scholarly journals The Potential Use of FinTech Developments in Takaful

2021 ◽  
Vol 8 (2) ◽  
pp. 109-121
Author(s):  
Hafidh Abdulla Hemed ◽  
Arwa Abubaker Abdullah Alamoudi ◽  
Anas Abdulkadir Abubakar Al Qassim ◽  
Bandar Mohammed Saif Qasem
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Insurance Industry ◽  
Academic Research ◽  
Big Data Analytics ◽  
Customer Experience ◽  
Business Environment ◽  
Competitive Intelligence ◽  
Islamic Insurance ◽  
Potential Use

Despite the increasingly important role that fintech play in the takaful industry, academic research in this area is quite limited. The overall aim of this paper it thus to explore the potential use of fintech in the Islamic insurance industry, especially in terms of its opportunities and challenges. Specifically, big data analytics and robo-advisory were explored and how takaful operators might incorporate them for better customer experience and gathering competitive intelligence. To remain competitive in a fast changing business environment, takaful operators need to identify and adopt fintech that could influence positively customer experience and optimise cost efficiency. This paper reviews the literature on big data analytics and robo-advisory, aiming to shed the light on the barriers and benefits of harnessing these technological advancements for takaful operators.

scholarly journals Big Data and Algorithms in the Public Sector and Their Impact on the Transparency of Decision-Making

2018 ◽  
Vol 331 ◽  
pp. 301-311
Author(s):  
Gergely László Szὄke
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Public Sector ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Legal Framework ◽  
New Wave ◽  
Short Introduction ◽  
The Public ◽  
Potential Use

Big Data is clearly one of the most used buzzwords nowadays, but it really seems that the phenomenon of Big Data will have a huge effect on many different fields, and may be regarded as the new wave of the information revolution started in the 60s of the last century. The potential of exploiting Big Data promises significant benefits (and also new challenges) both in the private and the public sector – this essay will focus on this latter. After a short introduction about Big Data, this paper will first sum up the potential use of Big Data analytics in the public sector. Then I will focus on a specific issue within this scope, namely, how the use of Big Data and algorithm-based decision-making may affect transparency and access to these data. I will focus on the question why the transparency of the algorithms is raised at all, and what the current legal framework for the potential accessibility to them is.

scholarly journals A standards-based ontology and support for Big Data Analytics in the insurance industry

ICT Express ◽  
2017 ◽  
Vol 3 (2) ◽  
pp. 57-61
Author(s):  
Dimitrios A. Koutsomitropoulos ◽  
Aikaterini K. Kalou
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Insurance Industry ◽  
Big Data Analytics

Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management

2017 ◽  
Vol 37 (1) ◽  
pp. 10-36 ◽  
Author(s):  
Florian Kache ◽  
Stefan Seuring
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Empirical Research ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Business Environment ◽  
Special Focus ◽  
Chain Management ◽  
Content Type

Purpose Despite the variety of supply chain management (SCM) research, little attention has been given to the use of Big Data Analytics for increased information exploitation in a supply chain. The purpose of this paper is to contribute to theory development in SCM by investigating the potential impacts of Big Data Analytics on information usage in a corporate and supply chain context. As it is imperative for companies in the supply chain to have access to up-to-date, accurate, and meaningful information, the exploratory research will provide insights into the opportunities and challenges emerging from the adoption of Big Data Analytics in SCM. Design/methodology/approach Although Big Data Analytics is gaining increasing attention in management, empirical research on the topic is still scarce. Due to the limited availability of comparable material at the intersection of Big Data Analytics and SCM, the authors apply the Delphi research technique. Findings Portraying the emerging transition trend from a digital business environment, the presented Delphi study findings contribute to extant knowledge by identifying 43 opportunities and challenges linked to the emergence of Big Data Analytics from a corporate and supply chain perspective. Research limitations/implications These constructs equip the research community with a first collection of aspects, which could provide the basis to tailor further research at the nexus of Big Data Analytics and SCM. Originality/value The research adds to the existing knowledge base as no empirical research has been presented so far specifically assessing opportunities and challenges on corporate and supply chain level with a special focus on the implications imposed through Big Data Analytics.

scholarly journals The Role of Big Data in Enhancing Customer Experience in UAE Retail

2018 ◽  
Vol 9 (6) ◽  
pp. 76
Author(s):  
Shital Vakhariya ◽  
Kirti Khanzode
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Success Factors ◽  
Big Data Analytics ◽  
Customer Experience ◽  
Structured Interview ◽  
Critical Success ◽  
Retail Business ◽  
Relevant Factors

Purpose: The objective of this research was to identify critical success factors for the adoption of Big Data in UAE retail. The use of Big Data, in this case, focused on improving its system of recommendations for a better understanding of consumer behavior and its impact on consumer experience.Design/Methodology/Approach: The research was done through interviews & observation of shopping patterns. A semi - structured interview script was used for the interviews.Findings: Based on the results, we outline some propositions related to the opportunities and obstacles for the implementation of Big Data in UAE retail.Originality/Value: The main contribution of the research was the identification of relevant factors to the adoption of Big Data that were not considered as critical for the adoption of previous technologies.Research Rationale: Few years ago, retailers had no idea who was buying what and from where they are buying and where not so bother about customer experience. Now Big Data helps retailers understand individuals' needs, allowing them to create segments to target. Big Data will help in understanding the buying trend. Not may study are conducted in UAE retail. This study will help to understand the adoption and role of Big data in UAE retail customer experience.This paper show how can big data analytics help to improve the retail business and can be applied in the sector and help in decision making.

scholarly journals Elucidation of big data analytics in banking: a four-stage Delphi study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Soltani Delgosha ◽  
Nastaran Hajiheydari ◽  
Sayed Mahmood Fahimi
Keyword(s):  
Big Data ◽  
Delphi Study ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Business Environment ◽  
Decision Makers ◽  
Service Development ◽  
Content Type ◽  
Product Service ◽  
Credit Risk Analysis

PurposeIn today's networked business environment, a huge amount of data is being generated and processed in different industries, which banking is amongst the most important ones. The aim of this study is to understand and prioritize strategic applications, main drivers, and key challenges of implementing big data analytics in banks.Design/methodology/approachTo take advantage of experts' viewpoints, the authors designed and implemented a four-round Delphi study. Totally, 25 eligible experts have contributed to this survey in collecting and analyzing the data.FindingsThe results revealed that the most important applications of big data in banks are “fraud detection” and “credit risk analysis.” The main drivers to start big data endeavors are “decision-making enhancement” and “new product/service development,” and finally the focal challenge threatening the efforts and expected outputs is “information silos and unintegrated data.”Originality/valueIn addition to stepping forward in the literature, the findings advance our understanding of the main managerial issues of big data in a dynamic business environment, by proposing effective further actions for both scholars and decision-makers.

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