Blog

Artificial IntelligenceFintech

Top 8 Fintech AI Use Cases

If there is one technology paying off, it's AI in Fintech. Artificial Intelligence has provided the banking business and the financial industry with a means to meet the needs of clients who want smarter, more convenient, and safer methods to access, spend, save, and invest their money.

Ostap Zabolotnyy
Ostap ZabolotnyyMarketing Manager
Top 8 Fintech AI Use Cases

Traditional financial services have been transformed into 'Fintech' because of disruptive technologies such as blockchain, the Internet of Things (IoT), and Artificial Intelligence (AI). Fintech apps have become the new norm in the financial services industry. The role of AI in fintech is astounding. Do you know that financial institutions are rapidly investing in developing and acquiring AI-based fintech products? 

AI in fintech investment is predicted to reach USD 22.6 billion globally by 2025, according to a recent Research and Market prediction! 

Artificial intelligence is not fast fashion; it is here to stay. So, how does it alter the face of the financial sector, what are the most popular applications of AI in fintech, and how do you capitalize on this emerging technology? Let's find out. 

AI in Fintech

Financial technology ("FinTech") refers to digital innovation in the financial sector in general. It now refers to a wide range of technological interventions in the financial services sector, including crowdsourcing, online client acquisition, mobile wallet, Blockchain, and cryptocurrencies. 

As businesses seek to learn about automation, machine learning, robots, analytics, and other topics, artificial intelligence (AI) has become a sought-after skill. Financial services organizations are attempting to implement AI for monotonous task automation, consistent customer service, deep-dive behavior analysis, and efficient fraud detection. 

AI in Fintech; Top 8 Use Cases

Stronger Security 

Artificial intelligence has significantly improved data security in the financial technology sector. Many banks and fintech companies offer client service through chatbots powered by AI. These AI models can provide several ways to improve security, such as resetting lost passwords and allowing additional access. 

Another method AI boosts financial security is through speech, facial, and fingerprint identification. This added layer of security makes it harder for hackers to exploit than standard passwords. While these processes are still being refined, it is feasible that AI-powered security solutions will eventually replace usernames and passwords. 

Cyber security becomes increasingly crucial as the world grows more online and less personal. Fintechs, banks, and other financial institutions are the most vulnerable because they handle billions of dollars daily. Keeping up with AI and machine learning breakthroughs, guarantees that your firm has the best security available. 

Greater Fraud Detection 

Deceptive financial behavior has increased in recent years, ranging from credit card and loan application scams to bogus insurance claims and illegal wire transfers. Individuals and corporations might lose millions of dollars because of these fraudulent banking operations. In addition to cash losses, businesses must deal with unpleasant customer experiences and potential reputational damage. 

Much of the AI venture funding in the banking industry is used to target fraud and cybersecurity. With so many daily financial transactions, it is practically impossible to analyze each transaction for erroneous or potentially suspect activities manually. 

Efficient AI systems can monitor financial transactions in real-time, and AI algorithms can discover abnormalities or strange patterns that deviate from a user's daily spending habits. Fintechs can respond to potentially fraudulent activities more quickly and accurately with AI. Superior AI systems can frequently detect suspicious activities before the scam occurs. 

Improved Customer Service 

Clients are becoming increasingly accustomed to receiving speedy responses at any time of day as artificial intelligence has already made significant gains in customer service for banks and fintech companies. Financial institutions must be available 24 hours a day, seven days a week, to answer queries and ease transactions. If you do not respond quickly to customers, you risk losing the business to a competitor. 

Call centers are frequently under pressure to address backlogs while still providing continuous help. AI-powered chatbots, virtual assistants, and other AI interfaces save workload by handling basic inquiries and the most common user concerns. This frees up time for customer service teams to handle more complex queries. They can be more attentive to the needs of their consumers, resulting in a better working relationship. 

AI is helping to improve fintech customer service by using advanced sentiment analysis, which focuses on analyzing the client's experience, detecting gaps, and training chatbots to solve those gaps. With AI-based technologies, communication between customers and fintech is easier and more accessible. Happier customers and customer service employees who are more content lead to a more profitable firm. 

Personalized Banking Services 

Customers of large financial institutions number in the thousands, if not millions. Providing individualized services to so many unique individuals would be a monumental task without AI-powered technologies. Personalization can increase client trust in your firm and increase brand loyalty. 

When customers download banking apps, AI systems collect and evaluate customer data. Data can be used to propose relevant pre-approved items and customized financial advice. AI in banking apps can also assist clients in tracking their financial objectives and expenses. 

AI systems will only get better at reading client data and offering personalized experiences because they are self-learning. To generate useful information, AI models evaluate voice and speech characteristics and can discern accurate patterns from monotonous babble. AI transcript analysis can forecast a customer's mood and guide agents on what solutions to provide them. 

Enhanced Algorithmic Trading 

Although algorithmic trading has been present since the 1970s, it has come a long way in recent years, with even more exciting developments taking place all the time. Algorithmic trading employs artificial intelligence (AI) technologies such as machine learning to conduct stock trades by following a pre-programmed set of instructions that analyze data to make trading decisions. 

AI has changed the typical trading desk by analyzing millions of data points in real-time and producing insights that statistical models cannot discover. Consumers may trade stocks and shares using user-friendly mobile apps and AI-powered decision-making thanks to AI in fintech. 

