We live in the era of rapid technological progress, with the virtues of that progress finding application in a variety of industries and niches, including finance. Financial institutions have always been at the forefront of technological innovation as they deal with large masses of customer data, financial analytics, economic forecasts, and financial planning.
Thus, with the rising trend of digitization, financial companies have already embraced the computational speed and error-free technologies the modern innovation offers.
One of the best and most promising innovations in FinTech is artificial intelligence (AI). The focus of AI is to achieve better efficiency with lower costs by performing human tasks and simulating human behavior at a much higher speed.
In other words, AI lets computers perform human tasks in terms of client demand forecasting, personalized customer service, and advice, as well as sensitive, accurate decision-making based on large masses of unstructured data. It's done much quicker than people, and usual computers can do, with the AI potential increasing day by day as machines learn and hone their intelligence and skills.
The primary benefit of AI for financial services is the impressive computational speed and the analytical potential it offers, allowing quicker and more sensitive decisions based on accurate analytical prognoses.
In other words, the key target of AI implementation is efficiency increase coupled with more client-oriented customization achieved with the help of advanced algorithms, big data analytics, and in-depth data analysis.
What is fintech?
In a nutshell, one can characterize Fintech as technology-oriented financial organizations applying the latest innovative technologies for the advancement and optimization of financial service provision. Due to the emergence of Fintech companies only around a decade ago, the challenges and barriers people used to experience on the way to accessing financial services are gone.
The use of cutting-edge technologies enables high-quality services at lower rates and well-organized and streamlined workflows with a small workforce. As Fintech companies are created initially with a focus on cutting-edge technology and innovation, nothing is surprising about their active interest in AI. Among the most famous Fintech startups investing in AI development are Aire, ZestFinance, and EyeQuant.
How is artificial intelligence used in finance?
There are many ways to adopt AI in finance and take advantage of its features and capabilities. Here are some core benefits financial organizations derive from AI integration in their operations today.
Previously, lenders had to go to a bank and file a heap of documents asking for a business loan, getting which was (and is) extremely troublesome. But with the emergence of Fintech, crowdfunding platforms like Patreon or GoFundMe merged to unite borrowers and investors in a space alternative to traditional banking. Now, if your idea is cool, you can attract investors directly, getting money from different sources to jumpstart your businesses without financial blocks.
2. Intelligent assistants
AI assistants have entered the financial industry and enjoy great popularity among users. For instance, such advisors are helpful in investment decision-making, analyzing large-scale stock and bind data, and giving users suggestions for buying or selling assets depending on their level of risk, financial goals, and the composition of their portfolio.
3. Blockchain and cryptocurrency
Probably the most famous application of artificial intelligence in finance, blockchain and cryptocurrency now rule the world of decentralized, alternative banking. Global crypto-exchanges like Coinbase allow users to exchange crypto-assets for money and vice versa, while new smart blockchain services (e.g., BlockVerify) help users avoid fraud by securing the intactness of blockchain data and transactions.
4. Insurance management
Insurtech is a new trend branching out of Fintech today. AI-enabled insurance services are much more customized and sensitive in terms of pricing and coverage, giving more people access to affordable insurance and bridging the gap between providers and users. Some bright examples of promising Insurtech startups include Oscar Health and Credit Karma, both raising considerable funds from the onset and exhibiting healthy growth within the past years.
5. Innovative mobile payments
As smartphone users are becoming the world's largest segment of Internet users, Fintech responds to their needs for payments and other financial services on the go. With a mobile phone in their hands, users can now perform all kinds of operations ranging from paying for goods and services to exchanging money, paying taxes, and even managing their employees' payroll.
6. Smart financial advisors
AI systems' ability to handle big data and analyze it smartly has found an application in Robo-advising and investment management. Robots of Betterment and Ellevest help clients make investment decisions based on large-scale stock dynamics data. At the same time, innovative stock-trading apps remove the need for an official stock exchange as an intermediary charging a commission.
Pros of AI application in fintech
The pros of applying artificial intelligence in Fintech in your business are numerous. Here are some of them you should consider if you plan to opt for the AI solutions.
- Large-scale cost cuts. Apart from the traditional financial institutions that have long bureaucratic pathways for all decisions, Fintechs are experiencing unprecedented growth because of quick and smart decision-making based on big data use, AI, and predictive intelligence. These gains are accompanied by better data and asset security, guaranteeing cost savings, and quality improvements at all levels.
