AI is getting extremely popular, and many professional fields are slowly adapting to this new notion. There are multiple AI use cases recorded in various fields. This idea might leave some people wondering how can AI adapt to such complex fields. Well, that is what we will be exploring. One of these innovative fields is finance. So, how is AI in finance doing? Let’s discuss
What Is AI In Finance?
Artificial intelligence or AI in finance is the use of technologies like machine learning that imitate human intelligence and decision-making to update the way financial institutions analyze, manage, invest, and protect money. It also aids these financial organizations to better understand markets and customers, learn from digital journeys, and engage in a human-like matter.
How Is AI Used In Finance?
Contrary to what people might think, AI is very much needed in the finance field. In fact, it has many uses including security, regulatory compliance, fraud, anti-money laundering (AML), and know-your-customer guidelines. Many financial organizations including banks, insurance companies, and more can perform many tasks such as forecasting performance and detecting anomalous spending behavior.
Using AI To Solve Challenges In The Finance Sector
Like any other business field in the world, the finance sector faces many challenges. Luckily this is where AI comes in and saves the day.
Now with AI in finance, you can convert speech to text to enhance your service with remarks and suggestions from customer interactions, like contact center sales calls. This creates a better customer experience and improves customer service.
One of the popular uses of AI in finance is using it to detect anomalies including fraudulent transactions, financial crime, cyber threats, and more.
With the aid of AI, you can now make your content, such as financial news, multilingual with fast machine translation. This helps in enhancing customer interactions and reaching more audiences wherever they are around the globe.
The presence of AI in finance allows you to extract structured and unstructured information from documents. You can analyze, search, and store this data for extensive document processing, loan servicing, and more.
You can use AI to create a human-like AI-powered contact center to make communication with customers easier and more genuine. You can use it in places like banking concierge or customer service, this will help lower costs and clear your human agents’ time.
Examples Of AI In Finance
There are different sectors where AI is used in finance. Therefore, many companies race to keep up with these evolving technologies and become the best in their field. Here is a list of some companies that specialize in using AI in finance in their respective fields:
AI In Credit Decisions:
AI aids banks and credit lenders to find solutions and make smarter decisions by using multiple factors that assess more accurately the traditionally underserved borrowers in the credit decision-making process.
Location: Chicago, Illinois.
Enova is a company that uses AI and machine learning to provide advanced financial analytics and credit assessment. This company serves small businesses and non-prime consumers and helps solve real-life problems. Such as emergency costs and bank loans while making sure that neither lender nor recipient is put in an unmanageable situation.
Location: New York, New York.
Ocrolus features a document processing software that combines machine learning with human verification. This software allows businesses, organizations, and individuals to increase the speed and accuracy when they need to analyze financial documents. Moreover, this software can analyze bank statements, pay stubs, tax documents, and more.
AI In Managing Financial Risks:
Financial risks are a huge issue in financial markets and can hinder the speed and accuracy of many businesses. That is why these markets are relying on machine learning to create more exacting models. The predictions will help financial experts use existing data to point out trends, identify risks, and make sure that they acquire better information for future planning.
Location: McLean, Virginia
Range is a membership-only fintech company that markets its services to millennials. This company prides itself on its integration of the old school and new ways of taking on wealth management services. Services such as investment, retirement, education, and estate planning. All of these are handed in via certified financial consultants. Moreover, these services are attached to DIY wealth management tools that are powered by AIs.
Location: Cambridge, Massachusetts
Kensho is a company that created machine learning training and data analytics software that can asses and analyze many datasets and documents. This data training software uses machine learning, cloud computing, and natural language processing. Also, it can provide easy understandable answers to complex financial questions.
AI In Quantitative Trading
Quantitative trading is the process of using large data sets to figure out the patterns that can be used to make strategic trades. This is where AI-powered computers come in, as they can analyze large and complex data sets at a faster rate and with more efficiency than humans can.
Location: New York, New York
Canoe makes sure that alternate investment data, such as documents on art and antiques, hedge funds, and commodities, can be collected and extracted efficiently. Their platform uses natural language processing, machine learning, and meta-data analysis to identify and categorize documents.
Location: San Mateo, California
Alpaca utilizes proprietary deep-learning technology and high-speed data storage to support its yield farming platform. This company is compatible with dozens of Cryptocurrencies and allows its users to lend assets to other investors in exchange for lending fees and protocol rewards.