How Financial Companies Use Big Data to Make Decisions
Emerging technologies such as artificial intelligence and machine learning are transforming financial companies. “Big Data” is at the heart of these innovations. It helps you find meaningful models that create value for your investments.
What is Big Data?
Every day, quintillions of bytes of data are captured from customers and their transactions. These heaps of unstructured information can add up and gain meaningful insight from all of this data which can be tedious and time consuming.
With the help of artificial intelligence (AI), you can quickly analyze data for relevant information in a fraction of the time. AI can identify potential patterns in data for business development and present the results in a clear and simple format. As a result, you and your business can make better business decisions in 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 behavior models, banks offer different types of financial services. These services can include credit cards, mortgages, auto loans, and personal loans.
Financial companies use big data to analyze investment options. These investments can include stocks, real estate and foreign currencies. Big Data plays an essential role in the management of the risk profile. Financial products are tailored to customer needs and improve returns.
Big data adoption
Source – IBM
“It’s important to remember that even the highest quality information doesn’t equate to knowledge. Investors can make decisions and act on the basis of knowledge – they cannot act on the basis of information, ”said Ruggero Gramatica, CEO of Yewno. “Big data can be extremely useful once applied, but it’s useless if you can’t put it together, process it and understand it. ”
Yewno | Edge is an investment research platform that takes hundreds of millions of constantly updated data points such as global patents, clinical trials, official filings, and news and uses artificial intelligence to associate these data points with tangible concepts such as companies, industries and investment trends. . He can build and back-test strategies, calculate exposure to concepts and assess indirect risks. It tames big data by turning information into knowledge.
Benefits of Big Data in finance
The digitization of financial services offers a wide variety of benefits to clients. Financial companies are leveraging big data to manage customer expectations and deliver personalized solutions. These benefits include the following.
Increase in customer satisfaction
By relying on data collected from customers, financial companies offer personalized investment solutions. Big Data can store financial information such as payment methods and product purchases. This can speed up transactions and save their customers valuable time.
By automating processes, big data can speed up workflows and streamline your business. Without big data, you will have to queue and fill out several forms by hand each time you want to register your request for the financial services you may need.
Hackers can steal invaluable customer information and sell it on the black market. Security measures such as fraud detection and unauthorized logins prevent cybercrime. Businesses are constantly under threat from these cyber attacks.
Banks have security systems that alert customers to suspicious activity. These unusual activities can include withdrawing huge sums 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 past behavior data.
You can assess the growth rate of companies and compare them side by side using big data. Day traders regularly refer to market data points to make profits and reduce losses.
Automated investment strategies
A popular emerging trend in the financial services industry right now is the application of algorithms to achieve better returns on investments. Data-driven AI programs have made it possible to manage your portfolio on autopilot.
Financial institutions track and reflect the performance of the best companies. These automated investment strategies do not guarantee better results. It is a financial trend that has been successful in attracting new and seasoned investors.
The challenges of Big Data in finance
While big data improves services for financial companies, it comes with its own set of challenges.
Rising costs of innovation
Big Data requires a high-tech infrastructure. The high volume of data generated by companies is stored in warehouses. The cost of new servers to store this data can be high. There are also additional expenses such as the price of cooling systems and other maintenance costs.
Financial companies typically pay a substantial fee to subscribe to big data services. But they may need to constantly upgrade their payment plans to keep up with the competition.
Unclear and unstructured data
The explosion in data captured via personal digital devices is largely unstructured. The quality of information collected from these sources may vary in value. Algorithms may not be able to interpret information or produce useful information.
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 data. Additionally, financial companies can struggle to decide which data to focus on and which to ignore.
Severe regulatory restrictions
Recent allegations of privacy breaches of personal data collected by mega-companies like Facebook and Google have prompted governments to enforce stricter Big Data regulations. Financial companies face a similar heat to collect information about customers and their behaviors.
General Data Protection Regulation and California Privacy Law require companies to follow strict data regulation laws. The function of these laws is to protect the personal information of people around the world.
Gain an advantage over your competition
As a leading provider of AI-powered solutions, Yewno | Edge connects the unconnected. Yewno | Edge can derive deep data connections and come up with pragmatic strategies to improve your investments.
Here’s a look at what Yewno | Edge has to offer.
Build a personalized inventory watch list
Based on your financial goals, you can create a personalized watch list to keep a close eye on your favorite stocks. You can quickly switch between various custom fields in the Stock Watchlist, such as volume, price, daily change, and fundamental data.
Strengthen your investment strategies
You can turn ideas into investment opportunities with Yewno | Edge. The AI platform allows you to test your investment strategies and improve your equity portfolio for better returns.
Yewno’s Strategy Builder can take a theme or concept and turn it into a strategy in seconds. For example, a trending theme is understanding which company will succeed in developing an effective vaccine against COVID-19. How do you know which company might be the winner without accessing thousands of articles, clinical trial research and more? Yewno can do this task in seconds. Below is an example of the last most exposed vaccine stocks.
Manage your risk profile
As with any investment, you want to increase the rewards and decrease the risk. Yewno’s cutting-edge AI filters millions of financial documents and news articles to clearly define the risks of your potential investments. A social media post can move the markets. Understanding the correlations of these events related to the stocks in your portfolio can be a difficult task. Yewno’s Conceptual Exposure can help you uncover hidden data risks that can sometimes go unnoticed.
Find the documents Markets in motion
Yewno | Edge’s new document search feature gives users the ability to bring up all the published information about the companies and concepts they are looking for, all in one place. The documents are published in both excerpts 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 research and make unexpected connections. You can also extract trending concepts that emerge from the documents.
Data-driven insights that impact investments
You can be overwhelmed by accumulating too much information, which leads to inaction. Yewno | Edge’s intuitive interface can make it easier for you to ingest large amounts of data and gain actionable insights.
Yewno | Edge’s advanced inference engine detects and explains financial data and its relationships over time. You can take advantage of these technological solutions to scale your equity portfolio. You can also trace these data connections back to their original source at any time.
Want to explore investment possibilities firsthand with Yewno | Edge? Sign up for a free trial now.
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