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Financial services
The financial services industry is the biggest spender on AI services and is experiencing exponential growth. Financial AI applications include algorithmic trading, portfolio composition, and optimization, fraud and cyberattacks prevention, credit, loan and insurance management
Algorithmic trading
According to CNBC, nearly 90% of traders fail to be profitable every year mostly due to the inability to simultaneously evaluate multiple market conditions and forecast stock prices accurately, insufficient decision speed, and emotional bias. Algorithmic trading (AT) uses ML to learn the data structure and then advises on trades or trades directly without human intervention. AT trades at the best possible prices with increased accuracy and reduced likelihood of errors, benefiting from computational ability to assess numerous asset parameters and emotional/psychological factors absence
Investment portfolio optimization
Each investor has individual goals and risk tolerance. The portfolio optimization is usually done either by the investor itself or by involving a human expert. Both options implicate significant human efforts and prone to errors and emotional biases. Advisors powered by NLP and ML algorithms automate the task and exclude human involvement together with associated mistakes. AI advisors' accuracy and performance are incomparably higher than humans'
Prevention of frauds and cyberattacks
Financial fraud and cyber crimes are one of the most dangerous and rapidly growing economic threats. Online payment fraud losses are expected to exceed $200 billion over the next 5 year [according to Juniper Research]. Digital crimes will cost $10.5 trillion annually to the world by 2025 [according to Cybersecurity Ventures]. AI can spot abnormal irregularities in data patterns that are normally overlooked by humans and, thus, prevent frauds and cybercrimes. At the same time, AI improves the precision of transaction approvals in real-time and reduces the number of false rejections
Credit and loan decisions
Every credit and loan is associated with a risk of non-return. AI analyzes all relevant data on customers and identifies bad factors, improving loan underwriting and reducing financial risk
Insurance management
AI can recommend appropriate insurance products in a user-friendly and human-like style, relieving a customer from hours of studying insurance conditions. As a result, insurance providers benefit from the increased amount of sales and customer satisfaction. AI can also support insurance officers in the risk assessment of issuing and paying insurance, thus, driving better company-wide decisions
$1 tln a year

for global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year

52% of people are confident that cyber-security is not a threat when sharing personal information online because of robust AI technologies
$46.3 bln

according to the latest Meticulous Research® publication, Artificial Intelligence in Cybersecurity Market is expected to reach $46.3 billion by 2027

85% of financial services companies is China, US & UK are currently using some form of AI
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