Today, the financial industry can’t do without modern technologies, namely Artificial Intelligence (AI) and Machine Learning (ML). The systems help to estimate different risks, understand clients’ habits, and reduce costs by automating processes. This article will consider the main benefits of applying AI and ML solutions in the financial sphere.
- AI and ML bring up issues of transparency, privacy, security, diversity, and inclusivity.
- A fintech business can enhance customer satisfaction, lower costs, and lift earnings by using automation and data analysis.
What is Meant by ML, AI, and Fintech?
Fintech is a collective concept that includes all the existing technologies banks and other financial establishments use. AI and ML are important parts of Fintech.
Learn more about Fintech definitions, evolution, and examples in our article.
AI is a separate section of computer science dedicated to building smart machines. Such systems can perform work that typically requires human intelligence. The best examples of AI are Siri, Alexa, email spam filters, self-driving cars, and the like.
ML is a special approach that allows specialists to “teach” computers without programming. Machine Learning is a subtype of Artificial Intelligence. Its work is based on Big Data: a computer uses historical data as input to predict new output values. This process resembles a baby who learns to classify objects and events independently and determine their relationships.
So, let’s find out more about the AI Transformation in Fintech.
How does Fintech Benefit from AI & ML?
The significance of AI/ML solutions is difficult to overestimate because they open numerous opportunities to improve and expedite service provision. We want to mention the following benefits:
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Saving time. Employees can only be involved in some processes if the computer performs the operations.
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Reducing costs. It’s impossible to imagine how many people you need to serve all clients manually. Moreover, it’s worth mentioning complex tasks, which, without modern AI and ML solutions, may take a decent amount of time and cost an arm and a leg.
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Uninterrupted working process. Human resources are limited, while machines work as long as needed and round the clock.
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Augmenting the capabilities of individuals. For example, specialists operate faster using modern tools such as AI software. Thus, the company's crucial decisions are made in the shortest possible time.
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Improving customer experience. The AI Transformation in FinTech is obvious: users can operate online and make payments quickly. Furthermore, financial companies have begun to understand customers' requirements better thanks to AI and ML.
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Fraud elimination. The computer monitors each account and internal system 24/7. If it notices something suspicious, it blocks transactions immediately.
AI & ML in Fintech: Real-Life Cases
It’s impossible to mention all existing use cases, so we have cited the most vivid ones below.
Chatbots
Bots with Artificial Intelligence can provide users with certain links and forms they request. A good example is users who wish to find out details about commissions. They must enter their request and get a link with a comprehensive description. Thus, consultants can focus on solving other non-standard problems instead of wasting their time on the simplest tasks.
A well-known fact: each client asks the robot differently. Machine Learning in Fintech helps gather user request data and improve language recognition.
Security
In the bank field, market players usually apply two-factor logins (password and biometrics). So, AI and ML solutions are crucial technologies that speed up the authorization process and enhance its accuracy. Moreover, some banks have implemented facial recognition thanks to the advanced versions of AI and ML.
Big Data & Analytics
The main task of any enterprise is to increase income. This may be achieved by analyzing customers' needs to offer exactly what they wish. Today, it’s easy to force smart computers to learn users' behavior, habits, and expenses.
Knowing user habits and frequent transactions is also a key to cyber security and early fraud detection.The system immediately blocks the account if it sees unusual and suspicious actions.
Better Risk management
With AI tools, businesses have another competitive advantage: they can predict future changes in the financial market. As a result, it allows for increasing sales, maximizing resource utilization, and augmenting operational efficiency by removing different risks.
Reducing paperwork
You can’t deny that finance is a highly confusing topic. It usually includes a lot of paperwork and processes to go through. AI/ML solutions simplify numerous things and even provide some assistance. Accountants and economists start doing their work faster and more accurately.
Other potential gains from AI applications in Fintech are:
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Improved Credit Quality Assessment;
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Advancement of financial inclusion;
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Stronger capital optimization;
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Better stress testing;
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Improved market impact analysis;
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Improved trading and investment strategies;
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Advanced compliance and risk mitigation.
Agilie expertise in AI-powered Fintech apps
In recent years, blockchain technology and cryptocurrency have seen significant growth and adoption. From decentralized finance to non-fungible tokens (NFTs), the possibilities seem endless. One area that has seen remarkable growth is the world of Web3 social interaction games. Agilie implemented this approach and created Lolypto - a Web3 game that combines social interaction, NFT staking, and AI technology.
Lolypto's gameplay is based on the "You laugh you lose" concept, where users play with NFT characters, which they call Jokers. Lolypto is a platform that enables users to buy, sell, and stake NFTs using their wallets while incorporating gamification. It allows players to interact with real people and earn real coins through a video chatting game that revolves around the fusion of two ideas - the video chat game "Flinch" and the move-to-earn game "Stepn." With Lolypto you can buy cryptocurrencies via third-party services like Moonpay and Circle.
Find out more about NFT game development in our article.
Based on the client's constraints on time and budget, a minimum viable product (MVP) version was defined, covering all fundamental technical aspects and allowing them to test the overall idea. The development team helped with the rest of the assets to start raising investments.
One unique feature that differentiates Lolypto from other NFT platforms is AI modules. These modules accurately detect whether a user is smiling, creating a more immersive and interactive experience. To ensure accurate predictions, the implementation involves a combination of dynamic configuration, ML-kit, and cloud-based solutions that consider lighting, internet speed, the distance between players and the camera, and antifraud measures.
Security is a top priority for Lolypto, which operates on the Binance blockchain. The team employs AWS environment tools to secure sensitive user data, particularly wallet information. To simplify cryptocurrency storage and management, Lolypto offers a custodial blockchain-based wallet that allows users to store their crypto in-game without additional fees, making it an accessible option for NFT newcomers.
Lolypto is a revolutionary AI-based chat game app combining NFTs and Web3 technology, providing users with a fun and engaging way to enter the cryptocurrency world. With its unique features, Lolypto is set to become a game-changer in Web3 social interaction games.
Learn more about Fintech software development services.
The main cons related to AI Transformation in FinTech
There are no ideal systems: even Artificial Intelligence and Machine Learning have certain cons despite a whole list of advantages. And the presence of cons doesn’t mean you should abandon modern technologies.
First, you should know that even AI and ML solutions make mistakes, so you shouldn’t count on infallible work without any control from employees. Alternatively, you can discuss a developer of the technology to provide you with guardrail software, which would switch off the AI solution when it begins to produce incorrect outputs.
Another crucial risk has to do with the integration and implementation. AI providers must understand your company's IT estate, processes, and data sets to develop a proof-of-concept model. The desire to adopt AI/ML solutions may become a protracted thing when there is a need for more discussion.
The last common snag is data transparency. Machine Learning requires clear and accurate information arrays. Otherwise, the level of errors in outputs is likely to be significantly higher. Thus, if a business can’t trace the quality of data, it must first develop internal tools for that. Also, such a company should have a manual on how to act in certain circumstances.
Agilie has been implementing fintech solutions since 2010. Our tasks are simple: to help you increase your company’s income by boosting your work and improving the quality of your services.
Contact us to discuss your project and find the most appropriate systems.
