The COVID-19 pandemic increased the pace of digital transformation in all industries, with the financial services industry being on top. The growing use of fintech apps proves the significance of digital transformation in the domain of finance. With the power of technologies such as blockchain, cloud computing, and AI, fintech has changed the traditional perspectives on finance. AI and fintech can shape the future of the financial industry with innovation.
Therefore, the applications of AI in fintech have attracted the attention of big players and startups offering financial services. Interestingly, around 90% of fintech companies use AI in some form. What are the different ways in which fintech companies can use artificial intelligence? Let us find out more about the different fintech AI applications, the benefits of AI in fintech, and examples of fintech startups that have embraced AI.
Why Should You Consider the Use of AI in Fintech?
Before you find out more about the top fintech AI applications, it is important to identify the reasons for embracing AI in fintech. Artificial intelligence can offer a wide range of advantages for companies and customers in the fintech space. Here are the notable advantages of bringing AI into the world of fintech.
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Better Decision Making
AI has the capability to process massive collections of financial datasets in real-time. In addition, the power of analytics with AI also helps ensure strategic decision-making. The insights by AI can help fintech companies with identification of potential risks and offering personalized financial advice to consumers. AI also offers support for data mining to develop an in-depth understanding of customer behavior and ensure optimization of services.
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Enhanced Risk Management
Artificial intelligence can also enhance fintech through better risk management. For example, AI applications in fintech facilitate the generation of credit scores with better accuracy. On top of it, artificial intelligence improves risk management by identifying suspicious patterns in transactions. As a result, fintech companies can ensure improved fraud detection and safeguards against money laundering.
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Advantages of Automation
AI can empower fintech with automation to deal with repetitive tasks. The best fintech AI applications point to the use of robotic process automation to simplify tasks such as email processing and data entry. It can help fintech companies achieve significant cost savings alongside improving efficiency of their workflow. Most importantly, AI can reduce the chances of human error and lead to more accuracy and reliability in all business processes.
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Personalized Customer Service
Artificial intelligence use cases in fintech also serve promising improvements in customer service through virtual assistants and chatbots. Natural language processing can help chatbots understand natural language to communicate with customers like humans. One of the prominent applications of AI in fintech for better customer service is the collection of different types of robotic advisors. AI can offer personalized recommendations to customers based on insights from customer data. Furthermore, AI-powered chatbots and robotic advisors can also move over the barriers of availability by responding to customer queries anytime.
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What are the Most Popular Fintech AI Applications in 2024?
The opportunities for adopting AI in fintech continue expanding with proof of success with fintech AI applications. The AI in fintech market might reach a total value of $61.3 billion by 2031. Here is an overview of the most popular fintech AI applications that fintech companies should adopt in 2024.
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Algorithmic Trading
The most common application of artificial intelligence in fintech is algorithmic trading. AI systems can enable real-time analysis of massive amounts of data. It serves as the foundation of one of the top fintech AI applications by uncovering insights that would be invisible to statistical models.
Therefore, fintech startups can help their customers in trading shares and stocks through user-friendly mobile apps. AI can guide consumers to better investment decisions through faster recognition of anomalies and evaluation of financial data for identification of trading trends. Algorithmic trading enables traders to look for profitable opportunities while avoiding potential issues.
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Credit Scoring
Fintech AI applications in 2024 would also focus on credit scoring by accounting for more factors beyond past credit history or income. AI systems can leverage different types of financial information to predict the likelihood of a borrower paying back the loan. Such types of AI applications in fintech can help lenders make decisions for approval of loans. AI algorithms can utilize different data points, such as social media behavior and demographics, to identify potential defaulters.
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Robotic Process Automation
The most important AI application in fintech is Robotic Process Automation (RPA), and it will gain momentum in 2024. The answers to “How AI is used in fintech” would focus on addressing the complex and routine back-end tasks. RPA can help in automation and streamlining of back-end office processes. For example, JP Morgan Chase uses a chatbot to complete work of 360,000 hours within a few seconds.
Some of the routine tasks that can be automated with RPA include security checks, mortgage and credit card processing, consumer onboarding, and security checks. RPA software helps banks complete their work with better efficiency, cost-effectiveness, and speed. Robotic Process Automation enables human workers to focus on core operations of fintech companies.
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Customer Support Chatbots
The fintech industry also leverages AI applications in the form of chatbots to offer customer support. AI-powered chatbots have led to massive changes in the approaches to customer service, particularly with respect to cost-effectiveness. Chatbots are one of the powerful applications of AI in fintech, and they have led to operational cost savings of almost $7.3 billion in 2023.
Some of the popular AI help desk software, such as Zendesk, help in collection of support tickets and expand the list of customer contacts. As a result, fintech companies can deliver better and seamless customer service with human-like interface. Popular examples of fintech AI applications for customer support include HSBC chatbot, Amy. On top of that, Bank of America also has a virtual assistant, Erica, who guides users and helps them make cost-effective decisions.
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Fraud Prevention as a Service
Consumers are gradually becoming more vulnerable to cybersecurity threats with the increasing levels of fintech adoption. Fraud prevention and awareness can help in ensuring secure fintech experiences. It is one of the best fintech AI applications that can strengthen risk management in fintech. AI models and machine learning algorithms can leverage predictive and prescriptive analytics for comprehensive fraud detection. With AI, fintech service providers can flag transactions that are more likely to be fraud attempts.
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Regulatory Compliance
The applications of artificial intelligence in fintech also invite attention to the possibilities for using AI to achieve regulatory compliance. Most of the top fintech AI applications can help in automation of the compliance process and effective monitoring of transactions to identify potential violations.
Artificial intelligence can help with efficient execution of compliance tasks such as AML and KYC checks, thereby reducing manual effort. AI can streamline compliance processes alongside ensuring lower compliance costs. Furthermore, AI can maintain comprehensive documentation of compliance processes, thereby creating an effective audit trail for regulatory reporting.
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Customer Segmentation
Fintech companies can reach their target customers through the use of AI for customer segmentation and targeting. AI systems analyze customer data to identify the market segments that can deliver the best results and also offer recommendations for targeted marketing campaigns. Artificial intelligence can help fintech startups with improved customer acquisition and customer retention.
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What are the Situations Where You Should Not Use AI in Fintech?
Artificial intelligence delivers a broad range of advantages in the domain of fintech with different types of applications. The answers to “How is AI used in fintech?” overshadow the fact that there are certain situations where you should not use AI in fintech. Some of the notable factors that indicate that you should not use AI in fintech include cost restraints and limited availability of data.
Furthermore, fintech companies that have fewer repetitive tasks and low complexity should avoid AI. Furthermore, a lack of expertise in AI is also a notable factor that can hold back a fintech service provider from embracing AI. However, fintech businesses of all sizes will need AI in some form in the future. Therefore, it is important to take the initiative and achieve a better competitive advantage for fintech companies with AI.
What are the Examples of Fintech Startups Using AI?
The examples of fintech startups that use AI can help you discover how artificial intelligence has actually helped in achieving promising improvements in fintech. Here are some of the most successful fintech startups that leverage AI.
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Enova
Enova is a trusted lending platform that offers services for advanced credit assessment and financial analytics. It showcases one of the best AI applications in fintech with its Colossus platform.
The new platform focuses on offering credit to people who cannot access traditional financial institutions. Enova also facilitates faster and more efficient processing of loan applications while reducing the time required to approve loans.
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Kasisto
As a result, Kasisto can shape the future of digital assistants by leveraging the capabilities of NLP models. Most importantly, it can tailor digital assistants to investment management, business banking, and consumer banking.
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Zest AI
The platform leverages thousands of data points to offer transparency to help lenders with a better assessment of populations that were traditionally at risk.
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What are the Challenges of Adopting AI in Fintech?
Fintech companies are likely to encounter different types of challenges in the process of adopting artificial intelligence. The challenges for adoption of top fintech AI applications include the massive amounts of sensitive data and need to establish trust. Fintech companies must also consider the importance of additional efforts required to achieve compliance. The most critical challenge in the domain of fintech is the risk of a carefully created image of a fintech company. This implies that you have to pay continuous attention to the workings of fintech AI solutions without any risks of failure.
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Final Words
The review of best fintech AI applications provides a new approach to understanding the advantages of fintech. Artificial intelligence is the most powerful technology that drives fintech and would also shape the industry’s future. Some of the popular examples of fintech AI applications, such as customer support chatbots and credit scoring apps, prove that artificial intelligence can create new milestones in fintech. However, it is also important to pay attention to the challenges of adopting AI in fintech by studying the examples of successful fintech startups that use AI. Learn more about the domain of fintech and how its future would depend on AI.