- Advanced fraud detection. Unlike the old-school rule-based system of fraud detection, AI helps to make smarter decisions based on fuzzy, unstructured data in real-time. As a result, fraud detection gets more accurate, with higher predictive power in ambiguous user behavior cases, enabling Fintech organizations to secure their users' funds and keep their sensitive assets intact.
- Efficient customer service. The progress of AI has made human-like chatbots a reality. Today, some users can't even distinguish whether they are chatting with a bot or with a human being as AI responses and problem-solving capacity are impressive. Today, AI-enabled chatbots are used by MasterCard, Lemonade, PayPal, American Express, and many other progressive organizations. Other examples are the KAI chatbots of Kasisto and the Co-Pilot chatbot by Digital Genius. The best about chatbots is that they continuously apply natural language processing and machine learning to understand people better, thus improving the quality of their service day by day.
- Smart decision-making. Managers of FinTech organizations receive better data for making decisions as a result of in-depth data analytics with AI. As a result, they can make more sensitive and accurate decisions, progressing towards data-driven management. With AI, financial institutions become more accurate and personalized in lending, payment, and insurance services, able to access broader pools of clients because of more intelligent credit scoring and borrower analysis approaches.
- Accurate predictive analysis. The best AI can now offer to Fintech is smart management of no-file and thin-file segments of the population, including people with no credit history (or a scarce one). Previously, such potential lenders were scored low in the banking systems following the traditional scorecard method. At the same time, AI helps examine the employment potential and wealth growth prospects of people who currently have little chances to qualify for a loan.
Cons of AI application in fintech
However, together with praising the advantages and innovations AI brings to the field of finance, one should stay cautious about the limits of this solution. There are some perils of artificial intelligence that optimists tend to overlook.
They may pose some gains of Ai introduction into question and even compromise the efficiency and quality improvements a financial organization can achieve. Let's take a closer look at the aspects of AI requiring caution and extra consideration.
- High implementation cost. Even though AI implementation is economically viable and promises significant cost cuts, its integration is still costly at first. Thus, some financial firms find themselves unable to embrace the innovative technology, remaining at the brink of progress while their competitors advance and take their market share.
- Limits to human intelligence replication. AI systems are praised for imitating human intelligence and performing tasks in a human-like fashion, though at a much higher speed. Yet, every businessperson implementing AI solutions should keep in mind that no AI system will ever get close to human performance as machines are doomed to remain machines. So, it's better to remain sober and realistic about the limits of AI potential.
- Limited improvement in performance. No matter how long the artificial intelligence systems learn, they still cannot surpass the human learning potential, with their capacity limited to the amount of historical data they receive.
- Poor creativity. AI systems are totally devoid of the uniquely human trait – creativity. Thus, they can perform some tasks tediously, accurately, and quickly, but they are unable to make unusual, extraordinary decisions, which is sometimes imperative.
- The threat of unemployment. A common fear surrounding the massive introduction of AI is the threat of unemployment it brings. Overall, it is valid for low-skilled labor worldwide, as automation allows replacing manual operations. Machines do not sleep and eat; the employer doesn't need to pay taxes for them or cover their vacations. Thus, in the long run, AI automation is indeed a business measure for cutting costs on otherwise costly manual labor.
However, AI is not a threat to highly skilled intellectual labor as such jobs are, on the contrary, gaining prominence and enjoying higher demand. Businesses need people who will program and operate AI systems, which can be done only by highly qualified professionals with expertise in engineering.
How will AI affect finance jobs?
Many people fear that the massive introduction of AI in all aspects of financial operations threatens human workplaces by making some jobs redundant. As we discussed above, in part, it is true as AI implementation results in efficiency advances without the need to involve more human forces.
In part, it is false as AI innovations are rarely concerned with replacing humans, more often dealing with the advancement of human decision-making, speeding up financial processes, making predictions more accurate and sophisticated, etc.
Thus, finance experts should not fear remaining overboard as a result of technological progress; instead, they should hone their professional skills to integrate into the new hi-tech workforce of the future.
Jumpstart your AI-enhanced fintech business with Datrics
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Even if you have never worked with AI and have zero technical expertise, you'll be able to create a suitable AI application for your business needs without wasting time on lengthy and costly software development.