IDRBT JOURNAL OF BANKING TECHNOLOGY



To read the Complete IDRBT Journal of Banking Technology (Inaugural Issue) please click here.

Editorial Board

Reflecting the thrust of the Journal, the Editorial Board of the Journal represents a fine balance of researchers and practitioners. The Editorial Board of the Journal is as under.

Editor-in-Chief
Name Affiliation
Dr. A. S. Ramasastri Director
Institute for Development and Research in Banking Technology (IDRBT)
Road No. 1, Castle Hills, Masab Tank
Hyderabad, India.
e-mail: asramasastri@idrbt.ac.in.
Editorial Board Members
Name Affiliation
Prof. Chin-Teng Lin University Chair Professor/Provost
Engineering and Information Technology
University of Technology, Sydney
Electrical and Computer Engineering
National Chiao-Tung University, Taiwan, China.
e-mail: Chin-Teng.Lin@uts.edu.au.
Prof. Constantin Zopounidis Director of the Financial Engineering Laboratory
School of Production Engineering and Management,
Technical University of Crete, Chania, Greece.
e-mail: kostas@dpem.tuc.gr.
Prof. Dirk Van den Poel Professor
Data Analytics/Big Data
Faculty of Economics and Business Administration
Ghent University, Belgium.
Tweekerkenstraat 2, 9000 Gent, Belgium.
e-mail: dirk.vandenpoel@UGent.be.
Prof. D. B. Phatak Professor
Department of Computer Science and Engineering
Indian Institute of Technology, Bombay, India.
e-mail: dbp@it.iitb.ac.in / dbp@cse.iitb.ac.in.
Prof. Kalyanmoy Deb Koenig Endowed Chair Professor
Department of Electrical & Computer Engineering
Professor of Computer Science & Engineering
Professor of Mechanical Engineering
Michigan State University, USA.
e-mail: kdeb @ egr.msu.edu.
Mr. Marc Hollanders Special Adviser on Financial Infrastructure
Monetary and Economic Department
Bank for International Settlements, Switzerland
e-mail: Marc.Hollanders@bis.org
Mr. Massimo Cirasino Advisor and Global Lead for Payments and Market Infrastructures
Finance and Markets Global Practice
The World Bank, Washington, USA.
e-mail: mcirasino@worldbank.org
Prof. Paolo Bellavista Associate Professor,
Department of Computer Science and Engineering
Università di Bologna, Italy.
e-mail: paolo.bellavista@unibo.it
Prof. Rajkumar Buyya Professor, Department of Computer Science and Software Engineering
Director, Cloud and Distributed Systems
University of Melbourne, Australia.
e-mail: rbuyya@unimelb.edu.au
Prof. R. K. Shyamasundar JC Bose National Fellow & Distinguished Visiting Professor
Department of Computer Science and Engineering
Indian Institute of Technology, Bombay, India.
e-mail: rkss@cse.iitb.ac.in
Prof. Sushil Jajodia University Professor
BDM International Professor of Information Technology
Director, Center for Secure Information Systems
Volgenau School of Engineering,
George Mason University, Fairfax, Virginia, USA.
e-mail: jajodia@gmu.edu
Mr. Thomas Lammer Senior Market Infrastructure Expert
European Central Bank
Frankfurt, Germany
e-mail: Thomas.lammer@ecb.int
Prof. Venu Govindaraju SUNY Distinguished Professor
Department of Computer Science & Engineering
Director, Center for Unified Biometrics and Sensors.
University at Buffalo, State University of New York, USA.
e-mail: venu@cubs.buffalo.edu

Banks have been adopting various technology solutions for carrying out their functions. All such technologies leveraged by banks can be broadly considered to constitute banking technology.

In view of the large scale operations, which were to some extent routine, banks first deployed the early versions of manual calculators. Gradually, they moved to electronic calculators and then to various generations of computers. Presently, banking sector is one of the biggest consumers of computing infrastructure. Similarly, banks have moved from the days of telegram to today’s digital networks for communications. Banking is moving closer to its customers through desktops and mobiles. Instead of banking, it is digital banking today.

