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How Financial Companies Use Big Data To Make Decisions

Benny Emerling

Emerging technologies such as artificial intelligence and machine learning are transforming financial companies. "Big Data" is at the core of these innovations. It helps you find meaningful patterns that create value for your investments.

What Is Big Data?

Quintillion bytes of data are captured from customers and their transactions every day. These heaps of unstructured information can pile up and draw meaningful insight from all that data can be tedious and time-consuming.

With the help of artificial intelligence (AI), you can swiftly scan the data for relevant information at a fraction of the time. AI can identify potential patterns in the data for business development and present the findings in a clean and simple format. As a result, you and your company can take better business decisions with less time.

In the financial sector, banks have a huge amount of data on their customers. Information such as cash withdrawals and deposits are recorded by banks. Based on these behavioral patterns, banks offer different types of financial services. These services can include credit cards, mortgage loans, car loans and personal loans.

Financial companies use Big Data to analyze investment options. These investments can include stocks, real estate and foreign exchange currencies. Big Data plays a critical role in managing the risk profile. Financial products are tailored to fit the needs of the customer and improve returns.

Big Data Adoption
Source - IBM

“It is important to remember that even the highest quality information is not the same as knowledge. Investors can make decisions and act on knowledge — they can not act on information,” says Yewno CEO Ruggero Gramatica. “Big Data can be extremely useful once applied, but it is useless if you cannot gather, process and understand it.”  

Yewno|Edge is an investment research platform that takes hundreds of millions of constantly updating data points such as global patents, clinical trials, official filings and news and uses artificial intelligence to associate those data points with tangible concepts such as companies, industries and investment trends.  It can build and backtest strategies, calculate exposure to concepts and evaluate indirect risks. It tames big data by turning information into knowledge. 

Benefits of Big Data in Finance 

The digitalization of financial services offers a wide variety of benefits to customers. Financial firms leverage Big Data to manage customer expectations and deliver customized solutions. These benefits include the following.

Increased Customer Satisfaction

Relying on data collected from customers, financial firms offer personalized investment solutions. Big Data can store financial information such as payment methods and product purchases. This can hasten transactions and save precious time for their customers. 

By automating processes, Big Data can accelerate workflows and streamline your business activity. Without Big Data, you’d need to wait in long lines and fill out multiple forms by hand every time you want to register your request for any financial services you may need. 

 Advanced Cybersecurity

Hackers can steal invaluable customer information and sell it on the black market. Security measures such as fraud detection and unauthorized logins prevent cybercrimes. Businesses are constantly under the threat of these cyber attacks. 

Banks have security systems that alarm customers when suspicious activity is taking place. These unusual activities can include the withdrawal of massive amounts of money and repeatedly entering the wrong ATM pin.

Reliable Research Tools 

Many financial companies offer tools to enable fundamental and technical analysis. These tools help you predict price movements based on data from past behavior.  

You can assess the rate at which companies are growing and compare them side by side using Big Data. Day traders regularly refer to data points from the market to make profits and cut their losses. 

Automated Investment Strategies

A popular trend emerging in the financial services industry right now is the application of algorithms to get better returns on investments. Data-driven AI programs have made it possible to manage your portfolio on autopilot.  

Financial institutions track and mirror the performance of top companies. These automated investment strategies do not guarantee better results. It’s a financial trend that has managed to lure new and seasoned investors alike.

Challenges of Big Data in Finance  

While Big Data does elevate the services of financial companies, it does come with its fair share of challenges. 

Growing Costs of Innovation

Big Data requires a high-tech infrastructure. The high volume of data generated from companies is stored in warehouses. The cost of new servers to store that data can be expensive. There are also additional expenses such as the price of cooling systems and other maintenance costs. 

Financial companies usually pay a substantial fee to subscribe to Big Data services. But they may have to constantly upgrade their payment plans to keep up with the competition.

Unclear, Unstructured Data 

The explosion of data captured through personal digital devices is largely unstructured. The quality of the information collected from these sources can vary in value. Algorithms may not be able to interpret the information or churn out useful insights.

Finding relevant connections between unrelated data points can be tricky for financial institutions. There is always uncertainty when trying to determine the business value of the data. Furthermore, financial firms may have a tough time deciding which data to focus on and which one to ignore.

Stern Regulatory Restrictions 

The recent allegations of the privacy breach on personal data collected by mega companies like Facebook and Google have instigated governments to enforce tighter regulations on Big Data. Financial companies have to face similar heat for gathering information on customers and their behavioral patterns.

The General Data Protection Regulation and the California Consumer Privacy Act require companies to adhere to stringent data regulation laws. The function of these laws is to protect the personal information of people around the globe.   

Gain an Edge Over Your Competitors 

As a leading provider of AI-driven solutions, Yewno|Edge connects the unconnected. Yewno|Edge can derive deep data connections and deliver pragmatic strategies to enhance your investments.

Here’s a glimpse of what Yewno|Edge has to offer.

Build a Customized Stock Watchlist

Based on your financial goals, you can create a personalized watchlist to closely monitor your favorite stocks. You can quickly toggle various custom fields on the stock watchlist such as the volume, price, daily change, and fundamental data.

Strengthen Your Investment Strategies

You can transform ideas into investment opportunities with Yewno|Edge. The AI platform allows you to test your investment strategies and make improvements to your stock portfolio for better returns.   

Yewno’s Strategy Builder can take a theme or concept and transform it into a strategy in seconds. For example, a trending theme is to understand which company will succeed in the development of a successful vaccine to COVID-19. How can you know which company could be the winner without accessing thousands of articles, clinical trial research and more? Yewno can do that task in seconds. Below is an example of the latest vaccine stocks with the highest exposure. 

Manage Your Risk Profile

As with any investment, you want to increase the rewards and decrease the risks. Yewno’s cutting-edge AI filters millions of financial documents and news articles to clearly define the risks involved with your potential investments. A social media post can move markets. Understanding the correlations of these events linked to the stocks in your portfolio can be a hard task. Yewno’s Concept Exposure can allow you to discover hidden risks arising from the data that sometimes could go unnoticed.

Find the Documents Moving Markets

Yewno|Edge’s new Document Search feature gives users the ability to surface all published information about the companies and concepts they’re researching, all in one place.  Documents are published in both snippets and full text and include patents, news, official filings, clinical trials and transcripts. Yewno|Edge also publishes a shortlist of related concepts covered in each document so that the user can better understand its relevance to their original search and make unexpected connections. You can also extract trending concepts that are emerging from the documents. 

Data-Driven Insights that Impact Investments

You can get overwhelmed by amassing too much information, leading to inaction. The intuitive interface of Yewno|Edge can make it easier for you to ingest vast amounts of data and arrive at actionable insights. 

The advanced inference engine of Yewno|Edge detects and explains financial data along with its relationships over time. You can leverage these technology solutions to scale your stock portfolio. You can also trace these data connections back to its original source at any given point of time. 

Want to explore the investment possibilities first-hand with Yewno|Edge? Sign up for a free trial now.

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