Today, artificial intelligence can process an application form in 5 seconds. It is useful in a changing banking sector. This technology has a lot to contribute to one of the oldest professions in the world. To better meet the expectations of its customers and keep them. Thus, enabling them to remain competitive in the face of many fin techs. Could AI in fintech be a game-changer?
AI and the banking sector
Personal finance
Let’s take a look at a simple element that everyone has become accustomed to these days: chatbots. Chatbots help in the personal online spaces of bank customers. They allow users to provide simple, rapid, and useful information.
Interest is the chatbot functionality integrated into a connected personal space of banks. Allowing for personalized finance. Chatbots offer more complex services such as investment opportunities. Including advice in savings management and investment management.
Customer service
In customer relations, AI will play a key role. it allows banks to have detailed information available on each of the customers. thus allowing them to improve their expertise to respond to different expectations. AI makes it easy to bring customers close to their banks by offering them great services.
Fraud detection
Thanks to Artificial Intelligence technologies, and in particular through Machine Learning. It is now possible to detect fraud. This is the case with the algorithms developed by the Monzo bank (United Kingdom). They were thus able to detect cases of fraud on prepaid bank cards and reduce the number of frauds from 1% to 0.1%. In other words, almost no more card fraud!
AI and the processing of routine tasks
The goal of using AI is to automate routine tasks and then help to relieve employees of heavy tasks. To let them concentrate on missions with higher added value. Both for the employer and for the employee. Today we can see AIs making it possible to record accounting entries. Including writing analysis reports, and process financial transactions. This helps to generate productivity and efficiency gains.
Artificial Intelligence and Trading
Quantitative trading
Quantitative management could possible through Artificial Intelligence. It was then that the Robots Advisers were born. They thus allow online management of portfolios of financial assets. All with minimal human intervention in the process.
Based on quantitative trading, we have been dealing with High-Frequency Trading for years. Some use AI (especially Machine Learning). Which allows them to analyze and make stock price predictions. This provides real help on asset buying and selling decisions.
Help with decision-making
AI is also used with a view to optimizing investment decisions by decision-makers. Let us illustrate our remarks with the case of Goldman Sachs. The AI they developed enabled Goldman Sachs to create their famous “sentiment” score.
Another decision support tool that can be very useful is textual analysis. AIs will analyze various types of data other than raw digital data. Like financial information, legal news, and economic and political news. Publications on social networks Inclusive. This is Possible using NLP (Natural Language Processing). NLP means that AIs will be able to read and analyze human language. This analysis makes it possible to know the state of the market and to make investment decisions.
Conclusion
AI shifts the work of understanding the context of technology by reducing errors. Including accelerating the speed of responses and customer satisfaction. the AI is there to assist in decision-making. By identifying any inaccuracies, the risks of fraud. By optimizing the ratio between profits, profitability, and customer satisfaction. AI is without a doubt, a game-changer in fintech.
