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AI and the Finance Industry

AI and the Finance Industry

Thursday February 13, 2020,

11 min Read

Automation is not a new concept in today’s digital world. Hundreds of businesses have adopted automation for automating various tasks. We all experience the benefits of automation in our daily life. Let’s begin from zero and reach the desired point.

Task Automation

Task Automation, is basically, the use of technologies, automatic machines or equipment to do a particular work with zero or minimal human intervention. Adopting automation and putting jobs to automated machines and systems help you to do what you want, making you free from tedious and monotonous work. It gives you a chance to leverage the power of technology and the digital era we are living in.

Artificial Intelligence

Artificial intelligence entered our life as the biggest transformation that had ever happened, this revolution has reached the consciousness of every enterprise.

Artificial Intelligence has actually penetrated our lives in a big way but we often do not even notice how deeply it has become a significant part of our lives.

Almost all businesses, from small scale to large industries, are considering deploying AI to smoothen business processes and enhance growth.

Not only you use AI in your smartphones, tablets, and cars but if you become conscious then you will realize that it’s everywhere around you.

Earlier, every business could not afford deploying AI because of its high-implementation cost, but the time has changed and even small businesses and startups, now, are able to adopt artificial intelligence to automate and streamline their business. It has enabled an increase in productivity with minimal errors. 

Software solutions have rivaled human resources and their tasks. This revolution has enabled hi-tech companies to design exceptional systems that would help to accommodate the digital workforce to complete tasks more efficiently. It has also enabled an increase in productivity with minimal errors. 

Artificial intelligence along with Machine Learning and other digital innovations and technologies have come together with new advanced capabilities of detecting fraud, recognizing patterns, and much more.

Potential of Artificial Intelligence

AI and machine learning (ML) will certainly have a great impact on your business’s efficiency. Smart systems can automate a vast amount of your work and help diminish the probability of human errors. Gradually, you will have a smarter system and more favorable outcomes.

According to Gartner 2018 CIO survey (registration required), only 4% of surveyed companies have deployed an AI-based solution. The rest of the companies are still planning. Global organizations are currently using artificial intelligence to make rational decisions.

Examples of AI implementation

  • Coca-Cola, the soft drink company, is preparing to design its own virtual assistant and incorporate the same into its vending machines.
  • Artificial Intelligence in the traveling industry is helping to optimize sales and price. It helps prevent fraudulent transactions and provide personalized advice for desired routes, dates, and costs if and when needed.
  • AI in the transportation industry is vigorously employed in developing self-parking and more advanced cruise control features, to make driving safer and easier. The biggest breakthrough here is- autonomous vehicles or self-driven cars are already running on the roads. And this tech-disruption will lead further to the launch of flying cars in the coming years.

AI In Finance

Artificial intelligence in the finance industry is a phenomenon that has already started to happen. The finance sector is experiencing numerous benefits with the implementation of Automation and AI just like other sectors.

It helps the financial executives and business in major ways like:

  • add value,
  • save time,
  • reduce costs, and
  • gain productivity.

For example, bots are designed to track accounts’ activity of customers to understand and analyze how account holders invest, spend, and make financial decisions, to give them customized advice accordingly.

AI-driven chatbot communicates with users and provides account information to help customers reset their passwords.

AI Transforming the Finance Industry

The finance industry is quickly changing and rising with the emergence and growth of AI for the past few years and is still under the process of development.

The finance sector is not just about buying and selling. It is a vast sector where many departments work together to provide the required services.

Here are 8 important use cases for automation and AI in the finance industry. Let’s have a look!

1. Maximizing Resources

AI helps finance industry companies save time and money by using algorithms to improve customers’ service, make predictions about the sales performance of the company, generate insights, etc.

2. Unlocking the Value of AI Algorithms

Automation has been in use for years and is replacing humans for repetitive tasks using machines. Some of the automated tasks that tools like automated cloud accounting software does include making calculations, looking for exceptions, and matching data records.

Artificial intelligence, however, is replacing human decision-making using more sophisticated and innovative technologies.

AI has the capability to learn and improve constantly. Types of data that AI can handle phenomenally well and beyond human accuracy are:

  • Parameters and numbers
  • Writing, analyzing, and interpreting the text
  • Spotting patterns
  • Object, human, and Face recognition
  • Activity detection
  • Automatic equipment audit etc.

Companies need access to big data sets and apply data processing power and interpret results to unfasten AI algorithms.

3. AI and Process Automation

Robotic Process Automation (RPA) is indeed the strongest tool for the finance industry for operational cost-cutting and enhancing productivity. Various repetitive and time-consuming tasks (such as managing payroll) that consume hours and hours of manual calculations are automated through an intelligent character recognition system.

Smart software generates reports and verifies data according to the given parameters, and extracts information from applications, agreements, etc.

Implementing RPA here eliminates the possibilities of human error and allows financial organizations to refocus workforce efforts on other processes that need human involvement.

4. AI and Trading

AI ensures accurate data management. The software can be used to analyze the present market conditions and can suggest outcomes, helping customers to take independent decisions whether they want to invest or not.

Trading and investment companies completely rely on AI for managing large data sets. Over the past few years, data-driven investments have been lifting constantly and closed in on a trillion dollars (in 2018). The so-called algorithmic or high-frequency trading has been expanding swiftly across the world as AI offers multiple benefits. Such as:-

  • Faster processing: AI-driven systems are capable of monitoring both structured data like databases and spreadsheets and unstructured data like social media etc. Manual processing of large amounts of data is extremely time-consuming obviously and would take many hands to carry out the job. On the contrary, AI finishes it in no time.
  • Quick decision-making: Faster processing of huge voluminous data at high speed allows you to make quick decisions which in turn results in faster transactions.
  • Accurate reports: AI uses algorithms that check the trading system and predict stock performance with more accuracy and generate valid reports.

