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Artificial Intelligence in Finance: Opportunities and Challenges

By Anonymous User posted Sun November 14, 2021 09:02 AM


AI is an unusual technology that can be used in various industries, and finance is no exception. Given that AI’s main benefit is its ability to work with large amounts of data, finance can profit from using Artificial Intelligence even more than other states. Artificial Intelligence is presently being used by many organizations that work in insurance, banking, and asset administration.

A great point about Artificial Intelligence is that it can be used in various ways. For example, AI-driven chatbots can support financial organizations in communicating with their clients. Artificial Intelligence also works as the basis for virtual representatives. Machine learning algorithms also allow algorithmic trading and can be applied for risk administration, fraud detection, and relationship management.

Artificial Intelligence in finance gives numerous advantages. Possibly, the main benefit of AI is that it provides countless automation possibilities. In turn, automation can improve financial organizations increase the productivity and performance of many processes. Also, since Artificial Intelligence can replace people in certain situations, it assists eliminate human biases and various failures caused by sensitive or psychological factors. 

Artificial Intelligence is also better at interpreting data. Machine learning allows computers to recognize data patterns, provide decision-makers with essential insights, and help organizations get more accurate reports.

So, how is AI used in finance?

Artificial Intelligence Now: Where It Works and What It’s For


Automation is so popular because it allows companies to boost productivity and cut operational expenses. Tasks that used to take a lot of time and challenged organizations to hire teams of low-skilled workers now can be completed much faster and easier. For example, Artificial Intelligence can use character identification to verify data automatically and produce reports according to specific parameters.

Automation supports companies in eliminating human errors and enables workers to focus their efforts on more critical tasks that a machine cannot complete. According to statistics, Artificial Intelligence helps businesses save up to 80% of the costs connected with data entry and other monotonous tasks.

Many big corporations realize the benefits of Artificial Intelligence, so they produce their own AI-driven solutions or use current automation solutions that allow you to adapt and use them for your specific purposes. 

Credit Decisions

Artificial Intelligence also assists banks to assess possible borrowers much faster and more accurately while also saving expenses. AI-based solutions can quickly analyze countless parts that can have an impact on a bank’s choice. Artificial Intelligence uses more complicated credit scoring approaches than conventional systems so banks can understand whether somebody is a high-risk candidate or simply doesn’t have enough credit story.

AI-powered software gives a higher degree of objectivity. Machines are not biased, which is a significant factor, especially in financial app development. Loan-issuing apps and digital banks enable banks to provide personalized choices and integrate alternative data, including smartphone data, into the decision-making method.

Artificial Intelligence is advantageous not only for banks but also for many other businesses. For example, automobile lending organizations report that the use of Artificial Intelligence enabled them to cut their losses by up to 25% yearly.


The trend of data-driven properties has been demonstrating steady growth throughout the last decade. Two years ago, data-driven investments closed on a trillion dollars. Artificial Intelligence and machine learning are applied in so-called high-frequency trading, also called quantitative or algorithmic trading. This kind of trading grows more and more popular because it offers various advantages.

AI-driven trading methods can analyze massive volumes of data much faster than people would do it. They can go with both unregulated and structured data. The fast speed of data processing directs to fast decisions and transactions, allowing traders to get more value within the same period of time.

Also, predictions made by Artificial Intelligence algorithms are more accurate because they can examine a lot of historical data. Artificial Intelligence algorithms can test various trading methods, offering a new level of validation effectiveness so that dealers can assess all the pros and cons before using a particular system.

Artificial Intelligence can analyze a particular investor’s long-term and short-term aims to recommend the strongest portfolios. Financial organizations often use Artificial Intelligence to manage their entire portfolios. Numerous organizations have also recognized the forecasting capabilities of Artificial Intelligence. 

Viewpoint and News Analysis

Hedge funds don’t want to share data about operating, so it can be difficult to know how they may use sentiment report. But, Artificial Intelligence has already proved its capabilities in digital marketing, and its ability to work with information from social media can be used in the financial industry. 

It makes sense to require machine learning for various automation and customization tasks and for news trends, social media, and other data sources that have zero to do with sales and stock prices.

The stock market responds to several different factors, not only to the ticker symbols. AI can be used to mimic and improve our intuition when it comes to hunting for new trends and getting signs. But, to perform such tasks, Artificial Intelligence needs to prepare data and understand its context better, which is still a difficulty. 

For example, AI-based chatbots can give concise answers to questions; however, Artificial Intelligence is still far from writing comprehensive reports or ad copy because it cannot know the context of the information it works with.

Risk Management

Risk control is another field of application of machine learning in finance. Artificial Intelligence offers unbelievable processing power and can handle massive volumes of both structured and unstructured information, it can handle risk administration tasks much more efficiently than people. ML algorithms can also investigate the history of opportunities and detect any signs of possible problems before they happen.

One of the main benefits of Artificial Intelligence in finance is that it enables companies like Baker Street Funding to analyze various financial actions in real-time, regardless of the market situation. Companies can choose any essential variables for their business preparation and get detailed forecasts and accurate forecasts.

Fraud Prevention

Artificial Intelligence has also been confirmed to be very effective in preventing and fighting fraud. Cybercriminals regularly develop new, more powerful tactics, but AI-based solutions can use machine learning and immediately adapt to the hackers’ plans. 

