In the financial sector, with the development of digital technologies, another source of dividends has appeared - artificial intelligence. Programs trained on large volumes of data are able to recognize patterns, predict trends, automate complex processes. As a result, neural networks help businesses make more accurate decisions, assess risks, optimize investment strategies. From the article, you will learn which neural networks are suitable for finance and how they can be used.
Is it possible?
Artificial intelligence is actively used both in the banking sector and in companies to solve financial issues.
The capabilities of neural networks in the field of finance:
- customer service and natural language processing;
- high accuracy of calculations;
- analysis of data arrays;
- reporting;
- accounting;
- drawing up prompts;
- forecasting risks and monetary losses;
- assessing the impact of external factors on the investment market.
It is important to understand that neural networks require a competent approach and understanding of the basics of analytics. It is impossible to fully trust artificial intelligence to manage business finances or bank clients’ money. Digital technologies have their limitations, which depend on the amount of source data, machine learning, and model updates.
How to use
Companies use AI in trading, insurance, and asset management. In the banking sector, chatbots inform clients 24/7, and robot consultants provide personalized investment recommendations. AI prevents cyberattacks, warns of unusual activity, analyzes user behavior, checks borrowers’ creditworthiness, and tracks credit history. Investment companies use AI tools for transactions that are carried out at high speed by evaluating real-time data and market trends.
Forecasting and analysis of market data
Forecasting is at the heart of every financial plan. And if earlier financiers had to be a bit of an oracle and predict market trends based on guesswork, now AI tools take on data analysis. Neural networks study the market to analyze consumer information for companies, identify trends, predict changes in stock prices, currencies, and other assets.
What tasks does AI perform:
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analyze trends and fluctuations based on news data;
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identify patterns in large volumes of information;
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detect anomalies;
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determine the optimal time to buy or sell assets;
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forecast exchange rates of currencies and securities.
AI-based market forecasting and analysis helps teams spend less time processing data and focus on strategic planning, which leads to better business results.
Risk assessment and investment optimization
Operational risks pose a serious danger to companies and threaten financial stability. And at the same time, if you do not take risks in investments, it is difficult for players to succeed. Neural networks do not just warn about risky transactions. They estimate probable losses, model scenarios, offer asset allocation strategies and optimize investment portfolios.
How AI helps in risk assessment:
- analysis of borrowers’ creditworthiness;
- assessment of market volatility;
- identification of hidden risks in the portfolio;
- forecasting the probability of default or bankruptcy of the company;
- automated risk insurance.
AI-based tools are capable of creating complex order placement strategies to manage risks in active transactions. Programs develop and automate option strategies for hedging, instantly make adjustments depending on market conditions.
Examples of successful application
AI can analyze almost any information on finance. This includes fundamental data, company cash flows, technical analysis, stock market fluctuations, stock movements, customer creditworthiness, etc.
Examples of the use of neural networks in finance:
- Banks use AI to analyze credit history, transactions and behavior of borrowers to determine the level of risk of issuing a loan. * Insurance companies automatically process insurance claims, determine the amount of payments, analyze photos of damage, medical records and reports to speed up payments to clients.
- Trading platforms use AI to predict stock prices, currencies, and cryptocurrencies. Neural networks process news, macroeconomic indicators, and identify patterns and trends.
- Banks and brokers use AI to create personalized offers for clients. The tools analyze financial habits, goals, and offer suitable products or investments.
Examples show that neural networks generally speed up transactions, increase the accuracy of forecasts, reduce risks, and improve customer service.
Tools and services
There is a wide variety of neural networks that can be used in finance without special technical knowledge. The most popular of them are:
- AlphaSense
- Kensho
- DataRobot
- ZestFinance
- ChatGPT
- QuantConnect
If the platform is unavailable in Russia due to sanctions, there is no way to pay for a subscription through the banking system of foreign banks, the Chat AI service will help you get access to popular artificial intelligence tools. All neural networks that can be useful for work and personal purposes are collected on one platform. You can use the tools on the website, using VK and Telegram bots, or install an extension in your browser.
Recommendations and results
AI is changing the work of financial organizations, helping companies and startups develop. It automates financial processes that previously had to be done manually, creates effective ways of interacting with clients, and manages risks. However, the introduction of AI tools in financial management requires the right approach:
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learn the basics of financial literacy and do not blindly trust AI;
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use proven neural networks with machine learning;
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ensure data security;
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update models regularly;
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invest in training employees to work effectively with the software.
Use digital assistants that create new opportunities for your business or personal investments. But do not forget about the importance of the human factor and critical thinking.
