analysis over Big Data Analytics on banking applications and their related concepts.

scholarly journals EXPRESS: “Get a £10 Free Bet Every Week!” – Gambling Advertising on Twitter: Volume, Content, Followers, Engagement and Regulatory Compliance

2021 ◽  
pp. 074391562199967
Author(s):  
Raffaello Rossi ◽  
Agnes Nairn ◽  
Josh Smith ◽  
Christopher Inskip
Keyword(s):  
Social Media ◽  
Big Data ◽  
Content Analysis ◽  
Volume Content ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Regulatory Compliance ◽  
The Internet ◽  
Policy Recommendations ◽  
Policy Makers

The internet raises substantial challenges for policy makers in regulating gambling harm. The proliferation of gambling advertising on Twitter is one such challenge. However, the sheer scale renders it extremely hard to investigate using conventional techniques. In this paper the authors present three UK Twitter gambling advertising studies using both Big Data analytics and manual content analysis to explore the volume and content of gambling adverts, the age and engagement of followers, and compliance with UK advertising regulations. They analyse 890k organic adverts from 417 accounts along with data on 620k followers and 457k engagements (replies and retweets). They find that around 41,000 UK children follow Twitter gambling accounts, and that two-thirds of gambling advertising Tweets fail to fully comply with regulations. Adverts for eSports gambling are markedly different from those for traditional gambling (e.g. on soccer, casinos and lotteries) and appear to have strong appeal for children, with 28% of engagements with eSports gambling ads from under 16s. The authors make six policy recommendations: spotlight eSports gambling advertising; create new social-media-specific regulations; revise regulation on content appealing to children; use technology to block under-18s from seeing gambling ads; require ad-labelling of organic gambling Tweets; and deploy better enforcement.

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamad Bahrami ◽  
Sajjad Shokouhyar
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Culture

PurposeBig data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.Design/methodology/approachThe study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.FindingsThe results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.Originality/valueThe present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

scholarly journals RISK MANAGEMENT 4.0: THE ROLE OF BIG DATA ANALYTICS IN THE BANK SECTOR

2019 ◽  
Vol 9 (6) ◽  
pp. 40-47 ◽  
Author(s):  
Grazia Dicuonzo ◽  
Graziana Galeone ◽  
Erika Zappimbulso ◽  
Vittorio Dell'Atti
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

scholarly journals Usefulness and Impact of Big Data in Libraries: An Opportunity to Implement Embedded Librarianship

2021 ◽  
Author(s):  
Subhajit Panda
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Information Overload ◽  
Big Data Analytics ◽  
Library Services ◽  
Data Practices ◽  
Data Life Cycle ◽  
Data Volume ◽  
Primary Focus

The concept of Big Data has been extensively considered as a technological modernisation in Library & Information centres. According to IDC, data volume is set to increase exponentially and envisages a data volume of over 160 zettabytes by the year 2025. Size is the first, and at times, the only dimension that leaps out at the mention of Big Data. Big Data is defined as information overload due to the volume, velocity, variety, variability & veracity of the data which must be processed to get value and better visualisation. Big Data contains the answer to several valuable questions related to patterns, trends & associations of user behaviour. It plays a major role in helping libraries to clearly understand the changing user needs, accordingly, reshape & restructure their services & procedures. The primary focus of this study was to explore the concept of Big Data in a library environment, steps to introduce Big Data in libraries and the use of Big Data in providing library services using the concept of data life cycle developed by DataONE. The main influential components to perform this study was the capabilities of Big Data analytics, the need & usefulness of Big Data practices, its significant utilisation in libraries and discuss some globally taken practical initiatives. The study highlights the important role of Big Data analytics capabilities to uncover new challenges of information utilisation, consequently helps a librarian to fulfil his role as an Embedded Librarian, both in theoretical & practical terms.

How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Surajit Bag ◽  
Pavitra Dhamija ◽  
Sunil Luthra ◽  
Donald Huisingh
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Supply Chains ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Hypothetical Model ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Capabilities

PurposeIn this paper, the authors emphasize that COVID-19 pandemic is a serious pandemic as it continues to cause deaths and long-term health effects, followed by the most prolonged crisis in the 21st century and has disrupted supply chains globally. This study questions “can technological inputs such as big data analytics help to restore strength and resilience to supply chains post COVID-19 pandemic?”; toward which authors identified risks associated with purchasing and supply chain management by using a hypothetical model to achieve supply chain resilience through big data analytics.Design/methodology/approachThe hypothetical model is tested by using the partial least squares structural equation modeling (PLS-SEM) technique on the primary data collected from the manufacturing industries.FindingsIt is found that big data analytics tools can be used to help to restore and to increase resilience to supply chains. Internal risk management capabilities were developed during the COVID-19 pandemic that increased the company's external risk management capabilities.Practical implicationsThe findings provide valuable insights in ways to achieve improved competitive advantage and to build internal and external capabilities and competencies for developing more resilient and viable supply chains.Originality/valueTo the best of authors' knowledge, the model is unique and this work advances literature on supply chain resilience.

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