IMPACT OF BIG DATA
The Big Data Which is Likely to Have an Impact on the Finance
This essay examines the impact that big data may have on finance and shows how postgraduate students might assist their industries to either prepare for opportunities or adapt to these challenges in the future. Basic, industries have over decades managed large quantities of data and used it as the dominant force. However, there is an increase in volumes of data collected in the last few years. According to (Www-01.ibm.com, 2019), there is a creation of 2.5 quitillion bytes of data daily result to the creation of 90% of data in the world. Organizations use the collected data to gain insight that helps in making critical decisions. This essay argues that data is very important to any organization. In particular, the financial sector widely depends on available data so as to make better-informed decisions. The essay shows the benefits that the organization have when they add commercial value to the data they collect. It also shows how to postgraduate students may use their knowledge to advice industries about opportunities associated with big data collection as well as how to avoid associated challenges. But for simplicity, this essay will narrow down its research on the banking and insurance company which are a good example of an industry that keeps big data.
One of the benefactors of big data are the financial markets whose trading strategy uses sophisticated algorithms. As Bail explains and says “The rise of the Internet, social media, and digitized historical archives has produced a colossal amount of text-based data in recent years” (Bail, 2014, p. 471) demands faster execution led to digitalization of trading in the financial markets. Success has achieved by the use of big data a wide variety of data that has been generated from different sources. In his book, Davenport states that “big data gives managers a comprehensive understanding of the importance of data to the company’s future and shows how the data can actually be used”. Big data becomes important when actionable information is extracted and combine with information sources from different geographical areas and other forms of assets so as to create a rich database. This gives a comprehensive outlook of the market and thus the information can be used in reporting profits and loses, trade execution, signal generation, and risk assessment, therefore, enabling the effective trading through market analysis.
Benefits of big data are limited by various factors like lack of skills, lack of data actionability, and use of old infrastructure and culture. These happen when banks use rigid IT infrastructure and bad legacy system. Others lack qualified human labor to perform the required task while some task is basically not actionable. Parallel and distribution systems will continue to be used in data analysis making it an effective way of analyzing data (Kambatla et al. 2014, p. 2570). But this claim is not totally true. Kambatla showed the use of the application on data the has been properly obtained. Moreover, his suggestion makes the assumption that the work is done by skilled people who deliver high-quality work. But it’s evident that much more researchers have found there exist some challenges that face big data. Big data requires advanced architectures and technologies in order to extract and analyze data but due to the size of the big data, it becomes difficult to analyze the data effectively (Katal, Wazid & Goudar, 2013, August). Similarly, their other research has shown that to get a result not only is the collection of data that is required but also some studies on business analytics and intelligence (Chen, Chiang, & Storey, 2012). This shows that human capital should be well equipped with relevant skills to carry on their work. Using unskilled laborious will result in ineffective analysis of data.
However, there are other threats that face big data and which have an impact on finance. Banks utilize the big database they have to detect activities that can lead to fraud and this helps in reducing risks associated with the fraud activities. The financial institution has always been at the risk of suffering from a fraud activity. In the past banks used to collect and analyze a small amount of data. In the current world, the continues card transactions have led to an increase in stolen accounts and this has led to losses in the banking sector (Tuo et al. 2004, p.58). Despite this banks continue to encourage customers to use online means of transaction. But to encourage electronic banking there is a need to enhance customers trust by reducing fraud in the platform. To do that managers will have to advance information science and service sciences (Yazdanifard et al. 2011, p. 10). One action that can take to prevent fraud is to notify subscribers in the system about the occurrence of the fraudulent activity. Some of the subscribers are financial institutions, retail houses, and law enforcement agencies (Kerr, 2004, p. 343). This will be possible if there is proper utilization of the available database.
Digitalization and big data technologies help in improving customer’s interaction in the industry within the digital sphere. Information like payment methods helps the banking industry to know the spending patterns of their clients which can help to categorize customers. Organization interaction with customers is an increase in modern society as industries seek to improve their competitive edge. Communication service providers in the different organization have the same devices of interacting with customers. Business is working to provide superior customer experience by highlighting the specific thing that drives each customer (Spiess, T’Joens, Spencer & Philippart, 2014). Big data helps organizations to improve in their customer interaction. Kunz states that the prior literature emphasizes customer interaction by a focus on how it benefits the firm and forgets to look at how customers benefit (Kunz, 2016, p. 136). The literature is relevant to big data as the data is used to determine how the organization will interact with the customer. This idea is supported by Gebert who claims that in order for businesses to gain the competitive advantage they apply the concept of knowledge management and customer relationship management. The financial organization, therefore, can get new knowledge and technology from sources like social media. King (2014, p. 236) indicate that social media are not only used for entertainment but rather they can be sources of new ideas.
In addition, big data helps financial institutions to have an easy customer segment. Banks have different categories of customer who have a different kind of financial requirements. Research done by Devenport (2013) shows that the first decade of the 21st-century startup firms and online organizations embraced the big data concept. Some of the organizations formed are companies like Facebook, Twitter, Google, and eBay. But more recent research has shown there is now a new list of leading firms in data analytic capability (GalbRaith, 2014). Hence, more firms have realized the power of having big data as it helps industries to categorize inappropriate parameters for easy analysis. Therefore, firms are able to advertise their products to various customers according to the needs of the customers. The target audience and the potential customer becomes very precise and the firm saves cash by reducing advertising cost while increasing sales. This means that each product is each advertisement and personalized at a certain customer and the product is presented to the customer for sale in a certain transaction (Kanevsky & Zlatsin, 2001). Segmentation of customers assists in easy management of the organization and effective analysis.
Big data affects the finance sector of any business and such data presents opportunities as well as challenges. Proper venture into big data has a positive impact on the business. Big data has the potential of bringing a revolution in the discipline of management (Wamba et al. 2015, p.237). However, there is empirical research that should be conducted before embarking on the big data. In the long-run big data affects not only the customers but also the organization. Therefore, in the near future, the concept should be applied by more and more organizations. Big data relates to a consumer’s privacy, welfare, and security (Kshetri, 2014). It also helps to divide big problems in the organization into small problems which are manageable. Risks are prevented therefore preventing losses that could be incurred.
Managers and business use big data due to its impact on the finance sector of business. But the organization should be careful to ensure that they obtain actionable data, and use skilled personnel to handle the data. Also, firms should review their policies so that they can abolish the rigid and old IT system so as to accommodate big data. Some of the benefits of big data are: improving customer interaction, preventing or avoiding fraud activities, and dividing customers into a segment for easy advertisement. The trend of keeping big data is at the rise among various industries leading to higher competition as each tries to increase their competitive edge. However, the customer benefits from the big data as they are treated better as firms compete on who will give the maximum and appropriate services. Therefore, not only is big data important to firms an industry but also to customers. Professionals should apply their skills to ensure that they possess the right level of database in their organization.
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