Adoption of technology is bringing several benefits to banking; some of them being – better customer service, operational efficiency and cost optimisation. Such technology adoption is being made possible by the work carried out by several individuals and institutions across the globe. While on one hand there have been advancements in computer, communication and other relevant technologies due to the research carried out in academic institutions; on the other hand, bankers and technology companies are working together to ensure that newer technologies are adopted for better banking. It is the combination of fundamental and applied research that is pushing banking technology forward.

The Institute for Development and Research in Banking Technology (IDRBT) was established by Reserve Bank of India over two decades ago. It is a visionary and forward looking initiative of the central bank of the country to establish a unique Institute exclusively for research and development in the area of banking technology.

The Institute has been carrying out research and development in the area of technology useful to banks and other financial institutions in India. Towards this objective, the Institute has been bringing out various publications that present the latest technological innovations and developments. The Institute hosts international conferences every year with participation of renowned researchers from across the world.

The IDRBT Journal of Banking Technology is the culmination of the Institute’s efforts to bring together high quality research output across all areas of technology that are directly or indirectly relevant to banking. The aim of the journal is to publish current research from academia and also present the emerging perspectives of practitioners.

I am happy that researchers and professionals of very high standing contributed to this inaugural issue of the Journal. It is an honour to receive an article by Dr. Duvvuri Subbarao, Former Governor, Reserve Bank of India on “Disruptive Innovation in the Financial Sector” for the very first issue. The article is an extension of his talk on the same topic at the 18th International Conference on Distributed Computing and Networking, held at IDRBT from January 05-07, 2017.

The three research articles – “Artificial Neural Networks for Artificial Intelligence” by Prof. Nikola Kasabov, “Anomaly Detection in Banking Operations” by Prof. Chilukuri K. Mohan and Prof. Kishan G. Mehrotra and “Indoor Self-Localization via Bluetooth Low Energy Beacons” by Prof. Marco Aiello et al - have dwelt on artificial intelligence, anomaly detection and location information, which are important areas of focus of banking technology. The article titled “Upcoming Research Challenges in the Financial Services Industry: A Technology Perspective” is an apt contribution by Raghu Krishnapuram, Anirban Mondal for the first issue of the Journal as it details the various current research areas in the financial services industry and draws the broad contours to the scope of the journal.

We have set ourselves the goal to make this journal a repository of high quality research and application articles on technology that is useful to banking. We feel, we have half-achieved the goal with the receipt of articles from reputed researchers and professionals from various parts of the world – making it a truly international journal. We endeavour to grow with every issue under the able guidance of the top-rated Editorial Board members and continued support from researchers and practitioners globally.

Dr. A. S. Ramasastri
Editor-in-Chief

Please click here to read the pdf version of Editorial.

Indoor self-localization via bluetooth low energy beacons

Azkario Rizky Pratama; Widyawan; Alexander Lazovik; Marco Aiello


Abstract: Indoor localization is concerned with mapping sensory data to physical locations inside buildings. Location of a user or a mobile device is an essential part of the context, and is therefore very useful for pervasive computing applications. Many proposals exist for solving the localization problem, typically based on image or radio signal processing, though the problem is still generally considered to be open, especially when costs and privacy constraints play an important role. In this paper, we propose a solution based on the emerging Bluetooth Low Energy (BLE) standard and off-the-shelf hardware. Such approach proves to satisfy economic constraints, while challenging in terms of accurate location. To translate beacon signals into locations, we consider several approaches, i.e., cosine similarity, nearest neighbourhood classification, and the nearest beacon. Our experiments indicate a vector based approach as the most suited one. In fact, we show its effectiveness in an actual office deployment consisting of five indoor areas: three multiuser offices, a social corner, and a hallway. We achieve 90% and 80% for accuracy and F-measure, respectively.

Keywords: Ubiquitous computing; Smart buildings; Indoor localization; Bluetooth; Low energy beaconing

To read the Complete article please click here.

