Artificial Intelligence In Finance: The Role & Ultimate Implications

Artificial Intelligence In Finance: The Role & Ultimate Implications

Just like every other sector, finance too is highly impacted by AI Mechanisms these days. Artificial Intelligence in finance has gone far beyond imagination and is utilized to process zillions of functionalities day in and day out.

From swiping cards for making payments to getting the exact percentage of remission, AI has overpowered the financial sector. Though these are very typical and important aspects, in this article, we’ll discuss what purposes artificial intelligence serves in financial planning and what major concerns stand before it.

Applications Of Artificial Intelligence In Finance

Finance Management is a core component of every economy, and the fast-paced lifestyles call for a system in place that can run uncountable calculations, provide metrics, and strengthen the ideology of customer understanding, and that system goes by the name of Artificial Intelligence (AI). 

The below-listed applications of AI in finance will assist in analyzing the revolution it has brought to the financial sector:-

1. Data Management & Analysis

Data is critical for making decisions in any sector, let alone the financial sector. With a plethora of large and small fintech companies coming up each year, huge piles of data get generated. It wasn’t this easy to compile and analyze such heavy loads of data before.

Artificial Intelligence In Finance: The Role & Ultimate Implications

AI has not just made the process less hefty but also provides accurate figures to rely upon. Based on the interpretation of such data, decisions related to credit lending, card issuance, etc., are made.

Because of this data analysis, social media giants like Facebook and WhatsApp have been able to integrate payment channels with the platforms. Not only that, in fact, certain social media platforms, including Facebook, have put AI in use to formulate campaign budget budgets as a part of modern-day social media marketing.

2. Formulating Plans & Strategies

Along with artificial intelligence, Machine Learning (ML) is also set together to run financial markets smoothly. Where today, corporations are deploying ERP to integrate efforts of all the departments within an organization; they are also investing in accounting softwares to manage inventory, reckon costs, tax, profits, risks, and manage orders.

Also, AI being deployed in finance also makes chances of getting errors as rare as hen’s teeth (as it is generally only plausible if wrong data is entered or if a wrong command has been given). Though the very aspects of the financial market are dynamic and can go in any direction anytime, AI gives close and most accurate estimations based on past trends and incorporates the effects of facets. Such data-driven insights are relatively more reliable than mere gauged ones.

This helps in disbursing the budget allocation with ease in the direction where necessary and forecasting the market behavior.

3. Helps In Verifying Credit Related Scores & Data

‘Get Instant Loan Approval’ is the favorite saying of firms involved in the finance sector. How do you think it is possible for fintech? Well, you guessed it right- Artificial Intelligence.

AI has eased the assessment process and analysis of several factors (including income variables, transaction history, repayment history, inflation index, amount of down payment, amount and number of installments, collateral, etc.) while lending loans and providing financial services.

This application of artificial intelligence in finance is exploited widely. It also holds a chance for people with no credit score to build a credit portfolio that can be of assistance in the future for availing of loans.

4. Detects Fraudulent Activities & Prevents It

A critical implication of deploying artificial intelligence in finance is detecting and preventing fraudulent activities. Integrating AI and ML, users’ behavioral trends of spending and depositing are analyzed so as to detect any uncommon or skeptical activity.

Moreover, automated or computer-generated messages and emails regarding payments, withdrawals, and deposits are typical examples showing AI’s advantages in the financial sector.

5. Algorithm Trading

When it comes to the stock market, the financial market has seen quite a massive investment in algorithm trading, the reason being the effort to continually cut down the time frame of analyzing the market patterns and making a move as fast as possible because there is no other way to get leverage in trading.

After all, the futures and options market is itself such an intensive field, and analyzing enormous data piles requires AI to foster market profits.

Together with ML and DL (Deep Learning), AI has made it possible to do so in a blink of an eye. These systems work on set algorithms that are capable enough to process such heavy data loads and provide insights in milliseconds letting the users rake in profits.

Today a number of people are integrating AI to develop their own app or platform that can assist users who aren’t well-versed with the very aspects of trading in making informed decisions by presenting real-time data in the form of figures, graphs, charts, and diagrams to interpret the information easily.

Also, with the rise in the count of investors in cryptocurrencies, AI is in more demand than ever.

6. Automated Process

The most basic yet effective solution provided by artificial intelligence in finance is handling clients via automated procedures. With chatbots, the customer has 24/7 assistance in place so they can connect with businesses and get help in a plethora of financial activities, be it managing cash flows, evaluating eligibility for loan approvals, etc.

Artificial Intelligence In Finance: The Role & Ultimate Implications

These robots work as per the embedded codes and algorithms and drive the optimum solution to the user irrespective of the time of the day he/she gets engaged with that particular service.

It also saves extensive labor spending as often people just wish to analyze different quotes or fetch information about criteria or a process to draw a fine comparison before actually going in for services.

Downsides Of Deploying Artificial Intelligence In Finance

Though AI has empowered the financial industry like any other industry, there are certain pitfalls yet to be worked out at a global level. The two major concerns associated with the utilization of AI in finance are discussed below:

1. Cyber Security Breaches

With the emergence of highly sophisticated algorithms and tools, there is a need to keep the eyes peeled for cyber security breaches. Cyber crimes make trusting artificial intelligence in finance a biting a bullet kind of task.

Artificial Intelligence In Finance: The Role & Ultimate Implications

These issues must be addressed with the implementation of strict policy laws so that any cyber attacker, be it a person or a big tech firm, can not have access to data beyond the required extent and get punished for its misuse or leaking it in any way.

2. Intensive Energy Consumption

No doubt AI has brought a wonderful revolution to the financial market but managing such heavy data with the integration of machine learning and deep learning comes at a heavy price in terms of enormous electricity consumption, which means the production of large-scale emissions and overexploitation of power resources which can adversely affect the environment and the needs of the population at global level, respectively. That’s why being carbon negative is the new emerging trend for tech giants around the globe.

With AI taking over almost every sector under its grasp, finance wasn’t going to stay untapped. So far, the above article has discussed the major areas of applications of AI in finance and major concerns related to it.