How Artificial Intelligence Is Going To Change The Financial Industry

The use of artificial intelligence is increasing in many industries including the financial industry. At the heart of artificial intelligence is machine learning algorithm which is software that improves when it is given more data. There are a number of ways that the financial industry is looking to utilize this machine learning and it could change the way that the industry operates in the future.

Used For Fraud Detection

Fraud is something that has always been around, but online fraud is proving harder to fight. Financial institutes find that declining transactions too aggressively only leads to a loss of customers and billions in losses. This is where artificial intelligence will come in handy and is already being tested by major financial institutes.

Machine learning algorithms will be able to detect fraudulent transactions which would be overlooked by human analysts. This will improve the accuracy of transaction approvals and reduce the false declines that can happen. This will be achieved by these algorithms learning the patterns of transactions for each person and determining if the new transaction is in line with this. This is actually something that Mastercard is already looking at with the Decision Intelligence technology that it has launched.

Banking Chatbots

Over the years, chatbots which are powered by natural language processing and machine learning have become a powerful tool. They can offer a conversational and personalized experience to users in many different domains. In the financial industry, these chatbots could be used to help people manage their savings and money.

Plum is an example of this already in use as it is a chatbot that you can access via Facebook Messenger. The chatbot will help you save money in small bits. When you register, you will connect the AI to your bank account and it will analyze your account to see how much you can save.

Banks have also been looking at AI chatbots to improve their self-service interfaces. The Bank of America is looking to launch their AI chatbot Erica which will be accessible through the mobile app. The chatbot will help users make smarter and faster decisions. Users will also be able to command the chatbot to make payments for them.

Algorithmic Trading

Crunching numbers is something that computers have always been good at and which can easily be used in the financial industry. With the advances in machine learning, computers will now be able to take on the complexities and subtleties of tasks such as trading stocks and forex. There are a number of hedge funds who are looking into this and have some results from this.

Sentient Technologies runs a hedge fund and was able to develop a machine learning algorithm that ingests millions of data points. These data points will be used to determine trading patterns and create trend forecasts. The company was able to use this algorithm to fit 1800 days of trading into a few minutes and open up traders to other tasks. This could revolutionize the way that stocks and other trading are completed.

How to Use Technical Analysis to Support Day Trading

Technical analysis is a system of analysis techniques which can be used to trade stocks, shares, and currencies. Technical analysis is based on the idea that the markets follow trends and that those trends are quite predictable – that asset values will always move within specific bounds.

There are a few core rules to technical analysis, and once you understand those rules you can have a good chance of predicting how the markets will move. There will always be some differences. There will always be some exceptions, but these rules can support a lot of trades. Thanks to the Trading Review team, we were able to label the most important ones below.

Map The Long-Term Trends

Looking at long-term charts that show the asset you want to trade on a monthly or weekly scale, spanning several years, will give you a clear perspective of the market. Once you can see that long-term trend, look at daily and intra-day charts as well. Even if you are planning on trading short term, it’s easy to be deceived by the short-term trends. You need to have a view of the direction of the market longer term.

Support and Resistance

Buy when the market is close to support levels – these are usually a previous low. Sell near resistance, which is a previous peak. Typically, when a resistance level is broken, it becomes a new support level – old highs become new lows. When a support level is broken, it becomes a selling high for the next market rally. Understand that psychological impact, and you will have a better idea of when to take gains and stop losses.

Reading Retracements

Percentage retracements and market corrections give you an idea of the next market trend. Often, in corrections, retracements of around 50 percent are common. Minimum retracements will be around one-third of whatever the previous trend was. Sometimes, a retracement of two thirds will happen. The Fibonacci analysis retracements are 38% and 62% and are worth watching as well.

Oscillators Identify Markets

Tracking oscillators will show you if a market has been over-sold or over-bought. You can use moving averages to see if a market’s trend is changing, but oscillators offer an indication of whether a market is about to turn in direction soon. The RIS and Stochastics Oscillators are handy indicators. An RSI over 70 suggests a market is overbought, and an RSI below 30 suggests over-selling. With Stochastics, the figures are 80 and 20 respectively. Using a 14 day or 14-week trend for Stochastics, and a 9 to 14 day or week trend for RSI will give you a clear idea of the status of the market. You can use the signals as a filter for narrower charts.

Heed Warning Signs

You can combine moving average data with oscillators to generate something like the Moving Average Convergence Divergence indicator. This will give you buy and sell signals and will give an early warning sign of any potential trend change.

Technical analysis is useful for stable, established markets. Fundamentals can make a market buck the technical trends, but they are still useful to know.