<ul>
<li> 
<strong>Enhanced Regulatory Compliance</strong>
<p> 
Due to the increase in cases of fraud and scams, banks are being coerced by regulatory bodies to have strict regulations. To be appropriately compliant with these regulations, Al comes to play. Relying on cognitive fraud data, Al observes customer behaviors, track transactions, identify dubious activity, and keep up with suspicious accounts. 
Al also helps businesses remain up to date with compliance rules and regulations by going through the compliance requirements and identify any changes through deep learning and natural language processing. Banks can, therefore, remain updated on ever-evolving regulatory requirements and align their regulations according to them.
Regulations governing the privacy and portability of information will determine the relative ability of financial and non-financial institutions to adopt Al, thus becoming as important as traditional regulations to the competitive positioning of firms.
</p>
 </li>
<li> 
<strong>Prediction of Future Outcomes and Trends</strong>
<p> 
With its ability to predict future scenarios through analysis of past behaviors, Al helps banks predict future outcomes and trends. Banks can identify fraud, detect anti-money laundering patterns, and make customer recommendations. Money launderers, through a series of actions, portray that the source of their illegal money is legal. With its power of Machine Learning and Cognition, Al identifies these hidden actions and helps save millions for banks. Similarly, Al can detect suspicious data patterns among humungous volumes of data to carry out fraud management. Further, with its vital recommendation engines, Al studies past to predict the future behavior of data points, which helps banks to up-sell and cross-sell successfully.
</p>
</li>
<li>
<strong>Cognitive Process Automation</strong>
<p>
This feature enables automation of a variety of information- intensive, costly, and error-prone banking services like claims management. Furthermore, it secures ROI, cuts costs, and ensures accurate and quick processing of services at each step. Cognitive process automation fundamentally automates a set of tasks that improvises upon their previous iterations through constant machine learning. 
Realistic interactive interfaces: Chatbots identify the context and emotions in the text chat and respond to it most appropriately. These cognitive machines enable banks to save not only time and improve efficiency but also help banks to save millions of dollars as a result of cumulative cost savings. Bank of America's chatbot Erica is currently available in 10 
states. 
</p>
</li>
<li>
<strong>Effective Decision-making</strong>
<p>Cognitive systems using Al technology think and respond like human experts, provide optimal solutions based on available data in real-time. These systems keep an inventory of expert information in its database called the knowledge database. