We have reached a new era where automation has become the name of the game, and when it comes to automation, Machine Learning (ML) is a key technology to understand.
Machine learning use has spread in several aspects of our lives today. It helps us get from point A to point B, suggests what to do with pressing issues, and is getting better at holding conversations. Is no surprise that in the world of finance we keep hearing about the combination of FinTech and machine learning. Applications of artificial intelligence (AI) in FinTech are predicted to be worth up to $7,305.6 million by 2022.
Machine learning algorithms are a great tool for pattern identification. They are able to detect correlations among copious amounts of sequences and events, extracting valuable information that’s hidden among vast data sets. Such patterns are often missed or simply can’t physically be detected by humans and our limited senses. The ability of ML to learn and predict enables FinTech providers to recognize new business opportunities and work out strategies that actually make sense.
Let’s take a look at some of the practical uses of ML in Finance and FinTech.
More loan approvals with lower risks
ML allows lenders to find patterns in a client’s credit history and financial behaviors with a high degree of accuracy and attention to detail. It allows financial institutions to see beyond credit scores in order to increase portfolio in a responsible way.
Keeps hackers and thieves away
Using machine learning techniques, FinTech providers can label historical data as fraudulent or not fraudulent. By running ML algorithms, the system will learn to recognize activity that looks suspicious. ML models can detect unusual activity, for instance in the course of an online transaction, with little to no effort.
Helps you keep up with compliance
Finance sector is always hit with new regulations constantly. Focusing on regulatory issues in FinTech and banking requires lots of resources. Even so, this investment can’t guarantee that all new rules are followed in a timely manner. AI and ML finance cloud platforms can automatically track and monitor regulatory changes as they appear, ensuring customer transactions comply with regulatory requirements.
Enhanced customer experience
The main reason people look for FinTech solutions is to avoid the often dense and slow practices of traditional financial institutions, since they need a swift, almost immediate response. With machine learning’s ability to look into petabytes of data to find out exactly what matters to a particular customer, financial institutions can create personalized offers and predict individual preferences. This way, companies can know what services or offerings a particular client is likely to appreciate.
As you can see, ML is not something from the future, it’s right here and right now. If you are looking for ML solutions for your business, we can help you out. Let’s have a talk!