How to Make Bank Transactions Safe

Money doesn’t like jokes or silly behavior. It gets real when Development Team takes the project with tasks like bank transactions. We at ChallengeSoft have experience with such assignments, and how easy it could be… in making trouble. 


That’s why this article has the safety of transactions as the main subject. We hope that after reading our article, you will be prepared for some issues and ready to make some effort for the bank transaction safety.

How Machine Learning Helps to Make Banking Safe

If we talk about the benefits of machine learning for coherent finances. It also contains fraud prevention. The fact is that the systems are constantly learning. In other words, the same fraudulent idea will not work twice. This is great for detecting credit card fraud in the banking industry. There are five financial cases where you should use machine learning:

The business now feels the need for artificial intelligence and machine learning as the world of financial services has entered an era. Machine learning in banking and finance is beginning to play a significant role in various processes, including loan approvals, stock forecasts, and fraud prevention.


More accessible machine learning tools, a variety of algorithms, and decent computing power will only increase the number of interactions between machine learning and bank transactions, so it’s time to catch up. 

What is the AI part in Safe Bank Transactions


Usually, financial transactions are carried out through online purchases or between businesses. This means that most fraudulent transactions also take place under the pretext of buying something.


Market Weakness: together with big data, machine learning allows not only to collect information but also to find specific samples, which allows performing functions of research and prediction. For example, you can predict currency fluctuations, identifies the best ideas for investing, credit risk (and find the middle ground between the lowest risks and the most appropriate credit for a particular user), examine competitors, and identify security vulnerabilities.


Costs Decline: Machine learning allows financial institutions to identify weaknesses in processes and more effectively organize the work of staff. The simplest example is chatbots that can successfully handle customer advice on simple and standard issues. Boots also do not require payment for their work! In addition to the fact that working with ML allows companies to reduce costs, it is logical that it also helps to increase profits by improving customer service.

Risks of Machine Learning in Bank Transaction


Thus, there are certain risks that can be encountered when setting up a banking transaction, but they are mainly related to the novelty of the technology and the lack of full understanding of users about how they actually work. Let’s consider them.

Changes of Job Offers: this is one of the most common risks and concerns associated with AI and machine learning, regardless of their scope. However, current research suggests that artificial intelligence in the banking sector will provide a much larger number of new jobs compared to the number of professions that will become unclaimed. 


The decline of the Trust: it is also thought that users will have less confidence in financial institutions due to fewer opportunities to work with human advisors. This is true, but only in part. Most likely, we will see this trend, but only in relation to people born in the previous generation, who are not too inclined to believe in technology, to begin with. But as for the generation of millennials who are willing to pay more for convenience and reliability, they will be happy to be able to perform any operation in a few clicks.


The Human Factory: it’s about ethical risks and false-positive result risks. They are associated with the fact that the amount of data that financial companies collect, store, organize, analyze, and use to their advantage (as well as for the benefit of customers) continues to grow. Machine learning systems and AI track user behavior patterns and compare them with accepted versions of the norm for each user.

ChallengeSofters about Bank Transaction Experience

Our CEO Kristina Husyatina got an experience with bank transactions. So we ask her some questions for you to sum up everything what we said about need and safety of the bank transaction.


Tell us about your experience with banking transactions. What exactly were you doing?

I have worked with the payment system on various projects. Their main task was one-time payments or subscripts. The main systems I worked with were Apple Pay, Stripe and Hyperwallet (from PayPal).


What did the customers insist on? What was the most important challenge for them?

The last challenge was the integration of Hyperwallet into an existing project. Hyperwallet was needed in order to enable European users to buy products and subscriptions. The Hyperwallet system required the collection and validation of additional user information.


What business would you recommend having a bank transaction?

I would recommend to any business that sells products or services. Now there are many options for payment systems, any business can choose which one suits them best.


Can you sum up your work as a professional?

Working with payment systems requires a lot of composure and analytical thinking, since any failures in the work of this system are the most critical for the client. Each product that is intended for the market of more than one country requires the integration of several payment systems, or one system with different settings, which would allow a user anywhere in the world to use this product without restrictions.


Integration of the second payment system into such as Hyperwallet, for example, enables users of European countries to successfully use all the paid product privileges or purchases. Since Stripe (one of the most popular payment systems these days) has limitations.