Posted Aug 18, 2022

In Business Analytics, Business Intelligence, Data Science, General, Performance Management


Read time 3 mins

Fintech companies are turning to artificial intelligence (AI) and machine learning (ML) to help them automate various tasks and processes. By doing so, they are able to improve their efficiency and accuracy while also reducing costs.

Here are seven ways AI and Machine Learning are infiltrating the FinTech industry:

  1. Security & Fraud Detection

The banking and financial sector is one of the most regulated industries in the world. Financial institutions have to comply with a plethora of rules and regulations imposed by various government agencies. With the increasing number of cyberattacks, the need for robust security measures has become even more important. 

AI and machine learning can be used to detect fraudulent activities and prevent them from happening in the first place. These technologies can be used to identify patterns in data that may indicate fraudulent activity. By using AI and ML, financial institutions can develop more effective fraud detection and prevention systems.

  1. AI-Driven Chatbots 

One of the most visible applications of AI in the financial sector is the use of chatbots. Chatbots are computer programs that simulate human conversation. They can be used to provide customer support, answer questions, and even sell products and services.

Many financial institutions are now using chatbots to interact with their customers. These chatbots can be used to provide information about products and services, answer customer queries, and even process transactions.

  1. Real-Time Decision Making

AI and machine learning can help financial institutions to make better and faster decisions by analyzing large data sets in real-time. This can help to improve customer service and to make better decisions about lending, investments, and other financial products and services.

  1. Accurate Credit Score

AI and machine learning can help to improve the accuracy of credit scoring by analyzing a wide range of data sources. This can help financial institutions to make better decisions about who to lend to and at what interest rates.

  1. Predictive Analytics

Predictive analytics is a type of AI that can be used to analyze past data to make predictions about future events. This can be used in financial services to predict customer behaviour, identify trends, and make better decisions about products and services.

  1. Personalization

AI and machine learning can be used to personalize financial products and services for individual customers. This can include providing personalized recommendations, tailoring products and services to meet specific needs, and providing a more personalized customer experience.

  1. Improved Asset Management

AI and machine learning can help financial institutions to better manage their assets by analyzing data to identify trends and correlations. This can help to make better decisions about where to invest, how to allocate assets, and what risks to take.


Fintech companies are using AI and machine learning to automate various financial tasks, including customer service, fraud detection, and investment management. This technology is helping these companies to improve efficiency and accuracy, while reducing costs. In the future, AI and machine learning are expected to play an even bigger role in the financial sector, as more and more companies adopt these technologies.

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