Recent surveys show that 19% of companies established a data culture. This trend can’t go past FinTech — the collective concept of software connected to banking and finances as this industry is driven by numbers, data, and predictions. So, what will the introduction of artificial intelligence and machine learning bring to the industry?
What Is FinTech?
As mentioned before, FinTech is all software and technological solutions that in some way work with money and finances. Its goal is to make various operations with money more easily accessible, safer, or automated for both regular people and businesses of different scales. The examples of FinTech are:
home budgeting assistants
digital short-term loans
algorithms for credit and insurance scoring
FinTech reshapes traditional financial services and competes with them, providing faster and more nimble solutions. Most successful startups in this field aim to provide fresh solutions for old needs, like transferring small amounts of money between people, and subsequently stealing the audience from traditional financial institutions that satisfy those needs in old ways.
Artificial Intelligence and Machine Learning
Though they sound like two separate entities, one is actually a subdivision of another. Artificial intelligence is a sub-division of computer sciences that study algorithms that mimic the process of human thinking and are called to solve problems typically solved by people. Programs that fall under this category can utilize special methods to react to inputs, learn from previous experience, and make decisions. Examples of AI tech are voice assistants (Alexa, Siri, etc.), self-driving cars, and spam filters.
Machine Learning is one of AI’s programming approaches. Instead of designing a specific algorithm for each given task in ML, a program “learns” the correct way to solve it through many iterations of trial and error. One of ML implementations, neural networks, are widely used for such tasks as pattern recognition. This specific field is very useful for FinTech as noticing trends is crucial for risk assessment, stock trading, and more.
How FinTech Benefits from AI and ML
AI/ML solutions can replace routine human labor and make it much faster as well as mine large amounts of historic data for useful insights. Here is exactly how it’s going to improve FinTech solutions:
Time-saving: once a machine learns to do a human job, it can perform it multiple times faster.
Lowering operation costs: replacing human labor with computer programs saves lots of money that can be spent on R&D
Always available: machines don’t have sick leaves and lunch breaks; they are always here when needed.
Enhancing human workers: with the help of AI solutions, employees can do their work faster and better and come up with unorthodox decisions more often.
Improving customer experience: AI can analyze hundreds of thousands of app and web user interactions to find fields for improvement. Also, robotized customer support assistants can take over at night time or during busy hours.
Fraud protection: much like spam filters, fintech ML can find patterns that correspond with suspicious activity and alert managers or take actions on their own.
To see real cases of implementing such technologies, see this article: https://agilie.com/blog/ml-ai-and-fintech-how-maching-learning-and-artificial-intelligence-help-you-benefit.
FinTech Companies Using AI/ML
More FinTech companies turn to AI each year, and there are already some big names among them. They include Intel Capital (Intel’s venture capital division), Numerai hedge fund, Core Scientific blockchain hosting, Riskified anti-fraud solutions for e-commerce, and much more.
AI and ML are a logical development not just for FinTech but for IT as a whole. They help drastically reduce operational costs while giving each customer a better user experience through a personalized approach. If you want to find out more about the role of AI in FinTech, check this article: https://agilie.com/blog/ml-ai-and-fintech-how-maching-learning-and-artificial-intelligence-help-you-benefit.