Have you noticed that it’s either 3 am or 3 pm when you open your banking application or visit your bank’s website, and you get the answer instantly? If you think that the customer support team works at the banks 24/7 to answer your general queries, then it’s time to burst the bubble.
As the world has revolutionized and now every sector is making the most from artificial intelligence, the finance sector has also employed AI to enhance their productivity. Around 80% of the banks globally understand the benefits of using AI and 70% of financial firms are already using AI for risk assessment, risk mitigation, fraud prevention, etc.
A study conducted by Business Insider reveals that the potential savings of banks by employing AI applications are around $447 Billion. These statistics are proof that in this era, AI will completely take over the traditional methods used in the finance sector.
Applications of AI in Finance:
- AI in Customer Support
Now, you don’t need to wait for a call to connect with a customer service representative, as AI has taken over the CSR department. No matter what the time is, you can ask your queries because of the integration of chatbots that offer personalized assistance.
The implication of AI also allows customers to access their online bank accounts via facial recognition or biometric features which is not only more secure but convenient too.
- AI in Risk Management
It has always been challenging to manage and lower the risks in the banking sector. However, artificial intelligence and machine learning have made it easier by using predictive analysis.
Where traditional credit scoring models calculate the credit scores by just analyzing the income and credit history of the borrower, AI models go beyond and identify non-traditional variables such as social media history, purchase behaviour, etc.
Machine language also helps in risk management when buying stocks by using predictive modelling to analyze the market situation, trends, and risks.
- AI in Preventing Cybercrimes
People believe that their data and money are safe in the banks but banks are the hot place for thefts and cybercrimes. Handling the sensitive data of the people is a concern for banks and finance companies so they are shifting towards security machine learning.
ML and AI reduce the chances of human error and the software detects and prevents cyber attacks by keeping a check on the traffic. Integration of NLP in algorithms helps in analyzing the thousands of emails to detect any malicious or suspected activity.
- AI in Algorithmic Trading
Nowadays trading is not just a game of guessing but it has shifted to high-frequency trading or algorithmic trading. It means that now people are more into data-driven investments. AI plays its role in algorithmic trading by analyzing past data and suggesting potential stocks and coins. This approach has brought reliability and stability in trading as data never lies!
- AI in Fraud Detection
A study shows that financial companies have lost over $500,000 just because of fraudulent activities. Since when the e-commerce and online payments have come into the picture, there has been a massive increase in fraud activities.
Using artificial intelligence to mitigate fraud is a good approach as fraud detection systems understand the patterns, spending, and history and alarm the authorities where things seem to be slightly abnormal.
Benefits of AI in Finance:
- Accuracy
One of the biggest perks of employing AI in finance is the reduced risk of human error. As AI and ML work on existing data and models, they learn patterns. It helps in analyzing large datasets accurately without missing the technicalities. It has also brought accuracy in credit risk assessment by excluding bias in the decision-making and generating results by a deeper analysis of multiple factors.
- Automation
The use of AI helped in cost cuttings by automating the variety of tasks. Artificial intelligence can be used for data entry, verification of transactions, and compliance checks. This is not only a budget-friendly approach that can save millions of finance companies but also an error-free method.
- 24/7 Availability
Whether it’s monitoring the performance of campaigns or surveillance of security systems, AI can handle all without any risk of blinking. In addition to this, AI models can also be used to provide 24/7 assistance to customers, enhancing their user experience.
- Speed
A human takes a lot more time to analyze the data and trends than artificial intelligence. As AI models are trained enough, they can analyze and provide insights into complex data sets within seconds which maximizes productivity and saves work hours.
Ethical Considerations of Using AI in Finance:
- Privacy & Security Concerns
As AI analyzes the personal information of the users, it points fingers towards the sources. People raise questions like why and how their data is collected and making it publicly available for AI tools. Additionally, AI tools must be equipped with multiple encryptions and security walls to protect the safety of data from cyber breaches.
- Integration of Signature Designs
As AI tools can access your data very easily to generate results, risks of misuse of your e-sign have also increased. Furthermore, these tools use e-signatures for verification purposes, so there’s a high risk of fraudulent activities. To avoid such issues, the signature design should align with the legal standards to ensure the validity of the transactions.
- Lack of Accountability
No system or tool is foolproof, and as AI has been used widely, there’s a high risk of a lack of accountability. As AI works on the past data, there are high chances of biased results while calculating the credit scores and no one can be blamed for it. Similarly, no one holds responsibility for ethical dilemmas that arise due to the use of artificial intelligence.
Conclusion
It’s an unsaid fact that every blessing comes with some cons in disguise. This same thing applies to the use of artificial intelligence. The right approach to using AI in our favour is not to completely rely on it; insights should be cross-checked, and the authority of decisions should be reserved for humans only.
