There are a wide variety of applications within the financial system for AI and machine learning such as: Trading signals: Machine learning increase efficiency and reduce costs of investment firms by swiftly parsing news from multiple sources and make trading decisions based on more sources of data than a person is capable of. However, these machine learning methods are susceptible to false news that could cause incorrect trading decisions, that can manipulate the outcome of the trading decisions.Sentiment Indicators: Social media data analytics companies use Artificial Intelligence and Machine Learning methods to discern ‘sentiment indicators’ among customers. Similarly banks, hedge funds, high-frequency traders and social trading platforms can find investor sentiment indicators extremely useful.Fraud Detection: Companies can also use machine learning methods for monitoring credit reports and mitigating risk. Financial institutions also increase productivity while reducing costs and risks, to comply with regulations by using AI for AML/CFT and fraud detection. Financial Fraud Financial Fraud is a deception with aim of appropriating other people’s financial assets, which could be their bank accounts, credit cards, mortgages, loans and credit information or even identities. Nefarious parties will use this information to acquire new loans, credit cards or steal identities. The most popular types of a financial fraud associated with using online services are the following:Carding or card skimming: By attaching magnetic stripe reading devices to Automatic Telling Machines, swindlers can obtain cards’ data. This data can be sold on the Dark Web for making fraudulent purchases on the internet.Malware or Spyware or Viruses: Personal and financial information can be stolen, causing substantial damage to users by infecting their computing devices with special software such as malware, spyware or viruses.Phishing: This sophisticated strategy involves creating a replica of a trusted website (such as that of a bank or credit card company) and directing users to such sites by either sending genuine looking emails or listing the links in web search results. When customers are directed to these websites, they unwittingly enter their credentials and confidential information which the website records and steals.Mobile viruses: Similar to malware on desktops and laptops, specialized mobile viruses help thieves steal the secret data that is stored on mobile phones.