Financial Services Must Learn How To Approach Big Data, And Use It

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A business is as good as its performance, and that performance is only good if it is monitored often. So, as a business leader, what tools can you use in order to effectively measure your business’s data?

As many financial professionals may know, analytics is the best way to gain insight in order to answers questions with accurate and strategic responses.

“Analytics is an encompassing and multidimensional field that uses mathematics, statistics, predictive modeling and machine-learning techniques to find meaningful patterns and knowledge in recorded data.” Sas reports.

For obvious reasons, analytics is extremely important in finance, mainly because customers are trusting financial service organizations with extremely sensitive and secure personal data.

“To fully leverage the value of customer data and drive profitable growth, financial institutions must bake advanced analytics into their cultural DNA. Those banks and credit unions that figure out make the right data available to the right people at the right time will have a significant competitive advantage.” The Financial Brand reports.

Financial analytics also works in a way that helps banks gain knowledge about the future of their business. It helps organizations stay competitive in the industry, and to make smart decisions. Sounds good, right?

It is good. It is so good in fact, that most banks have incorporated financial analytic tools in their services.

Who Is Using Analytics?

Citibank, one of the world’s largest financial service institution, uses data to drive decisions and deliver customers top-notch experiences. 

“At Citi, model testing allows for a holistic understanding of innovative use cases by deconstructing data at its most granular level as well as synthesizing structured and unstructured data sources. It comes down simply to “what can data do for us?” among business leaders at many of these venerable institutions.” Forbes reported.

According to Forbes, this bank is using engineering and big data analytic activity in order to predict the future of the bank and to create a “jump start” approach that will ultimately provide the bank benefits.

The main target of Citibank has been to focus on customers by using web analysis and big data in order to spot any anomalies, like unusual spending, that could result in cyber fraud. This follows a predictive model, that is made possible through analytics.

In a similar way, Goldman Sachs is leveraging data in order to “become the next Google on Wall street”, according to an article published by Business Insider.

According to BI, Goldman Sachs is taking a strategic and analytic approach to using data with machine learning in order to help employees target customers effectively.

Goldman Sachs understands that they manage large amounts of data, so now they want to do something with that data to further position themselves to succeed above the competition, and to deliver direct results for their customers.

“What really makes us valuable is the immense amount of data that we have,” Chavez said. “In this job of inspiring our clients to call us because they have risks they don’t want or want risks they don’t have, there is incredible information content, and using that for the benefit of the clients to get a better result is what we’re up to.BI reports.

This proves that financial institutions are taking Google and Amazon’s lead by understanding the importance that data holds, as well as how crucial it is to use it effectively, with analytic tools.

Speaking of these tools, there are many different types of analytics that businesses can use for productive results. Let’s take a look at the different types of analytics.

You may be able to incorporate one into your business!

Business Intelligence

Some of the best ways to predict the future are to look at history. In business, examining the history of what has worked and what hasn’t, can be effective.

Business intelligence provides the tools that make this possible. It looks at internal and external data in order to prepare for an analysis that creates reports, dictating what is important to execute, depending on the trends in the market that are found.

By using historical information, combined with new data, business intelligence answers questions using the technology driven software that supports better decision making among higher management and business professionals.

In order to effectively carry out business intelligence, businesses must adapt the workplace to provide the tools to support the operations. For example, IT departments must set up tools like data ware houses and data marts that allow users to acquire data and create reports.

What Is A Data Warehouse?

A data warehouse is supported by the main frame of the business operations. As a matter of fact, we recently talked about mainframes in one of our recent Digital Diary posts!

If you didn’t catch that post, you can read it here.

Let’s recap. Mainframes support business functions. They are referred to as “big iron” and act as a support system for processes, using a centralized form of computing.

“Typically, a data warehouse is housed on an enterprise mainframe server or increasingly, in the cloud. Data from various online transaction processing (OLTP) applications and other sources is selectively extracted for use by analytical applications and user queries.” Techtarget reports. 

So, What Is A Data Mart?

Now that we covered what a data warehouse is, it is only fair we give data marts some credit.

The data mart is usually a “subset of an organizations warehouse”.  Its primary purpose is to look at data in a unique and tactical way.

In order to produce optimized results, data marts can be used with software called data virtualization, which pulls and combines data. This is done to meet the needs of business professionals using data to carry out business operations.