An AI system adjusts to a changing trading environment more quickly since a machine learning model constantly takes in new data and learns from it. In the next generation of algorithmic trading, AI in fintech will further lower trading risks with better-educated decision-making. Systems will be able to recognize and account for anomalies more effectively, evaluate financial information to spot trading trends, and rapidly react to execute appropriate market trades. 

Robotic Process Automation (RPA) 

Any FinTech or Banking business is all too familiar with the complexities of managing ordinary back-end activities. By utilizing a 'smart chatbot,' these institutions may automate and streamline back-end office procedures from end to end. 

RPA can be used to automate the following typical tasks: 

  • Onboarding of new customers 
  • Checks for security 
  • Operations involving trade financing and the loan application process 
  • Inbound calls for routine queries like account statements and transactions 
  • Processing of credit cards, account closures, and mortgages 

Finally, while human agents focus on providing a customer-centric banking experience, RPA software will enable banks to work more efficiently, swiftly, and cost-effectively. A win-win for all. 

Save Money and Resources 

Fintech industries can save billions of dollars in capital, labor costs, and resources using AI-powered solutions. Manual procedures are often more time-consuming and expensive due to labor expenditures. AI automation saves money and time by taking over these activities and duties. Customer service teams will experience a drop in staffing costs as AI technology handles lesser questions. 

AI saves banks money at the front office through personalized insights, in the middle office through anti-money laundering, and in the back office through credit underwriting. Banks can offer better deals and attract more customers because of the money saved by deploying AI technologies. As a result, money is saved while income and profit are increased. 

Credit Scoring and Loan Prediction 

Artificial intelligence can help financial firms make better decisions by detecting trends in past data, such as lending loans to customers. Clients can be profiled using machine learning algorithms depending on their risk score. As a result, credit scoring is regarded as one of the top financial technology developments. 

5 Startups Implementing AI in Fintech

We've compiled a list of how artificial intelligence is being applied in finance companies leading the way. 

Enova 

Enova created the Colossus platform, which uses artificial intelligence and machine learning to give advanced analytics and technology to non-prime consumers, enterprises, and banks to support responsible lending. 

The Colossus problem assists customers in resolving real-world issues, such as emergency costs for consumers and bank loans for small enterprises, without putting either the lender or the beneficiary in an untenable scenario. 

ZestFinance 

ZestFinance created the Zest Automated Machine Learning (ZAML) platform, an AI-powered underwriting system that assists businesses in assessing borrowers with little to no credit information or history. 

The technology uses hundreds of data points and gives transparency that current underwriting systems cannot, allowing lenders to properly assess groups that have previously been considered "at risk." ZAML is a complete platform that institutions may swiftly install and scale. 

Canoe 

Based in New York, Canoe ensures that alternative investment data is quickly collected and retrieved by employing APIs, AI, and advanced data science capabilities to ingest, validate, and provide critical information. 

Kasisto 

Kasisto is the creator of KAI, a conversational AI platform used in the finance industry to improve customer experiences. 

KAI assists banks in reducing call center volume by giving self-service options and solutions to clients. Furthermore, AI-powered chatbots provide customers with calculated advice and assistance with other daily financial decisions. 

Vectra 

Cognito, an AI-powered cyber-threat identification and hunting tool, is created by Vectra. 

Vectra's software automates threat detection, identifies hidden attackers, especially targeting financial institutions, speeds up event investigations, and even identifies compromised data. 

Benefits of AI in Fintech

Introducing artificial intelligence into finance has helped financial institutions and companies streamline processes, make better decisions, provide increased security to their clients and more; Let's take a look at how AI can assist organizations in the financial industry move one step closer to their objectives. 

Higher User Engagement 

AI solutions monitor app users, respond to their questions instantly (chatbots), or collect analytics on user preferences and activity patterns. 

Optimized Workload 

AI technologies help fintech employees with routine tasks, including answering common questions, categorizing clients, and monitoring transactions and emerging regulations. 

Secure Payments 

AI in fintech enables continuous payment monitoring and user verification, filling countless security vulnerabilities that humans cannot see. 

Reduced User Support Cost 

AI and machine learning in finance reduce the chance of human mistakes and save you money on user support in the long run. 

Data-Driven Decision Making 

AI investigates every dark corner to assist you: it gathers documents, creates reports, and makes predictions. You gain a powerful tool for developing actionable business strategies. 

Future of AI in Fintech

As AI grows more widespread in finance, experts believe that its application will spread across new industries, resulting in increased crossovers and, as a result, tensions, particularly in data access. 

However, the amount of money that financial services firms invest in training their employees will ultimately determine how much AI is employed in the business. Those who can better use new technologies and their capabilities can autonomously establish a competitive environment, form fundamentally new values, and allocate resources more efficiently. The financial business will undoubtedly shift, potentially undermining existing methods. 

Conclusion

Fintech is evolving quickly because the market is growing at the same rate. Every year, new patterns emerge, and one player can drastically alter the game. Understanding the fundamental changes and the required field of development allows business owners and CEOs to clearly understand the industry, identify strategies to stay ahead of competitors, and make smart decisions for the company's future. 

Daily technological advancements and improvements are expected to have a long-term impact on our lives. All we have to do now is sit back and observe. 

Get our infopack

Best quick guide to start working with us.