Artificial intelligence for identifying and preventing frauds

Financial industries have been using different algorithms for detecting fraudulent behaviour for a while. However, these have been operating with manual processes using pre-defined rules, which resulted in low accuracy and false positive or false negative outcomes. Machine learning also brought a great improvement potential in this activity among many others.

Financial institutions have stacked up a huge amount of data related to customers and transactions, which is the perfect playground for machine learning algorithms. This kind of artificial intelligence is able to recognise patterns in the given data and create rules on its own according to them. By tracking and analysing customer behaviour, a well-developed AI can detect anomalies with a high accuracy, so it can report possible fraudulent users and activities in real time.

Training must be carried out on data that describes customer steps and paths in detail, moreover this data must be categorized manually based on fraudulence for proper training. It can be made on two way (usually the combination of them is used): supervised and unsupervised learning.

While machine learning is a huge step forward in fraud detection, there is still room for improvement in the technology. Since such an algorithm is worth as much as the data behind it, as they develop in quality and quantity, the efficiency of systems like mentioned will increase significantly.

Automated customer service using speech recognition

You must have spent a few minutes waiting to contact a customer service representative. Usually, such telephone calls are made in urgent cases, so it is truly frustrating to wait, or if the customer may not be able to reach the customer service at all. An already spoilt customer experience can be further aggravated by an annoying wait melody or the frustrating questions before a human representative answers the phone. Many believe that this may be a thing of the past in the near future.

All bank executives are aware of the problems mentioned above, but there is no automated customer service available yet. Why? The answer lies in the complexity of such a system. The first step is to convert the caller's question/request into text. This will allow the information to be digitally processed. The subtitled text must then be interpreted by the machine using different NLP solutions. Since we are talking about completely free usage of the given language, this makes it difficult both to transcribe the speech and to interpret the written text. The next step is to choose the right answer to the customer's question, and then to inform him. If the task does not seem to be troublesome enough, let's think of the incredible speed needed for all of the things mentioned, as we want to replace real customer service assistants. Hopefully, the rapid development of AI technology will overcome these difficulties in the short term, and we will be able to easily solve our banking problems with automated customer service.

A speech recognition solution can not only improve customer experience and feedbacks, but can also give direct competitive advantage to the financial institutions utilizing the technology. By transcribing the communication with your customers, you can instantly analyze it. It is possible to determine the percentage of calls that were complaints, their contents or the proportion of calls that ended with positive feedback.

We may manage our finances through virtual assistants

Chatbots and virtual assistants can be found in many places in our everyday life and could even help us with our banking needs soon. In addition to basic operations such as checking our balance or initiating a transaction, it could also send personalized messages, alerts and promotional notifications using a specially designed chatbot. The client may be notified of unusual credit card charges, such as abnormal direct debits. The chatbot can also alert if the customer would run out of money by the end of the month expecting the same spending rate, and it could also provide specific suggestions in such a case. Conversely, if a client generates extra wealth at the end of the month, personalized saving plans could be offered to him.

As described above, there are many innovative ways to use a virtual assistant or chatbot in the financial sector. The potential of the technology is therefore worth recognizing and exploiting for all leaders in the sector.

Source: Fintechnews, Finextra, Netguru