In their constant search for new opportunities to maximize profits and cut losses, businesses usually turn to digital technologies. Thanks to recent advances in artificial intelligence, companies can optimize their routine operations, enhance security, and streamline business analysis, among other invaluable benefits. The scope of implementation of AI in FinTech is pervasive, and its advantages are undeniable. As a result, artificial intelligence has already achieved wide-scale adoption, and it is expected to become a critical requirement for financial business in the next three years. In this article, we will review the most popular uses of AI in the financial industry, along with its advantages, challenges, and future prospects.
AI in the FinTech Market
Fintech is an extensive concept that encompasses the implementation of various digital technologies in the financial services industry. These days, artificial intelligence, Big Data, blockchain, cloud computing, and the Internet of Things are the top five technologies that represent the leading trends in FinTech. Among them, AI arguably has the most diverse implementations thanks to its crucial role in data analysis and process automation.
One of the beneficial features of artificial intelligence is its ability to effectively cooperate with other digital technologies. Such cooperation greatly enhances the range of tasks that AI can perform. So, thanks to this feature, artificial intelligence has become a versatile and invaluable tool for the purposes of security, customer service, audit, and many other aspects of FinTech.
The Role of Artificial Intelligence in FinTech
These days, companies of all sizes seek ways to optimize business processes with the help of digital solutions. As a part of digital infrastructure, artificial intelligence plays an essential role in many financial processes. Of course, the ultimate role of AI-powered solutions is to increase the profitability of companies through a range of benefits and business opportunities.
The recent survey of 500 financial services professionals conducted by Statista revealed the most acknowledged benefits of implementing AI in the respective industry. Here are the results of the survey and some other applicable advantages in the context of FinTech:
- Better customer experience.
- Improved operational efficiency.
- Lower costs of running a business.
- Gaining a competitive advantage.
- Access to accurate predictions and analysis.
- Discovery of new business opportunities.
- Improved risk management.
- Better security of assets and property.
These and other benefits offered by digital technologies have revolutionized the financial sector. Even the oldest banks started investing in FinTech and shifted their operations from traditional “pen-and-paper” manual approaches to automated methods.
Opportunities Presented by AI in FinTech
Thanks to the constant development of artificial intelligence, experts keep devising new ways to implement it in FinTech.
Customer Experience. AI-driven chatbots are typically the first thing that comes to mind when considering the implementation of artificial intelligence in FinTech and other industries. However, having an AI-based personal wealth manager that analyzes your income and spending behavior is a financial service that has a prominent future. Artificial intelligence can also be successfully used for offering personalized investment advice that considers numerous variables like the client’s age, location, financial history, education, interests, risks, trends, and so on.
Risk Management. Artificial intelligence is vastly beneficial for every financial institution as a risk management system. The AI algorithms can gather and analyze the client’s financial history to make better decisions on whether they are eligible for specific loans. Credit scoring and automated loan processing empowered with FinTech AI or machine learning models can significantly minimize and even eliminate the risks associated with loan approval.
Fraud detection. Fintech companies need custom AI-empowered fraud detection software for successfully fighting cases of account botting like creating bot networks and fake accounts, online payment fraud, identity theft, and others. Here’s everything you’d like to know about fraud detection with machine learning and AI.
Innovation in Services and Products. Artificial intelligence algorithms boost the efficiency and quality of market research, customer surveys, trend analysis, etc., to create new offers that better fit customer demands. Additionally, AI takes significantly less time to generate multiple results and recommendations based on the analyzed data.
Market Expansion. AI in the FinTech market is widely used for more efficient and reliable market research, customer surveys, and trend analysis to expand the business reach with fewer or zero risks. AI-driven forecasting helps banking, financial, and other institutions to open offices in new locations with a favorable business climate.
Regulatory Compliance. Custom AI systems vastly increase the quality and effectiveness of anti-money laundering (AML) and know-your-customer (KYC) guidelines. The system verifies customer documents by comparing them against various internal and third-party registries within minutes and helps the manager or the automated system make better-quality decisions on each client.
Automation of operations. Despite the fact that the implementation of artificial intelligence reduces the need for staff, it won’t replace qualified specialists. On the contrary, it only helps to accelerate processes like decision-making and data analysis. Thus, it serves as an assistant rather than a full-scale employee replacement. Most importantly, AI systems eliminate human errors that may result in money or reputation loss.
Enhanced security of computer networks to prevent breaches and data leaks is also one of the perks of using artificial intelligence in FinTech companies. The AI-based system effectively detects anomalies when employees perform actions like logging in, requesting specific information, etc., as well as protects the entire company’s infrastructure from malware.
AI and IoT for the security of offices and branches. Surveillance, face recognition, behavior analysis, and other security things are already widely and successfully used in FinTech and many other industries. Automated security protocols are designed and used to prevent and neutralize armed robberies and thefts, which is especially important when the company deals with enormous sums of money and the sensitive personal data of thousands of clients.
AI Use Cases in FinTech
Nothing proves the validity of a concept better than successful real-life implementations. Below are a few examples showcasing the use of artificial intelligence in leading financial enterprises.
