Information technology trends in the financial sector in the last five years.

Information technology trends in the financial sector in the last 5 years

Meeting with existing and potential customers in the credit, banking and insurance spheres, I was inspired to share the opportunities offered by modern information technologies for the financial sector. Most of the article will be devoted to Artificial Intelligence technologies, which are gaining more and more popularity in recent years.

Credit risk assessment of individuals with Machine Learning

One of the most important processes affecting any business, especially in the financial sector, is data analysis. If in the past data was used to analyze results, then in recent years more and more companies are analyzing data to make predictions, which nowadays can be done quite accurately thanks to the possibilities of machine learning and predictive analytics.

Credit risk assessment is a complex process that can be made easier with Microsoft Azure Machine Learning. For example, you can get data about the applicant who submitted an application from the application database and based on the obtained data, create and train a prediction model (Predictive model) and deploy it as a web service in the Microsoft Azure environment. Predictive Analytics can help evaluate loan applications and grant loans only to those borrowers who meet certain criteria. In this way, the credit evaluation process can be partially automated and the application processing time can be significantly reduced.


The use of artificial intelligence in customer service is becoming more and more popular. Artificial intelligence consists of three technologies: machine learning (Machine Learning), natural language processing (natural language processing) and cognitive computing (cognitive computing).

Chatbots are one of the trends in banking in recent years. Artificial intelligence chatbots can in most cases replace a customer service specialist who, for example, answers questions asked by customers on the company’s website, providing prompt customer support around the clock. When a chatbot is newly implemented in a company, it cannot completely replace a customer service specialist, it can answer general and standardized questions. Using this technology in customer service, it is possible to automate such actions as: customer identification, greeting, saying goodbye, accepting orders, general phrases, answers to frequently asked questions, making payments, accepting problem questions, etc. However, over time, the chatbot, communicating with the customer, acquiring more and more information, “learns” (Machine Learning) and is able to answer more and more complex customer questions, thus there is less and less need to burden customer service specialists.

Customer service specialists have more time available to deal with more complicated customer problem situations. In this way, the company can reduce costs, optimize customer service processes and ensure prompt and continuous customer service according to high quality standards.

Virtual assistants, voice recognition

E-commerce platforms are introducing virtual assistants that use voice recognition technology. Voice recognition technologies are another way consumers can buy goods, services and use online banking. A buyer can simply tell a machine connected to a virtual device (such as the microphone of a mobile phone or PC) what he/she wants to buy, in what quantity and when to receive it. In this way, you can place an order in an online store using a mobile phone and pay, for example, while driving a car, without having to use your hands to enter text in the order form.

One of the examples where a chatbot can be used is, for example, to automate online visit bookings. The customer opens the company’s website, writes in the chat window or says verbally the desired visit date and time for the consultation, and the chatbot or virtual assistant checks the possible times and space in the customer consultant’s digital calendar and confirms the customer’s preferred visit time or offers another time if the chosen time is not available, and registers this visit in the customer consultant’s calendar, about which the customer consultant receives a notification by e-mail or sms or in another way.

Biometric authentication

Bank customers around the world are increasingly using mobile banking (mobile application) to make transfers. Using biometric authentication, you can, for example, log in to your account in the application.

HSBC Bank in China offers its customers a mobile application where they can log in using facial recognition and even make transfers of up to 50,000 RMB per day (that’s about 6,350 Euros). To make a transfer, the customer must open the camera in self-portrait mode and the application checks the customer’s identity by comparing the image on the camera with the photo stored in the bank’s customer database. Face recognition authentication methods have been used for decades, but only in recent years have they evolved struggle with face scanning also in many points of sale for goods and services, by scanning the face, when a photo match is found with a photo ID stored in the system database, the customer only needs to enter a phone number to confirm the payment. It should be mentioned that facial recognition technology is developing and widely used in China, which is why the Chinese government launched a project in 2015 to create a facial recognition database of Chinese citizens to be able to recognize any Chinese citizen in a few seconds.

On the other hand, Bank of America, in order to authenticate in the bank’s mobile application, offered its customers the opportunity to log in by taking a photo of the iris of the eye. The Australia and New Zealand Banking Group (ANZ) mobile application allows you to log in and make transfers with Voice ID. Voice ID in the ANZ app can be used to make BPAY payments above AU$10,000.

Several companies use solutions based on Microsoft Azure Cognitive Services, applying Microsoft Object and Face Recognition.

This article was an introduction to some of the technologies that are gaining more and more popularity in recent years (the article was written in 2017).

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