Such solutions are mainly effective when it gets to fighting credit card fraud. This kind of fraud has become more and more popular during the last few years because of the increasing popularity of online activities and eCommerce.

AI-driven fraud discovery tools can analyze clients’ behavior, track their locations, and manage purchasing habits. Hence, they can immediately detect any unusual actions that diverge from the regular spending pattern of a particular customer.

Banks can also use AI to deal with other kinds of financial crime. For example, Artificial Intelligence can be used to fight money laundering. ML algorithms can instantly detect unusual activity and minimize the costs of investigating money-laundering systems. 

Personalized Banking

The benefits of Artificial Intelligence become apparent when it comes to personalization and giving additional advantages for users. For example, banks use AI-powered chatbots to offer appropriate help while also minimizing the workload of their call centers. Financial institutions can also use various voice-controlled virtual assistants. 

Many apps offer personalized financial guidance so that users can achieve their financial aims. These smart-systems can track regular expenses, income, and buying habits to provide the financial suggestions necessary and optimized plans. 

Ways How AI Transformed the Finance Industry

The financial industry has transformed dramatically since the mid-1990s. Digital technologies have greatly influenced this area, and now it’s more digitized than ever because of digital banks and mobile banking. We live in an era when steam and convenience are the main competitive benefits in any industry. 

Millennials and Generation Z are the most significant part of the workforce, and they’re used to receiving all the necessary data and purchasing products by just tapping on the screens of their mobile devices.

Hence, this market is becoming even more active and competitive. To withstand intense competition, businesses need to keep up with the latest technological aims. Artificial Intelligence is a technology that gives businesses significant improvement by facilitating numerous processes.

Specialists predict that Artificial Intelligence will have saved financial businesses about $1 trillion by 2030. According to the investigation, more than 35% of banks are already using Artificial Intelligence to decrease the response time, better recommendation engines, and perform voice recognition and predictive analytics. New application areas appear all the time, and organizations learn to use Artificial Intelligence for their specific purposes.

One of the most vital trends in innovation is the use of Artificial Intelligence to improve client experience. Some customer-oriented answers, like chatbots, have become mainstream. At the same time, algorithmic analytics, task mechanization, and process automation are growing more and more popular in finance because businesses realize what benefits these technologies offer. 

Although robotic automation involves rule-based, technically not intelligent ways, this technology is often used along with various Artificial Intelligence solutions. ML is the most common type of technology compared with AI, and it also plays a vital role in the transformation of banks and the financial business in general.

ML has already shown its tremendous potential in various applications, and the financial sector is no different. The main advantages of machine learning in the finance industry are gathering, processing, and organizing huge amounts of information. 

Solutions that are based on ML require little to no support from humans. They can learn from past data, detect patterns in it, and use these penetrations to operate with data in the prospect. Some answers also use these models to make predictions. 

When talking about Artificial Intelligence, ML and automation are discussed most often. These subsets of Artificial Intelligence are indeed very useful and they can produce amazing results fast so guests can quickly evaluate the advantages of the new technology and its ROI. But, there are also less visible areas of AI that are nevertheless very impressive. 

What to Expect in the Future from Artificial Intelligence in the Financial Industry

Customer service

Conversational interfaces and chatbots are becoming more and more common. Organizations can use many universal chatbot solutions from various niches, but companies already produce industry-specific software intended for banks and other financial institutions. Such software will help clients make the required calculations and evaluate their budgets fast.

Additionally, voice recognition allows banks to assist in the most convenient way probable. Such solutions will surely become a huge competitive advantage because banks that give quick interaction and querying will attract clients of traditional banks that need their users to log onto banking portals, look for the essential functions, and search for the necessary data themselves.

New Standards of Security

Passwords, usernames, and security issues may disappear from the financial business in the next few years. Safety is essential in the financial industry because most people would rather have their social media accounts hacked than become victims of hackers who want to keep their credit card information. 

Accordingly, the financial industry is most likely to use AI-backed protection solutions to ensure that no one can reach their customers’ data.

We’ve previously mentioned that Artificial Intelligence can detect unusual and different behavior. Thanks to speech perception and facial recognition and the analysis of other biometric information, banks might add new layers of security or even replace traditional passwords with more powerful approaches.


Automated solutions for financial sales now exist, but not all of them involve ML. Most frequently, these are rule-based ways. But, virtual assistants can also give recommendations more smartly. For example, they are already able to make suggestions on potential changes to the portfolio, but they can also analyze different websites with advice on insurance services and help you pick a plan that meets your objectives.

AI-driven applications are becoming more and more personalized, and personalized recommendations are no longer used solely.


Chatbots and automation software are not the only progress in financial machine learning associated with Artificial Intelligence. ML enables financial institutions to simplify various time-consuming tasks and to cut costs significantly, so there’s no wonder that the financial business is already using Artificial Intelligence in various areas. 

For example, Artificial Intelligence can help reduce risks, fight fraud, and assist banks in making credit choices.

Another great benefit of Artificial Intelligence is that it gives countless personalization possibilities. Mobile banking will proceed to evolve, and financial businesses that fail to adopt the latest tech trends will likely lose their consumers. Given that Artificial Intelligence can work with massive amounts of information and make forecasts based on the basic set of factors, the role of ML in trading will also increase.

AI has already transformed many industries permanently, and its tremendous potential is clear. Hence, it makes sense to require wider adoption of Artificial Intelligence in finance and provide for new opportunities.