5. AI and Fraud Detection

According to a 2015 study by the research firm Javelin Strategy- a suspected fraud that wrong rejection of authorized transactions caused losses for retailers for about $118 billion annually. Fraudulent activities on credit cards have also been increasing for the past few years because of expanded e-commerce and online portals for shopping. This is where Machine Learning (ML) helped industries and consumers to safeguard themselves from cyber frauds. ML Algorithms are capable of analyzing data points to identify many frauds (regarding financial transactions) and spotting unusual patterns.

The smart software can analyze and recognize the consumers’ details like their location and purchase history to develop a behavior model that is used to alert customers if anything is tracked outside the pattern. Automation provides automatic responses through investigation and reports, the analysts/employees/consumers/security teams to act upon if needed.

The workforce’s proficiency to detect frauds in the cyber world is whereas not up to the level of AI. Thus financial firms and systems using ML and AI ensure the real-time approvals and accuracy of data reducing false declines that eventually result in more efficient processing.

6. AI and credit Judgments

The manual decision for granting credit is a lengthy and time-consuming process especially when there are multiple accounts and queries to handle. This involves a number of activities like checking accounts, eligibility of customers on the basis of their previous loans, and decision for issuing a credit, etc. Using AI, this task is no more an ordeal.

Artificial intelligent software, like cloud accounting, is a robust technology helping in the accurate risk assessment of the borrowers and making correct decisions on the basis of powered algorithms that use alternative information and help to evaluate the eligibility of customers and hence, making smart and tactful judgments on granting credits without being biased on gender, race, and other factors.

Furthermore, Machine learning algorithms are used by Digital banks and other loan issuing apps that use alternate data for e.g. smartphone data to assess loan eligibility and give personalized options.   

U.S based automobile lending companies have reported favorable outcomes using AI in their system for their needs and this report exhibited cutting losses by 23% per year after bringing AI onboard.

7. AI and Risk Mitigation

Risk management is one of the most important roles of automation and artificial intelligence in the finance industry. ML algorithms use the learning software to analyze past risk cases and make predictions on potential future issues. AI in the finance industry is a powerful tool for mitigating various risks by:-

  1. Analyzing real-time activities in the businesses,
  2. Making accurate predictions, and
  3. Providing detailed forecasts.

Artificial but smart intelligence with its power processing handles large amounts of data in no time. The ability of intelligent software in handling both structured and unstructured data is done within very less time as compared to humans.

“Employing artificial intelligence on the Amazon Web Services platform has shown a notable improvement in risk analysis” - A U.S leasing company, Crest Financial.

8. AI and Personalized Banking

Artificial intelligence has proved itself to be a superpower by conquering tediousness and erroneousness in almost every sector, specifically when we are talking about personalized banking.

AI sparkles exploring new methods and providing numerous and additional advantages to individual users. AI-driven systems in the banking sector, such as smart chatbots, enable a user with self-help solutions and simultaneously diminishing the call centers’ workload.

The software can look up account activity, check balances, and schedule payments. Many apps offer personalized financial advice to help individuals achieve their financial goals. These AI-driven systems can track income, recurring expenses, and spending habits and accordingly offer an optimized plan and suggest financial tips.

The biggest US banks (Wells Fargo, Bank of America and Chase) have launched mobile banking apps that alarm their users with reminders to pay bills, plan their expenses and interact directly with their bank in a more streamlined and easier way, from accessing data to completing transactions.

Expectations from AI

Artificial intelligence has still a lot more to give to the finance industry. However, whatever it has gifted until now is no less than a boon for every associated person and organization. AI has certainly reshaped and still in the process of reshaping the landscape of business in this sector.

The future is hoping for more secured accounts and transactions with the expansion of adopting block chains and cryptocurrencies. This might reduce transaction fees due to the absence of a mediator.

Cognitive computing is also helping constantly to improvise all kinds of digital assistants or apps that might help in managing finances in an easier way since smart machines and AI will be able to execute all tasks from bill payments to tax filings.

AI technology applications and emerging finance companies will influence the future of finance. This is like setting the stage among the industry’s leading giants for the growing competitiveness.

In the following years, AI will help financial services companies generate

  • more revenue,
  • maximize resources, and
  • mitigate risk in trading, lending, investment, and banking.

We also expect to have better customer care services that use self-help Virtual Reality systems with more advanced language processing.


Artificial intelligence helps financial firms in making money by enhancing accuracy in trading and more efficient wealth management. Automation and AI can also be used in customer service, sales, retention efforts, and compliance as well.

Since the benefits of automation and Artificial Intelligence in financial services are versatile and difficult to overlook, many finance companies are investing in AI-based systems of their own.

Business masters actively explore innovative AI use in finance and other fields to get a robust edge on the market.

According to Forbes, the implementation of AI in financial services has shown 65% positive changes. As of late 2018, just one-third of organizations have taken the move to implement artificial intelligence into their business processes.

Many still misjudge it, to be on the safer side, being cautious about time and outlay such an organization will demand, and hurdles in implementing Automation and AI in financial services.

However, they should be alert for the future about not adopting AI now, which may cost them far more in the long run.