Employing robotic process automation for high-frequency repetitive tasks eliminates the room for human error and allows a financial institution to refocus workforce efforts on processes that require human involvement.
Fremont, CA: Artificial Intelligence (AI) in the financial industry is rapidly changing the business landscape, even in traditionally conservative areas.
Given are five ways how AI is impacting the finance sector:
AI and Fraud Prevention
The growth of e-commerce and online transactions have led to an increase in credit fraud. AI’s fraud detection system studies the clients’ behavior, location, and buying habits and triggers the security mechanism when something seems wrong and contradicts the established spending pattern.
AI is also useful when it comes to money laundering. Machines recognize suspicious activity and help to cut the costs of investigating the alleged money-laundering schemes.
AI and Personalized Banking
Banking sectors use the AI-powered smart chatbots that help clients with a holistic self-help solution reducing the call-centers’ workload. Voice-controlled virtual assistants are also gaining popularity as they get smarter by the day. Both these tools can check balances, schedule payments, look up account activity, and more.
Many apps offer personalized financial advice, helping individuals achieve their financial goals. From tracking income to essential recurring expenses, and spending habits, these intelligent systems come up with an optimized plan and offers financial tips.
AI and Trading
Data-driven investments, also called algorithmic, quantitative or high-frequency trading have been growing slowly over the last five years and has been expanding across the global stock markets;
[vendor_logo_first]Intelligent Trading Systems monitors both structured and unstructured data in a fraction of time, making faster decisions and faster transactions.
Algorithms can test trading systems based on past data, transforming the validation process to a whole new level before pushing it live, thus helping predictions for stock performance more accurate.
AI also puts together recommendations for the most robust portfolios depending on a specific investor’s short and long term goals.
AI and Credit Decisions
Compared to the traditional credit scoring system, the AI scoring process is based on more complex and sophisticated rules. It helps lenders differentiate between high default risk applicants and those who are creditworthy by a lack of extensive credit history. Besides, unlike humans, the AI-powered machine is not likely to be biased.
Digital banks and loan-issuing apps use machine learning algorithms to use alternative data (e.g., smartphone data) to analyze loan eligibility and provide personalized options.
AI and Risk Management
AI in the financial industry plays a crucial role when it comes to risk management. The enormous processing power can handle a large amount of data quickly, while cognitive computing helps manage structured and unstructured data. Algorithms analyze the history of risk cases and identify early signs of potential future issues.
It can also analyze real-time activities in any given market or environment. The accurate predictions and detailed forecasts it provides are based on multiple variables vital to business planning.
See also: Top Fintech Solution Companies
