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The Use of Data Analytics in Financial Markets

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At Meraglim™, we take a multidimensional approach to our product. Not only do we give our clients access to our panel of prominent experts from a variety of fields, we also use an AI analytic engine to provide data analytics as a service (DAaS). More and more, companies are contracting companies to provide DAaS, as the valuable information this provides can be revolutionary for business. With the emerging technologies breaking into the market today, it’s imperative to implement the analytic tools at your disposal or risk falling behind the curve. Recently, our partner IBM collaborated with Saïd Business School at the University of Oxford to look into how banks and financial markets organizations are using data analytics to change the industry in “Analytics: The real-world use of big data in financial services.” In this blog, we will review their findings and how data can serve your team.

The Importance of Data in Financial Markets

For banks and financial services companies, there isn’t a physical product for them to offer. Supplying information is their trade, and data is an important resource for providing quantifiable support for their services. Within the financial services industry, there is endless data to be mined from the millions of transactions performed on a daily basis. The important advantage analyzing this data provides to financial institutions is evident; IBM and Saïd found that 71 percent of financial markets firms report that they have developed a competitive advantage by using financial data analytics. When comparing this statistic with the respondents to a similar research study by IBM two years prior, it increased by 97 percent. While banking data has grown to provide more valuable information, in our technologically advanced world, people are now banking and managing finances in a variety of ways. This unstructured data has important promise for reading into customer’s insight. This detailed information can guide investors, financial advisors, and bankers to making the best decisions for their customer base while staying compliant with regulatory laws. Companies have successfully used this data to identify business requirements and leverage the current infrastructure accordingly.

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Big Data Movements Today

Most financial organizations today recognize the importance of big data, and are slowly implementing plans on how to use it. The majority are either currently developing a big data plan (47 percent) or are already implementing big data pilots (27 percent). In their study, IBM and Saïd found four findings that demonstrated how these companies are using big data.

The customer is king

More than half of industry respondents identified customer-driven goals to be their priority for big data. This stands to reason as more and more, banks are facing pressure to be customer-centric. Financial institutions must keep the customer in mind when designing their technology, operations, systems, and data analytics. Data analytics is an important tool because it enables companies to anticipate changes in the market and customer preferences to quickly take advantage of any opportunities that present themselves.

Companies need a scalable big data model

The research also found that the most important consideration companies must make when creating a big data model is that it must be able to accommodate the ever-growing amount of information from different sources. In a survey of these financial institutions, though only half of companies reporting said that they integrated information, IBM found that roughly 87 percent of respondents reported having the infrastructure that was necessary to accommodate the addition of more information.

Integrating data across departments and areas has been a challenge to businesses for many years now, particularly in respect to banks due to the sheer amount of data that comes into play. This complex part of integrating big data is an essential component. It most often requires the integration of new analyzing software components, such as NoSQL and Hadoop. However, the financial industry is falling behind in this respect.

Efforts are focused on existing sources of data

When looking at what financial institutions and banks are doing in terms of big data efforts, the majority are focused on using the data sources they already have internally. This makes sense, because, while big data has clear and important implications for the future of these companies, they want to take a cautionary approach rather than trying to find brand new data and risking it being useless. It also speaks to practicality, as there are many uses for the internal data of these companies that is as of yet untapped.

Most commonly, respondents to this survey were analyzing log and transactions data. Every transaction and automated function of the bank or other information system is used, which cannot be analyzed by traditional means anymore. As a result, there is years and years of data that has yet to be analyzed by these institutions. Today, the technology finally enables this information to be used, though someone with the analytical skills is also necessary.

Banks and financial markets could catch up to their peers in terms of analyzing more varied types of data. Roughly 20 percent of respondents analyzed audio data, and about 27 percent analyzed social media. A lack of focus in unstructured data could be disrupting their ability to do better in these terms.

Analytical ability is important

While data in and of itself plays an important role, it cannot be put to use without proper analysis. For big data to be the highest value, it is essential for financial institutions to access the right data, use the right tools to analyze it, and have the necessary skills to analyze it. This is why it may be necessary for financial institutions to hire outside counsel, as they may not have the needed analytical skills.

While participants in the study who were engaged in big data efforts had a strong foundation in certain major analytics, such as basic queries and predictive modeling, these institutions need to work more on data visualization and text analytics. The more data there is, the more important these two elements are to gaining meaning from data. Yet only three out of five respondents with big data efforts included data visualization.

Additionally, financial institutions fall significantly behind when compared to other industries in terms of analyzing different kinds of data. Fewer than 20 percent of respondents included the ability to analyze natural text (such as call-center conversations) in their big data efforts. Text analytics allow companies to not only look at what was said, but the nuances involved in language. These allow companies to see a bigger picture of what the customer desires and how to improve customer relations. They fall even further behind from their peers in terms of other types of data, including geospatial location data and streaming data. While they may have more technology to analyze these areas, they rarely have the people with the skills necessary to apply this data.

Recommendations

Based on the information they generated, the research team proposed several recommendations for financial institutions and their big data use. First, they suggested that it is imperative to focus efforts on the customer: understanding your customer is the key to success in the market. Additionally, they emphasize developing a big data plan that aligns with their business’s needs and resources; while it is important to keep up with the technology, it is imperative that an effective blueprint is in place to ensure that any challenges can be addressed. This ensures that the company can address future additional data needs. Additionally, researchers suggest that initially building on already available data is key for approaching big data analytics in a pragmatic way. Businesses should also consider their own priorities for growth and pinpointing what data to look at, as opposed to just looking at what is in front of them. Finally, they should implement big data strategies by finding quantifiable measures of success. Most importantly, business leaders and technology specialists need to be able to support each other through their endeavors to implement big data plans.

Meraglim™ is a financial technology company that uses financial data analytics to provide our clients with the information they need to remain one step ahead of everyone else. If you are curious about how our financial technology may benefit your organization, learn more here today.

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