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Fintech AI explained - 2023 Updates

Marketing in Fintech

When it comes to financial technology (fintech) and artificial intelligence (AI), it's important to understand that these two industries are closely intertwined. Fintech is revolutionizing the way we handle our finances, and AI is playing a big role in making that happen.

First, defining fintech & AI

First, let's define fintech. It's an umbrella term that refers to any technology-enabled financial service. This can include things like mobile banking apps, online lending platforms, and even virtual reality-based financial planning tools. Essentially, fintech is any technology that is making it easier for people to manage their money.

Now, let's talk about AI. AI is a branch of computer science that deals with creating machines and systems that can "think" and "learn" like humans. This can include things like natural language processing (NLP), which allows computers to understand and respond to human speech, and machine learning (ML), which allows computers to learn from data and improve their performance over time.

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AI used in Fintech

When it comes to fintech, AI is being used in a variety of ways. For example, AI-powered chatbots are being used to provide customer service on banking apps. Machine learning algorithms are being used to detect fraudulent transactions. And natural language processing is being used to help financial advisors understand their clients' needs and offer personalized investment advice.

Software that uses AI

One of the biggest benefits of using AI in fintech is that it can help to automate many of the manual tasks that are currently done by humans. This can save time and money, while also reducing the risk of errors. Additionally, AI-powered systems can often make more accurate decisions than humans, which can help to minimize risk and increase efficiency.

Another advantage of using AI in fintech is that it can help to personalize financial services. For example, a robo-adviser can use machine learning algorithms to understand a person's risk tolerance and investment goals, and then offer personalized investment advice. Similarly, a chatbot can use natural language processing to understand a customer's question and provide a relevant answer.

Use cases - Fintechs

Here are a few examples of Fintechs using AI.

1. Wealthfront - Financial Reporting

With 440,000 members and $25 billion in assets under management, Wealthfront is one of the top robot advisors in the market. The minimum account requirement is only $500, offering many investing possibilities, including cryptocurrency. It also has relatively cheap costs, with most accounts paying just 0.25% and no transaction fees. Since UBS bought Wealthfront at the beginning of 2022, the company is anticipated to grow even more quickly. (

2. Kasisto - Automating Customer Experiences

AI allows you to adopt a set of AI-powered digital assistants trained to emulate your best bankers. They host human-like conversations, typically matching and often exceeding live agent performance. (

3. Accountable - Accounting

Accountable is a smart mobile app for freelancers that calculates your taxes in real-time, gives you the recommendations you need, and guarantees your peace of mind. It uses different types of AI to make the experience with the app as simple as possible. (

4. KBC Bank - Chatbot (Kate)

Since the end of November 2020, private KBC customers can use Kate. Kate helps to arrange a payment, tells if the salary has been deposited, and can show the car insurance certificate. Kate works both via chat and via speech. The assistant also offers "proactive services", for example, advice on how to save on the energy bill. If there was a storm nearby, Kate will ask if there was any damage and help to file a claim. (

Thirty percent of the conversations (703,000) effectively led to further actions. (

These are just a few examples of the many companies using AI in fintech. As the technology continues to advance, we can expect to see even more companies leveraging AI to improve their products and services.

It's not magic

However, it's important to note that AI is not a magic solution for all fintech problems. There are several challenges that need to be overcome when using AI in fintech. One of the biggest challenges is data privacy and security. Financial institutions need to be able to ensure that the data they collect and use for AI systems is protected from unauthorized access and hacking. Additionally, there are concerns about the potential for AI systems to make biased decisions, particularly when it comes to things like lending and credit scoring.

Image Credit: Arkadiusz Warguia/Getty Images

Another challenge is the lack of understanding and trust in AI among consumers. Many people may not fully understand how AI works, and may be hesitant to trust it with their financial information. This is why it's important for fintech companies to educate their customers about the benefits and limitations of AI, and to be transparent about how they are using it.


In conclusion, AI is a powerful tool that is being used in many ways to revolutionize the fintech industry. It can automate manual tasks, personalize financial services, and improve decision-making. However, there are also challenges that need to be addressed, including data privacy and security, bias, and consumer trust. At VisualVisions, we work with fintech companies to help them harness the power of AI in a way that is safe, secure, and beneficial for their customers.

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