Across the financial industry, a vast amount of technology is utilized to enhance the speed and accuracy of transactions in securities trading, banking, risk management, and other areas. Most of this technology is designed primarily for back-office use by financial firms themselves. However, some crucial exceptions apply directly to consumers.
This article examines five major technologies that are transforming the financial industry today and should be considered by any investor or trader seeking success.
Mobile Devices and Smart Phones
With the proliferation of smartphones and tablets, mobile computing has become a necessity for anyone seeking to stay current with financial markets. For example, anyone who trades stocks or options must have immediate access to real-time stock quotes at all times.
Traders can no longer wait until they get home to check market prices on their computers. Stock quotes from online sources may be delayed by up to 30 minutes or more. Smartphones can deliver quotes instantly with a market analysis that may even include real-time news reports and commentary from experts like Jim Cramer.
Blockchain Technology
Blockchain technology is a relatively new, yet rapidly growing, technology within the financial industry that enables individuals and groups to transfer money quickly, securely, and more cost-effectively than through a third party. Financial institutions worldwide are increasingly investing in blockchain technology. They see it as the next step in delivering personalized and efficient banking services to their customers.
It is based on decentralized methods and information storage, thereby eliminating the need for a central authority to facilitate transactions. By utilizing decentralized systems, transactions can be processed more efficiently, with lower costs and enhanced security.
For example, a bank may leverage blockchain to allow companies to pay employees their wages automatically or to provide their customers with refunds. Blockchain can be used to protect sensitive information. By storing all transactions in an unfalsifiable manner, blockchain ensures the accuracy and permanence of data.
Blockchain is a shared ledger that maintains a continuously growing list of ordered records called blocks.
Rather than relying on a single central authority to control the entire network, blockchain technologies utilize encryption, digital signatures, and other security methods that enable multiple parties within a network to share access.
This provides a secure way to keep records, offering the financial industry a reliable solution for accurate data management.
Machine Learning and Predictive Analytics
Machine learning and predictive analytics are the key ingredients for success in financial markets. They provide an opportunity to develop new products and services and help to understand the behavior of customers, competitors, and partners. They allow you to get ahead of your competitors, to increase profitability, and gain market share.
Doing business successfully in today’s world means being a data-driven enterprise. This requires the collection, analysis, and proper interpretation of customer and operational data. Machine learning can help you effectively process this information and make better decisions more quickly.
Implementation of machine learning algorithms, evaluating their performance, and tuning parameters to achieve better analytics are ways to solve challenging financial data problems. This reduces manual labor and saves money in the long run.
Machine learning can also be utilized for fraud detection, risk management, and compliance purposes. It involves the ongoing review of transaction and behavioral data that is analyzed to detect signs of fraudulent activity. Detection may include links between transactions and accounts, unexplained changes in account balances, and/or behavior that falls outside typical patterns.
Cloud Computing for Financial Industry
There are many benefits of using cloud computing for the financial industry:
- Reduction of IT costs – with cloud computing, IT costs can be reduced because there’s no need to purchase servers, which are then maintained by in-house IT personnel. All support is done by the cloud provider, resulting in a reduction of costs related to maintaining infrastructure, hiring new staff, or outsourcing support services to vendors like IBM or HP.
- Improved security – Security is of paramount importance in the financial industry since it deals with client confidential information. In a traditional client/server architecture, all data is stored on the server side. This means that any user with access to the network can access all the data stored on the server, without restrictions. In contrast, in cloud computing, users only have access to their own data. This enhances security by protecting confidential information from being inadvertently or intentionally disclosed to unauthorized third parties.
- Built-in high availability and disaster recovery – It is essential to have backup plans in place in the event of a disaster, allowing for quick data recovery. Cloud computing enables users to access their information from anywhere with internet access without having to rely on traditional storage devices. In addition to having backup plans, it is equally important to test those plans regularly so you are familiar with how to use them when you need them most.
- Quick and easy provisioning of resources – If you need more resources, you can quickly scale up and then shut down those extra servers when they are no longer required. The provider takes care of maintenance so you don’t have to devote in-house staff to it. It offers a wide range of choices for your cloud provider in terms of location and server type, allowing you to optimize for both performance and cost.
Big Data and Data Warehousing
Big Data is a term that refers to data that is too large to manage using conventional database systems. The amount of data has increased significantly over the past decade due to several factors, including the Internet, smartphone usage, and social media.
Big Data can help financial firms make better decisions by integrating predictive analytics, text mining, or social network analysis into their business processes. Data warehouses are used to store data and ensure its integrity, as well as to implement decision support systems, reporting applications, and web portals.