“A virtual data mart provides knowledge workers with access to the data they need while preventing data silos and giving the organization’s data management team a level of control over the organization’s data throughout its lifecycle.” Techtarget reports. 

Now that we have discussed how the primary functions of business intelligence work, let’s look at a few themes that business intelligence umbrellas.

Self-Service Business Intelligence

Self-service BI is an approach that targets individuals who are not exactly tech-savvy, by providing user-friendly tools such as dashboard navigation.

This approach does not require users to have a background in statistical analysis, or data mining in order to access and work with corporate data.

“This approach extends the reach and scope of BI applications to address a wider range of business needs and problems. At the same time, this extension must support the information workers’ need for a personalized and collaborative decision-making environment.” Tableau reports.

In order to support workers using this approach, a proper framework must be implemented. This can be done by first assessing users and then what tools will be needed in order to access self-service BI.

The benefits of this approach are simple in regard to the work environment. It enhances agility and control among users, as well as places a focus on specific data that should be used.

Operational Business Intelligence

Operational BI works in real-time, providing data that is needed on a day to day basis, in order to make tactical business decisions. By acting in real time, businesses are able to react right away, which can be helpful when it comes to catering to customers’ expectations.

“OBI works on continuously occurring business events and processes and is typically implemented in scenarios requiring business insight on a daily, short-term or frequent basis.” Techopedia reports. 

By dealing with data that is current, financial services are put in a position to provide targeted customer engagement on an immediate basis. This is important for banks who deal with cyber security threats.

Open Source Business Intelligence

We’ve talked about open source software on Digital Diary, read about it here.

Open source software allows programs to be made public on the internet, for users to view, modify, and share when accessed. Open source BI charges vendors for documentation and codes in order to access data.

Collaboration Business Intelligence

Collaboration business intelligence basically just makes analyzing more of a group effort, encouraging a group effort. In order for this approach to be effective, proper tools must be integrated into the work place.

“Tools allow peers to analyze data and exchange information and ideas through Web 2.0 tools like blogs and wikis. Modern tools also support brainstorming through social networking-like features, which continue to gain popularity for both business and personal use.” Techtarget reports. 

Using modern social tools promotes data driven decision making among teams. Collaboration is always important in any industry, especially the finance industry. Building collaborative internal and external relationships can set your team up for important opportunities.

Benefits Of Business Intelligence

The benefits of business intelligence are clear and concise. According to Chron, they are as followed.

Fact-Based Decisions

Management is able to read data found in reports in order to make strategic decisions such as what customers want, what works and what does not.

Improves Sales and Negotiations

Business intelligence can improve sales because it provides up to date and valuable data like sales trends and markets. Data-driven sales pitches are also impactful.

Identifies Opportunities

By using deriving data from business intelligence, companies can reflect on their own strengths and weaknesses, as well as establish any untapped opportunities that approach the market.

Being able to be a step ahead of these opportunities, enables businesses to react and make the proper changes that will further position them to have an advantage over competitors.

What’s Next?

Once you use these data analytic approaches to derive data, it is important to actually use the data found in order to make effective changes in your organization.

Banks need to answer the question, “what if” when it comes to different scenarios that affect the company or the targeted customer.

As financial institutions start to work with big data, they can begin to grow, by making necessary changes based on accurate, analytic information.

Using analytic information as a tool is so important in the financial industry because it supports organizations to meet the constant change that approaches as well as the growing competition.

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With digital transformation affecting the financial service industry, it is important for banks and major players to adapt techniques and tools in order to meet the growing market. Using different business intelligence tools in order to approach big data, gives organizations an opportunity to be ahead of the competition and to remain above the digital wave.

It is clear that data is growing, which can easily create issues with financial firms when it comes to targeting customers. the way customers are approached has changed, with the emergence of different types of data. It is crucial to control the data that is expanding, as well as to always keep it secure in order to protect customers private information.

Financial institutions must adapt to change, and learn new approaches in order to manage the massive volume of data that is growing.

C-level IT leaders in the financial services and insurance sectors are dealing with many challenges as digital transformation becomes an imperative. Understanding not only the convergence of Mobile, Social, and Cloud but also the possible implications of Artificial Intelligence, Machine Learning and Blockchain is vital to stay ahead of the competition.

This is not just another “Financial Services” event. Spaces are reserved for the best in the business. Apply to attend here!

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