How is AI used in fintech, and how does it affect its progress
With fintech companies using AI for anything from automation to customer service improvements, it can be foolish to miss out on the opportunity to add it to your own business.
7 September, 2022
Today, fintech and artificial intelligence go hand in hand to provide users with the financial services innovation they have so desperately needed for a long time. Since fintech literally means technology-driven products in the financial sector, what better to use to stimulate its progress than one of the most technologically advanced practices of the present, i.e., artificial intelligence? However, exactly how is AI used in fintech to foster the desired innovation, and where is fintech going after it has taken the most out of it?
With fintech companies using AI for anything from automation to customer service improvements, it can be foolish to miss out on the opportunity to add it to your own business. Check out our latest ideas for fintech startups if you’re not sure which product to develop. Don’t forget another important aspect of your project’s success is fintech design that will make your digital solutions more user-oriented.
Brief AI fintech market overview and examples of AI technologies
In Fintech, artificial intelligence is not a new occurrence. It’s what basically started a myriad of innovative products in the financial sector. Today, its market share in fintech totals to over 12 billion US dollars in 2022, which is around 9% of the total AI global market and is expected to grow four times in the next decade.
AI for Fintech has brought many benefits, mainly from a productivity standpoint. For example, data entry speed and accuracy have improved up to 80%. The effectiveness of artificial intelligence caused a few industries to intermingle in order to produce better results, for instance, InsurTech (insurance+technology) and RegTech (regulations+technology).
No wonder more than a third of all financial services companies has recently adopted AI. As an example of AI technologies, let’s look at a few prominent AI fintech startups. A Singapore-based company called Active.Ai develops advanced AI-powered chatbots and provides custom solutions for banking, insurance, and capital markets.
Then there’s Token Metrics - a platform for cryptocurrency analysis, trending, and investments from Texas, USA. Another startup that merges Fintech and AI, Axyon AI, is an Italian investment management solution that automates asset management and trading. And lastly, Kreditech, a German startup that deals with AI-powered credit score calculations.
How is AI used in fintech
One of the most popular fintech AI use cases is virtual bots and advisors. They can not only answer various client inquiries any time of day or night but also guide users through different financial operations or solve minor problems. Another use case is automated compliance software, or RegTech, made to help with regulatory compliance-based paperwork thanks to Natural language processing.
AI fintech companies also create churn prediction solutions that analyze user behavior and use the gathered data to help businesses better keep their loyal customers. They can predict a change in preferences or spot if a customer begins to experience dissatisfaction with service quality and then offer advice to remedy these issues.
How is AI used in banking
Thanks to AI, digital banks are now much safer, and it’s all because of the additional identification features, such as fingerprint scanners or face recognition. Artificial intelligence has also made possible customer behavior predictions for two main purposes - either to deliver more personalized experiences and solutions or detect if a customer is making purchases outside their usual spending patterns, i.e., to predict possible fraud.
By the same token, banks use AI to assess if someone is creditworthy. AI-gathered and evaluated data lets them charge their clients correctly based on people’s credit scores and behavior patterns, for example, not overcharging their dependable clientele. Whether with fraud or credit scores, anomaly detection is the primary way AI is used in banking.
AI for fintech crypto
Just like AI fintech, crypto has been one of the latest catalysts of industry growth. Thanks to blockchain technology and its decentralized data storage, the financial sector currently experiences more transparency and better access to financial markets. AI has introduced more data processing power and task automation.
Together, they bring a new level of data security and augmentation. They can both be used to facilitate safer multiparty transactions while also enhancing their speed. Take loans, for example. If the applicant’s personal data is stored on the blockchain (i.e., not owned or managed by one system), it will be more secure, while AI handles the approval automation. All in all, it will lead to a better customer experience.
Benefits of AI for fintech
When we discussed how is AI used in financial services in the previous chapter, we covered the most essential benefits. Let’s see what else AI fintech has to offer.
- Improved decision-making. How well-informed you are about a particular issue or a situation determines the quality of your decisions. Yet, only AI can bring such data processing and analysis levels in current data-heavy business environments.
- Automation. You can also use artificial intelligence-powered solutions to automate and streamline your internal business processes - from alleviating repetitive yet error-prone tasks to managing documentation more accurately.
- Lesser user support costs. With AI, there’s no need to hire multiple people to address routine customer needs or consult them on any of the user issues. Combined with machine learning, AI is available 24/7 for any support clients may need.
- Financial predictions. No matter how raw, fickle, unstructured, or massive data is, the AI’s ability to analyze it is unparalleled. For finances, it means correct predictions and insights about strategies, investments, trends, exchange rates, etc.
- User behavior analysis. Predicting use behavior is not only helpful in detecting possible fraud but is also used to boost engagement and offer more tailored solutions. The predictive analysis feature mainly keeps track of user preferences and patterns.
What’s next for AI in fintech, and how can you use it to your benefit?
Despite the AI fintech solutions galore, they have yet to tap into the true potential of artificial intelligence. When we fix the gap between unrealistic expectations and AI implementation mastery, in just a few years, we will be able to see widespread smart adoption of all the range AI has to offer by a new generation of artificial intelligence fintech companies.
The most popular notion of what will come next for AI in fintech is more industry coverage. AI will seep into and cross over more and more areas of the financial market, especially those directly handling massive amounts of data, such as fintech cyber defense, credit scoring, data mining, and internal process control and optimization.
Ultimately, Fintech AI companies are here to stay, and you can easily be one of them. Use this article as a little nudge in the right direction and think about developing a fintech application that either wholly or partially utilizes artificial intelligence. Whatever you decide, Merge can help you with it!