AI Assistants and Robo-Advisors
These customer-oriented solutions may take the form of a separate mobile or web application, but more often, they are integrated into a more complex online banking app. Usually, they communicate with customers via in-app chats, mobile notifications, or SMS. These FinTech AI assistants enable personalized approaches to improve customer experience and cover many vital issues, from account security to financial advice.
Many banks employ such multifunctional chatbots as their 24/7 customer support. Among them is Bank of America with its AI assistant Erica available for customers via a smartphone. Capital One offers Eno, a chatbot available both on the bank’s website and inside a mobile app. A standalone service Cleo is an AI-powered personal finance assistant available as a mobile app.
Automated Fraud Detection Systems
For obvious reasons, financial enterprises do not specify the details of their security systems. However, most of them prefer to announce the implementation of AI solutions to prevent fraudulent activities. This way, FinTech companies attract clients and partners and send a warning to potential lawbreakers. For example, both PayPal and Mastercard use data processing systems that employ AI and ML for real-time detection of possible fraud attempts and other suspicious activities.
AI Tools for Regulatory Compliance
Similar to the previous type of AI solutions, many FinTech companies employ the same technologies to meet applicable legislation. Many states enforce strict rules regarding data protection, anti-money-laundering (AML) measures, know-your-customer (KYC) processes, and other programs that are compulsory for the finance industry. To comply with such laws and standards, providers of financial services use AI analytics combined with machine learning and Big Data technologies. For example, JP Morgan has an AI Research team that creates synthetic datasets for further use in AML, fraud detection, and other programs.
Challenges and Ethical Considerations
Though AI-powered fintech solutions have proven their reliability and improvement potential, many experts are concerned about related ethical issues and challenges. These problems slow further development and limit the scope of AI applications in FinTech.
- Issues regarding data privacy and security. First of all, AI involves gathering and storing large amounts of data, which requires adequate security. Additionally, FinTech AI solutions are allowed to access financial information, so they can be used as a proxy by hackers to steal this data.
- Machine logic vs. fairness. AI decisions can be biased due to the flaws in algorithms and learning strategies. For example, when calculating credit scores or authorizing loans, AI may be discriminatory due to its reliance on statistical methods rather than a personalized approach to every specific situation.
- Regulatory challenges. As digital technologies improve, governments pass more laws to regulate the use of sensitive information and enforce transparency and accountability. Providers of financial services must ensure that their AI solutions comply with the growing list of rules and regulations.
- Less human employment. Artificial intelligence performs most tasks faster and better than human workers. Some may see it as “job stealing,” which presents an ethical issue considering regular surges in the unemployment rate.
Future Prospects of AI in FinTech
Numerous use cases prove that FinTech and AI are already inseparable, and the bond between them will continue to grow. The ongoing improvement of artificial intelligence is the hard requirement for this technology to remain efficient in all its current applications and discover new beneficial implementations. Below are several promising trends that will shape the future of AI in FinTech.
Improvement of Natural Language Processing
One of the current tasks of engineers is to simplify communication between AI and people. To engage in productive conversation, computers must learn to interpret human languages more accurately, take the context into consideration, and remember previous dialogues with every particular user. As one example, the development of NLP technologies will bring new capabilities for AI chatbots thanks to better speech recognition.
Focus on Deep Learning
To improve artificial intelligence, machine learning methods also have to evolve. Deep learning involves using multi-layer neural networks to analyze information, similar to thinking processes in a human brain. This is vital for financial services since data processing is the core task of AI in FinTech.
Further Automation of Financial Services
One of the ultimate business tasks of AI is ensuring high efficiency and profits for FinTech companies. To continue this trend, companies will increase the level of automation using bots integrated into the corporate infrastructure.
More Accurate Predictive Analysis
As a result of improved machine learning, Artificial intelligence will be able to perform more complex analysis and make more weighted decisions. This is especially beneficial for robo-advisors, risk management, and other financial aspects that depend on accurate predictions.
Closer Cooperation with Blockchain Technology
Further advances in AI and blockchain will improve automated secure transactions with high transparency. This is beneficial for every implementation that involves regular payments, which is vital in our era of subscription-based services.
Final Thoughts
Artificial Intelligence has already transformed the entire financial industry across the globe and continues empowering it with new enhancements. The automation of crucial processes, security increase, improved data analysis and forecasting, and better customer experience via personalization are only a few advantages from the long list for every fintech company that has already adopted AI or is considering it.
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FAQ
How is AI used in FinTech?
Artificial intelligence has many uses in the financial service industry. The potential applications cover customer support, risk management, regulatory compliance, market research, and many other areas. AI is also vital for ensuring effective measures to prevent fraud and money laundering.
Are there AI solutions for FinTech clients?
AI chatbots have become a standard feature of most online banking apps. They offer personalized support, including wealth management, investment advice, security control, and many other features. Thanks to Natural Language Processing, artificial intelligence can engage in a human-like conversation. Some financial AI assistants cooperate with the Internet of Things, so users can easily talk to them using Amazon Alexa or Google Assistant.
