The Match Made in Heaven: 9 Examples of Using AI in FinTech

Artificial intelligence has become omnipresent. It has penetrated into so many business fields that it's hard to say if any AI-free niches remain. AI has various practical applications in the fintech sector and throughout the financial world more generally. It solves problems, saves time, and earns money, so more and more businesses are choosing to use this universal tool for their benefit.

In most cases, artificial intelligence deals with data and helps companies to analyze large amounts of it quickly and inexpensively. But that’s not the only way it's used. There are also dozens of different applications and those are what our article is all about.

1. Credit risk assessment

Сredit scoring is an evaluation of how likely it is that a customer will repay a debt, and computers have proven to be the best assessors.

AI conclusions are based on various data sources that can include both conventional metrics (total income, credit history, etc.) and rather unexpected ones, like favorite locations or even an email provider.

An algorithm interprets all of this information and provides an accurate, individual credit score assessment.

The key benefit of the technology is an opportunity to exclude the human factor from decision-making, since human assessments can often be very subjective. It is also very useful in regions where banks and lenders can't access enough financial data about each single person.

A good example of using AI in FinTech is the project created by our client, Fido Solutions. They provide financial services in developing African and Asian Pacific countries where small lenders often can't build their credit histories in a traditional way. This is where AI comes in handy.

2. Detecting fraud

Most people act quite the same each time they access banking or other financial services.

These behavioral patterns can be monitored and analyzed by AI in order to catch actions that don't fit the user's normal behaviors. For example, if someone tries to apply for 10 identical loans in 5 minutes, a computer can mark this as a suspicious anomaly.

This is one of the most effective ways to detect fraudulent activity and saves people billions of dollars annually.

It's also worth noting that the analyzed data is anonymized and encrypted to protect users’ privacy.

Check out a related article:
State of Blockchain in 2023: Perception, Fundraising and Adoption

3. Increasing safety

What works for a single user can also be applied to an enterprise. Just as AI detects fraudulent activity related to your personal bank account, it can analyze the whole system to detect data leaks and breaches.

AI is applied in many novel authentication techniques—for example, face or fingerprint recognition.

There are so many ways that AI can be applied in FinTech security that the topic definitely requires a separate article. Luckily we have one! Check it out here.

4. Automated customer service

Customer service is another business function where AI solutions are as good as gold.

AI chatbots are widely used to quickly answer common customer questions, which improves users’ experience, reduces load on call centers, and saves tons of money.

Additionally, they can be set up to help users navigate a company's offerings and to utilize user data to provide recommendations or custom solutions, thus increasing sales.

5. Predictive analytics

Artificial intelligence can predict a users' intentions. For example, if a customer makes a single request for a statement of expenditures for the previous month, the AI predicts his next request based on his previous behavior and provides the required information in the same response. Thus, companies can minimize the number of server requests and the overall load on the system, while the customer gets a paramount user experience. It's a win-win solution.

6. Financial forecasts

Financial institutions often use AI to identify and analyze patterns in raw data. Technology has proven to be very effective even if the information is far from ideal, and it often does the job more effectively than a human analyst.

In FinTech, AI can provide valuable insights into the stock markets, exchange rates, investments, and predications about short- or long-term trends.

Moreover, AI’s ability to analyze unstructured data can be applied in many less obvious ways, such as predicting product/market fit and adjusting marketing tactics based on recent customer behavior.

7. Smart decision making and advising

By processing massive amounts of real-time information coming from both local and global markets, AI enables FinTech to make intelligent decisions. Financial advisers and analysts gain deeper insights into the whole industry. They can use these insights to make better recommendations about loans, insurance, and wealth management, thus improving their services and building trust.

Data collection and analysis with artificial intelligence also allows businesses to make proactive decisions by predicting future trends and acting accordingly.

8. Insurance management

The insurance industry would be impossible without accurate risk assessment. Companies can prepare complex customer profiles from various data points, uniting both financial and health risks. Using such profiles, they can offer customers optimal insurance packages. This kills two birds with one stone: offer a better user experience and minimize business risks at the same time.

An example of modern insurance solution can be another case of ours. We helped our client to build a comprehensive mobile app to help protect growers against shallow yield losses while retaining flexible insurance coverage that was clear, easy to use and understand, and fully tailored to their needs.

9. Wealth management advising

Many customers would like access to personalized wealth management advisory services, but since many FinTech companies in this field make their profits from commissions, offering such services to lower net worth customers is not advantageous for them. AI bridges this gap.

Businesses can apply AI and ML solutions to provide users with personalized financial advice based on their historical financial activity. This allows them to serve a greater number of customers without requiring more human resources.

Both users and companies benefit: users get quality advise at a decent cost, and businesses increase their profits by supporting more customers.

Check out a related article:
7 Fintech App Development Fields to Launch Your Business in 2022

How You Can Use AI in Fintech

There are dozens of ways you can apply this technology for your business based on your goals and specific needs—and they are not limited by the list above. The sky is pretty much the limit when it comes to using AI.

As a first step, you can utilize our FinTech app development and artificial intelligence development expertise and contact us to analyze your business and develop an optimal solution for your needs. Our 17+ years of experience and industry knowledge are always available to you.

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