Big data and Internet of Things (IoT) technologies in Omani banks: a case study

Stuti Saxena and Tariq Ali Said Mansour Al-Tamimi

Stuti Saxena is based at the Department of Political Science, Central University of Haryana, Mahendragarh, India. Tariq Ali Said Mansour Al-Tamimi is based at the Department of Statistics, Sultan Qaboos University College of Science, Muscat, Oman.

Abstract Purpose The purpose of this paper is to underline the significance of invoking Big Data and Internet of Things (IoT) technologies in Omani Banks. Opportunities and challenges are also being discussed in the case study. Design/methodology/approach Four Omani banks representative of local, international, Islamic and specialized banks are being studied in terms of their social networking presence on Facebook and their e-banking facilities. Also, impetus is laid upon the aggregation of internal data and vast amounts of semi-structured external data from public sources, including social media. Findings The case study shows that Big Data analytics and IoT technologies may be utilized by the Omani banks for facilitating them in forecasting and nowcasting. Besides, customers may be better managed with better and efficient services. However, there are challenges in tapping these technologies such as security, infrastructure, regulatory norms, etc. Practical implications Banks in Oman need to appreciate the utility of Big Data and IoT technologies, and for this, a robust IT infrastructure should be institutionalized. Originality/value The case study is a major step in integrating Big Data and IoT technologies in Omani banks across four variants of national, international, Islamic and specialized banks. This is the first study where such integration has been emphasized in the Omani banking sector.

Keywords Big data, Information management, Banking, Technology-led strategy, Internet of things

Paper type Case study

1. Introduction

The significance of IT in banking and financial services may be witnessed by the changing technology landscape over the years. Therefore, banking sector has been harnessing the potential of IT in providing services to the customers. Besides tapping the electronic channel for providing services and improving customer relationship, banks have been invoking social media networking for improving their relationship with the customers (Ozdora-Aksak and Atakan-Duman, 2015). On the one hand, self-service technologies like the ATM are providing services to the users and generating a large amount of data regarding the transactions, and on the other hand, the utilization of social networking media has been instrumental in the accumulation of data regarding the responses and feedback from the users. Voluminous data are being exchanged during banking transactions internally as well as externally. Besides, Internet of Things (IoT) technologies are useful in channelizing the data collection and processing stages for an organization. The present case study seeks to address this call by proposing the integration of Big Data and IoT technologies in Omani banks by substantiating our argument with a case study of four Omani banks which are deploying self-service technologies and social media (Facebook, for instance) with the objective of providing better customer services. Elsewhere, banks have adopted Big Data analytics for processing the humungous data stored with them

Received 18 March 2017 Revised 13 May 2017 Accepted 15 May 2017

DOI 10.1108/FS-03-2017-0010 VOL. 19 NO. 4 2017, pp. 409-420, Emerald Publishing Limited, ISSN 1463-6689 Foresight PAGE 409

about the customers and transactions. For instance, banks in England (Bholat, 2015) and Singapore (Ng, 2012) have integrated Big Data analytics in their operations for providing efficient customer services. Likewise, research has laid emphasis upon invoking IoT technologies for streamlining performance. IoT implies that individual, man-made or natural, objects and interrelated collections of objects, e.g. in homes and cars, can be made uniquely identifiable by radio tags, sensors and actuators, and thereby become virtually represented in wireless and wired internet structures (Andersson and Mattsson, 2015, p. 85). We posit that Omani banks have the potential to harness the Big Data sourced from self-service technologies and their social media platforms and apply sophisticated tools and technologies for on a real-time basis as well as nowcast and forecast solutions for unforeseen problems. Further, we emphasize upon the utility of IoT for the banking sector in Oman for ensuring efficiency and effectiveness in services.

The paper is structured as follows: Section 2 shall provide a brief about Big Data; Section 3 shall provide a review of IoT; Section 4 shall provide a brief about the significance of Big Data and IoT for the banking sector; Section 5 shall discuss about the banking sector in Oman; Section 6 shall provide a case study example of how four banks in Oman are using social media for customer management; Section 7 shall provide a brief about the integration of Big Data analytics and IoT in the four banks and provide an overview of the challenges and prospects which may result by integrating Big Data analytics and IoT in the banking sector in Oman; Section 8 shall provide summary remarks followed by a section on limitations of the study and further research directions (Section 9), and the paper shall conclude with social and practical implications (Section 10).

2. Big Data

Big Data pertains to the five Vs which imply volume, variety, velocity, veracity and value. Volume of data implies that there is a lot of data which need to processed, variety denotes different formats in which data are made available and stored, velocity indicates the speed with which data are generated on a real-time basis, veracity implies truthfulness and credibility of the data thus collected and finally, value implies the utilitarian aspect of the data. Even in the banks, the data which are generated is of high volume, high velocity and diverse in form (Bholat, 2015).

