How Can AI Be Used to Improve Financial Decision-Making?

In this article, we will discuss how AI can be used to automate routine tasks, detect suspicious activities, and predict borrowing behavior. It will also show you how to automate various legal documents and financial statements. The benefits of AI for financial decision-making are many. Among them are the following:

AI can automate repetitive tasks

The benefits of using AI in the financial services sector are many. It can automate routine tasks that require human judgment and input, allowing banks and other financial institutions to focus on more productive work. For example, an employee in a bank may spend countless hours updating a customer's information, but a robot can do that job for them. AI can also analyze large data sets in real time, helping them to spot patterns and optimize their processes.

As AI is getting more sophisticated, banks are realizing the benefits. For example, AI is helping banks manage the risk associated with money loaned to their customers. It is using machine-learning algorithms to analyze credit histories and identify patterns that humans may miss. It can also analyze huge data sets in days, providing insights into optimal price rates and market price forecasts with a high degree of accuracy. It has the potential to free up personnel, improve security, and ensure the business direction.

AI can detect suspicious activities

By improving the detection of suspicious activities, artificial intelligence can help financial institutions make more informed decisions about their customers. AI can be trained to identify patterns and make decisions based on accumulated data and analysis of millions of transactions. It can identify behaviors that may be unusual, such as large wire credit transactions, high-frequency counterparties, or unique originators, and combine this information with market information. This technology can also be used to detect emerging threats.

Because financial organizations handle a large volume of personal data and money, the implementation of AI technology into these organizations has many benefits. It can detect suspicious activities, reducing the number of false alerts and allowing human experts to focus on more critical tasks. It can also reduce the risk of a bank or financial institution being the victim of fraud. In fact, financial institutions can expect increased fraud detection with the use of AI.

AI can predict loan borrowing behavior

Artificial intelligence can analyze customer spending patterns and actions to predict how they will borrow loans. This capability is particularly important in areas where traditional credit isn't available. A loan applicant can download an application to analyze their social media activity and browsing history. AI can be trained to recognize patterns that could lead to bad decisions, such as a night owl's post on Facebook. And the results of these analyses can be used to improve financial decision-making for lenders.

AI can also help banks correct gender discrimination by compensating for changes over time and artificially boosting women's loan approval. One lender, for example, used AI to balance its data, ensuring that women earned 30 percent more money than men for equal loans. By retroactively adjusting its data, the lender was able to increase the proportion of loans made to women while maintaining their relative ranking.

AI can automate legal documents

Despite its name, AI can automate legal documents to improve financial decisions. Unlike human lawyers, AI does not perform complex tasks, but speeds up routine tasks and supports better decision-making. AI is trained by collecting data, including legal performance metrics, from various contracts. The data is then labeled to train AI. However, this process is not without flaws. In some jurisdictions, public data is not available and the quality of these datasets can be questionable. This means that AI generative systems may end up overly biased and producing inaccurate results.

Commercial banks are increasingly under pressure to "churn out" complex documents. But this process also increases the likelihood of error-prone data and incorrect information. With automated legal document generation, banks can produce more documents in less time. This means a greater rate of production for all stakeholders. Automation of legal documents also helps reduce human error. Artificial intelligence can automate the creation of legal documents in all sectors, including finance.

AI can scan regulatory documents

For many financial institutions, compliance with regulatory requirements is an absolute necessity. AI can leverage Natural Language Processing (NLP) technologies to scan thousands of documents in a matter of seconds, checking for issues that are not compliant with regulatory requirements without requiring human intervention. Expense reports are one example of a complex document with many compliance risks. AI can scan and identify issues with expense reports without requiring human intervention, reducing the need for manual review.

Because AI is a highly data-intensive technology, it may be vulnerable to cyberattacks, which could impact consumer privacy. Despite this potential vulnerability, the RFI does note several key challenges with AI adoption. The RFI specifically asks for input on cybersecurity issues, managing third-party AI/ML, and other relevant information. Because AI may increase privacy concerns, it is important to ensure the soundness of models.