AI is one of the most exciting technologies currently attracting many headlines due to recent developments and innovations. This branch of computer science aims to create programs capable of understanding data and carrying out human tasks. As such, it has a lot of potential applications in just about any industry.
It can help make businesses more efficient, removing a lot of tedious jobs and improving processes through automation.
AI has the potential to revolutionise the world, and many industries are already being affected. However, few industries are utilising AI as much as the financial services industry. In the financial industry, AI can be used to make finance more accessible while also making companies more efficient and profitable. Here are just a few ways that AI technology is currently transforming financial services.
Algorithmic trading uses AI and computer programs to execute trades on financial markets. Trading on the stock market is done every day, and the majority of trades are carried out by people. However, a growing number of trades are made each day by algorithmically trained bots and computer programs, which have been set up to profit from the market.
You can learn more about this practice and how it works with an algorithmic trading online program. Put simply, the process can be broken down into several stages. It begins with collecting data from financial markets and using this to train a computer program. Data on price, volume, and trading activity are all used to identify patterns and predict future movements.
Aside from collecting and analysing data, more complex algorithmic trading programs can also manage risk based on a complex set of rules, many of which are created based on data. If the AI is programmed to do so, it will also execute trades by sending buy or sell orders to an exchange, making the process much faster and more efficient.
Algorithmic trading essentially uses past market data to predict what might happen in the future. This type of model can also be used in other areas of finance, including insurance, forecasting, risk management, and loan applications. Generally, a machine learning algorithm is developed, which allows the program to learn and improve without being programmed.
Several different types of machine learning algorithms are used to predict outcomes in finance. Different learning models have their own advantages and disadvantages and may be better suited to particular tasks. Supervised learning algorithms are what’s commonly used in algorithmic trading. However, unsupervised learning models can potentially be used for fraud detection or loan application approvals.
The difference between supervised and unsupervised machine learning models is that supervised models use labelled data sets. On the other hand, an unsupervised model will analyse clusters of unlabelled data. For example, this could be used to analyse customer purchases and detect potential outliers that could be caused by fraudulent payments.
Improved Customer Service
Customer service is another major aspect of the financial services industry that AI can change. Financial services companies rely on great customer service, as this helps to gain customer’s trust.
Although many customers prefer to speak to a human advisor, AI customer service can save time and costs while still delivering high customer satisfaction. AI chatbots have become commonly used, but these should be used in conjunction with real advisors to ensure that customer questions are answered satisfactorily.
New developments in AI have also created natural language processing tools, which are far better at understanding and responding to customer requests. While these can’t replace human customer service agents yet, they do a good job of supplementing them and improving the overall support that customers can receive.