Anomaly detection in banking operations

Chilukuri K. Mohan1; Kishan G. Mehrotra


Abstract: This paper presents an overview of anomaly detection algorithms and methodology, focusing on the context of banking operations applications. The main principles of anomaly detection are first presented, followed by listing some of the areas in banking that can benefit from anomaly detection. We then discuss traditional nearest-neighbor and clustering-based approaches. Time series and other sequential data analysis approaches are described. The problems posed by categorical data are also discussed, along with the methods proposed in the literature to address the same. The ensemble methods are presented, followed by mathematical perspectives on anomaly detection.

Keywords: Anomaly detection; Banking; Time-stamped data; Categorical data; Ensemble methods

To read the Complete article please click here.

Artificial neural networks for artificial intelligence

Nikola Kasabov


Abstract: Artificial neural networks now have a long history as major techniques in computational intelligence with a wide range of applications for learning from data. There are many methods developed and applied so far, from multiplayer perceptrons (MLP) to the recent ones being deep neural networks and deep learning machines based on spiking neural networks. The paper addresses a main question for researchers and practitioners: Having data and a problem in hand, which method would be most suitable to create a model from the data and to efficiently solve the problem? In order to answer this question, the paper reviews the main features of the most popular neural network methods and then lists examples of applications already published and referenced. The methods include: simple MLP; hybrid systems; neuro-fuzzy systems; deep neural networks; spiking neural networks; quantum inspired evolutionary computation methods for network parameter optimization; deep learning neural networks and brain-like deep learning machines. The paper covers both methods and their numerous applications for data modelling, predictive systems, data mining, pattern recognition, across application areas of engineering, health, robotics, security, finances, etc. It concludes with recommendations on which method would be more suitable to use, depending on the data and the problems in hand, in order to create efficient information technologies across application domains.

Keywords: Artificial intelligence (AI); Artificial neural networks; Evolving Connectionist Systems (ECOS); Neuro-fuzzy systems; Spiking Neural Networks (SNN); Evolving spiking neural networks; NeuCube; Quantum inspired neural networks; Spatio-temporal pattern recognition; Data mining

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Upcoming research challenges in the financial services industry: a technology perspective

Raghu Krishnapuram; Anirban Monda


Abstract: Several key transformations in the macro environment, coupled with recent advances in technology, have opened up tremendous innovation opportunities in the financial services industry. However, many research challenges need to be addressed for realizing the full potential of innovation in financial services. Examples of such challenges include context-aware analytics over uncertain and imprecise data, design of user-friendly interfaces for improved expressiveness in querying financial service providers, and personalization based on fine-grained user preferences especially in the presence of sparse data. In this paper, we arrive at these research challenges based on an analysis of the macro environment and technology trends, and provide our vision and perspective on the same.

Keywords: Financial services industry; Macro environmental trends; Financial technology; Intelligent digital mesh; Innovations

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Disruptive innovation in the financial sector

Duvvuri Subbarao


Abstract: Disruptive innovations have been happening in the field of finance as a consequence of a magical combination of technology and financial engineering. The Indian financial sector too has seen disruptive innovation not just in payment systems but also in the segments of deposits, credit and insurance. This article discusses the key drivers behind this disruptive innovation in Indian financial sector including internet penetration, usage of smartphones, improved online presence and policy initiatives. Further, the article elaborates the disruptive innovation that is presently caused by FinTech companies in accelerating the pace of change and reshaping the financial services industry radically.

Keywords: Disruptive innovation; FinTech; Indian Finance; Technologies; Demonetisation

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Publisher Contact

Queries, if any, may be sent to

S. Rashmi Dev

Assistant General Manager - Publications
Institute for Development and Research in Banking Technology (IDRBT)
Castle Hills, Road No.1, Masab Tank, Hyderabad - 500 057.
Telephone: +91 (40) 2329 4163
Fax: +91 (40) 2353 5157
Email: ijbtqueries@idrbt.ac.in