Across the financial industry, an enormous amount of technology is used to improve 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, there are some important exceptions that apply directly to consumers.
This article examines 5 major technologies that are changing the financial industry today and should also be considered by any investor or trader who wants to be successful.
Mobile Devices and Smart Phones
With the explosion of smartphones and tablets, mobile computing has become a necessity for anyone who wants 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 as much as 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 is a relatively new, but quickly growing technology within the financial industry that allows individuals and groups to transfer money quickly, more securely, and more cheaply than it could through a third party. Financial institutions across the globe 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, so it removes the need for a central authority to facilitate transactions. By using decentralized systems, transactions can be processed more quickly, with lower costs and increased security.
For example, a bank may leverage blockchain to allow companies to automatically pay employees their wages or for providing 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 having to rely on one central authority to control the entire network, blockchain technologies use encryption, digital signatures, and other security methods that allow multiple parties in a network to share access. This provides a secure way to keep records, giving financial industry a deal 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 customer and operations data collection, analysis and proper interpretation. Machine learning can help you to effectively process this information and make better decisions faster.
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 used for fraud detection, risk management and compliance. 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 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 financial industry since it deals with client confidential information. In a traditional client/server architecture, all data are 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 improves security by protecting confidential information from being accidentally or intentionally exposed to unauthorized third parties.
- Built-in high availability and disaster recovery – It is important to have backup plans in place when a disaster occurs so that you will be able to recover your data quickly. Cloud computing allows users to access their information from anywhere with internet 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, then shut down those extra servers when they are not needed. The provider takes care of maintenance so you don’t have to devote in-house staff to it. And it offers a lot of choice for your cloud provider in terms of location and type of server, so that you can optimize for 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 grown in the past decade due to several factors like the Internet, smart phone 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, and also to implement decision support systems, reporting applications, and web portals.