3 Tools How to Improve Artificial intelligence and Machine Learning in Financial Services

Written by: Becky Holton Financial organizations work with thousands or even millions of users all over the world. Their job is to handle and administer huge datasets in order to ensure quality customer experience and flawless functioning, which is by no means an easy task.In such circumstances, banks and other financial services have to utilize state of the art technologies just to keep pace with their competitors. Artificial Intelligence (AI) and machine learning are the latest trends in this field because they provide users with in-depth explanations of complex financial concepts.Our post will explain the purpose of AI and machine learning and discuss three ways they can improve financial services. Let’s take a look!

Machine Learning and AI: Definition and Benefits

Before we show you how AI and machine learning influence financial services, we need to define these two concepts. AIrepresents software technologies that make a computer or robot perform equal to or better than normal human computational ability in accuracy, capacity, and speed. To put it simply, AI is the ability of computers to simulate intelligent human behavior.On the other side, machine learningis an application of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. In other words, machine learning is the creation of self-taught computers.The two technologies bring companies a number of substantial benefits, with the crucial advantages being these:
  • Data mining : AI and machine learning have the power to draw meaningful conclusions out of seemingly unrelated datasets.
  • Real-time assistance : Intelligent programs are so fast that they can generate results in real-time.
  • Automation : They also automate most of the manual process and speed up the work of financial services.
  • Cost-efficiency : Automation makes manual work unnecessary, thus shrinking the number of employees and cutting operational costs.
  • Accuracy : Fewer employees also means that financial organizations make fewer mistakes.
  • Trend prediction : Smart machines can analyze the history of financial transactions and predict future trends, helping financial services to prepare in advance.
  • Practical Impact of AI and Machine Learning on Financial Services

    Now that you understand the concepts of AI and machine learning, it is easier to discuss the ways they impact financial operations. There are so many examples to consider here, but we want to narrow down the options and focus on three major features only. Without further ado, let’s check them out:

    1. Fraud prevention

    Administering massive data volumes forces banks, insurance companies, and similar services to pay special attention to security. The study shows that for every dollar of fraud, financial services companies incur $2.92 in costs.Besides that, data breaches can ruin the reputation of a financial organization, which is yet another reason to use advanced protection mechanisms. AI and machine learning are doing exactly that because they are able to analyze information in real-time and identify suspicious activities.This is possible thanks to the system’s potential to analyze everything from users’ locations and transactions all the way to vendors, withdrawals, and many other details. That way, new technologies can quickly detect fraudulent activities and send an early warning to protect financial services and their clients.Related: 5 Ways Virtual Financial Advisors Can Rank Organically

    2. Improve customer service

    Customer service is gradually becoming the most important segment of modern businesses. Almost half of the financial servicesbelieve that the improvement of customer service and experience is the best way to differentiate from their biggest competitors.With AI and machine learning at their disposal, banks and other financial institutions are able to explore every aspect of the consumer journey, detect pain points, and eliminate shortcomings. Furthermore, it is now possible to personalize customer experience and tailor offers so as to match the requirements of each client individually.Once again, these two systems are designed so as to analyze the entire history of interactions with a specific customer, so you can customize a product to make it perfect for any given client at any given moment.

    3. Simplify content creation

    Content creation is usually considered to be a part of digital marketing, but the truth is that financial services also require a fair share of quality content. What makes smart machines even more useful here is the fact that finance-related content is often repetitive and administrative.In other words, writing programs don’t have to exercise extreme creativity in order to get the job done properly. There are tons of amazing content creation and dissertation editingagencies out there such as Easy Essaysor Custom Essay Service, but they all praise the power of AI and believe it could become the future of finance-focused content writing.


    New technologies influence pretty much every aspect of our daily lives and businesses, so it’s not surprising to see them penetrating the financial services market as well. In this article, we defined the concepts of AI and machine learning and discussed three ways these two features improved financial operations. We tried to focus on the basic aspects exclusively, so feel free to leave a comment if you have other questions about this exciting topic – we would be glad to answer you!