Digitalisation and Big Data Mining in Banking

open access articleBanking as a data-intensive subject has been progressing continuously under the promoting influences of the era of big data. Exploring the advanced big data analytic tools like Data Mining (DM) techniques is key for the banking sector, which aims to reveal valuable information from the overwhelming volume of data and achieve better strategic management and customer satisfaction. In order to provide sound direction for the future research and development, a comprehensive and most up to date review of the current research status of DM in banking will be extremely beneficial. Since existing reviews only cover the applications until 2013, this paper aims to fill this research gap and presents the significant progressions and most recent DM implementations in banking post 2013. By collecting and analyzing the trends of research focus, data resources, technological aids, and data analytical tools, this paper contributes to bringing valuable insights with regard to the future developments of both DM and the banking sector along with a comprehensive one stop reference table. Moreover, we identify the key obstacles and present a summary for all interested parties that are facing the challenges of big data

ERM Quarterly, Quarter 3, October 2016

In this issue • Support instruments in focus: innovative business transfer measures • Case in focus: Major overhaul in Polish mining sector • Case in focus: Planned Caterpillar closure at Gosselie

A Review on the Role of Big Data Analytics in the Financial Services Industry

The financial services industry's digital revolution has facilitated the penetration and transformation of advanced analytics, machine learning, artificial intelligence, big data, and the cloud. These technologies are used by large organisations to expedite digital transformation, meet consumer demand, and improve profit and loss. While the majority of organisations hold enormous amounts of useful data, they typically lack the knowledge essential to maximise its value because the data is unstructured or incorrectly recorded inside the organisation. This article discusses the applications of Big Data Analytics in the financial services industry and how they are being employed. Text analytics, audio analytics, and predictive analytics are just a few of the approaches now being used to provide value to financial organisations. This can assist in resolving various critical issues in the field, including market forecasting, fraud detection, credit scoring, real-time targeted marketing, and overall customer experience enhancement

RegTech in public and private sectors: the nexus between data, technology and regulation

Higher regulatory compliance requirements, fast and continuous changes in regulations and high digital dynamics in the financial markets are powering RegTech (regulatory technology), defined as technology-enabled innovation applied to the world of regulation, compliance, risk management, reporting and supervision. This work builds on a systematic literature review and a bibliometric analysis of the literature on RegTech, its influential papers and authors, its main areas of research, its past and its future. The resulting multi-dimensional framework bridges across four main dimensions, starting with regulation and technology, where one or more regulations, not necessarily financial ones, are addressed with the support of technologies (e.g. artificial intelligence, DLT, blockchain, smart contracts, API). Data play a central role, as sharing them enables data ecosystems, where additional value can be attained by each market participant, while data automation and machine-readable regulations empower regulators to pull data directly from the banks' systems and combine these data with data obtained directly from customers or other external sources. Several applications emerge, both for regulated entities, covering matters of compliance, monitoring, risk management, reporting and operations, as well as for authorities, which can leverage on RegTech (SupTech) solutions to make policies, to undertake their authorising, supervising and enforcement operations, for monitoring and controlling purposes, and even to issue fines automatically. As a consequence, stakeholders can reap a series of benefits, such as higher efficiency and effectiveness, accuracy, transparency and lower compliance costs but also risks, such as cyber risk, algorithmic biases, and dehumanization

Big Data and Its Applications

In times when everything is online, one thing which is common in every application is the use of data. Data is being generated every second, when applications are generating exponentially larger data sets every second it’s the big data which comes into effect. The major objective of this paper is to state the meaning of big data, figure out various ways as how to digest this data. Further this paper will also focus on the applications of Big Data in multiple segments: Finance, Banking and Securities and  Health Care Sector

e-Government in a connected society: a friend or a foe (32)

Organisations in the last decade are faced with the challenges posed by modern technology, changes in consumer behaviour and the emergence of new enterprises, whose operations are entirely based on innovative business models and the digital business. Digitization itself is the concept, which often occurs during the strategic plans of the organizations. Although public administration does generally not fall within the areas of high competition, the external environment is also forcing it into changes. These changes may be seen through the renewed portal of public administration, an increasing emphasis on digitization of the services, connecting e-Government towards the people etc. However, it is often forgotten that digitization is not based merely on technology itself, but it should include also organizational aspect and business process management as well. The purpose of this research in progress is to present the concepts behind e-Government and to demonstrate the extent to which digitization of public services is following objectives such as reducing costs, shortening business cycles and improving the quality of service. The paper will through the eyes of the end user highlight the shortcomings of the public administration digitalization and indicate possibilities for future development