In the corporate sector, organizations like Amazon, IBM and Hewlett-Packard have been deploying Big Data analytics for processing the humungous data generated by them every moment. Also, other sectors like public sphere, healthcare, education and environment are gradually moving forward to integrate Big Data in their operations. Big Data, provided that are analyzed properly, might be a very useful tool for business decision-making. Nevertheless, combining and processing them is not possible using traditional analytical tools, and thus requires the development of the sophisticated software solutions. As the term Big Data generally refers to data sets so large and complex that traditional tools are no longer sufficient to process them, appropriate IT infrastructure and dedicated software are prerequisites to analyze such data properly.

3. IoT: a brief

IoT may be defined in simple terms as (envisaging) a society where all members have access to a full-fledged Internet environment populated by self-configuring, self-managing, smart technology anytime and anywhere (Nolin and Olson, 2016, p. 362). Things are categorized as a hierarchy of five domains (Sundmaeker et al., 2010). The lowest domain corresponds to domain 1 where there are real-world entities or virtual entities which interact with each other as well as with the infrastructure supporting these entities; domain 2 corresponds to the level where the things are imbued with sensors, and they are able to interact with the environment; the third level is domain 3 wherein the virtual entities engage

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in collaboration and networking with other entities; domain 4 is an advanced level wherein the entities are able to exchange communication with the environment and reason out different aspects; and domain 5 corresponds to the most sophisticated level wherein things are able to self-replicate themselves besides monitoring, managing or preempting other things.

The term IoT was propounded in a crude form in 1999 (Ashton, 2009), and it refers to information-sensing devices and technologies, such as global positioning system, (RFIDs), infrared sensors, laser scanners, gas inductors, etc. [. . .]. It is a (Dweekat et al., 2017, p. 270). Furthermore, IoT helps in linking objects or processes which enable better monitoring and interaction. There are four layers of IoT architecture:

1. the sensing or perception layer (collects and transmits data with the help of object identification properties and reader tools);

2. the gateway and network layer (connects objects or things and allows them to share and exchange information with the help of a gateway, an internal network or a local area network and an external network or wide area network);

3. the management service layer (in-charge of information analytics, security control, process modeling and device management); and

4. the application layer (collected and transitioned data are reserved, processed through certain techniques to be used for a plan and objects or things are managed and controlled).

IoT technologies are useful in supply chain management, logistics, manufacturing (Zelbst et al., 2012), food chain industry (Grunow and Piramuthu, 2013), healthcare sector (Chong et al., 2015), etc. (For an extensive review of IoT, please refer to Mishra et al., 2016).

4. Big Data and IoT for the banking sector

Banks and financial institutions are yet to invoke Big Data in their operations (Bholat, 2015; ., 2016). There are many ways in which customer relationships are forged via banks. For instance, the most commonplace means of customer relationship management is through the offline banking mode wherein the customer visits the bank or other . The other popular means of transacting with the customer is via online modes. For instance, electronic banking or virtual banking is invoked wherein internet banking, telephone banking, ATM, WAP-banking and other means are being invoked (Cheng et al., 2006). Likewise, m-banking or mobile banking is utilized to provide customer services over mobile networks and devices (Lee et al., 2015; Yadav et al., 2015). All these offline and online channels act as potent sources of Big Data for the banks.

Besides, banks indulge in customer relationship management (CRM) activities through their activities on social networking media like Facebook or Twitter. This dimension of banking is known social banking, wherein banks may engage the customers and predict their behaviors using insights from social data (Ghazinoory et al., 2016). Thus, these social banking activities are again a potent source of Big Data, in the sense that banks are apprised of the needs and requirements as well as feedback and grievances regarding various issues.

Likewise, with the issuance of plastic cards (credit cards and debit cards) and other customer products where sensing technologies are involved, IoT technologies are being harnessed by the banks for generating customer data and drawing meaningful insights from the same. This is also implicative of the security of confidential data (personal information of the customers) against cyber crimes. IoT technologies generate Big Data in their own turn, and they are useful in helping the banks to understand customer needs, market dynamics, and strategic issues with unmatched precision (McKinsey Quarterly, 2015). Identification may be made easier, and

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smartphone users (i.e. customers) may benefit from global positioning systems (GPS), sensors and electronics to identify their location. In case of theft or misplace of the plastic currency, IoT technologies come in handy to find the lost objects. Finally, IoT technologies are useful in social networking as they help in taking count of the social networking activities of the users.

5. Banking sector in Oman

The Sultanate of Oman borders the Republic of Yemen, the Kingdom of Saudi Arabia and United Arab Emirates. The area of Oman is about 309,500 km2. The population of Oman has been growing over the years, and the government is in the process of releasing its latest census figures in 2020 (www.omansultanate.com/demographics.htm). The internet usage is on the high in Oman which is attested by 2,584,316 internet users as in December 2014, which amounts to 78.6 per cent penetration[1]. Until recently, the country was gearing its economy through oil and gas resources. However, with the push on diversification of the economy, the country is envisaging itself into fortifying other sectors like logistics, fisheries, mining, tourism and hospitality (Ninth Five Year Development Plan, 2016-2020).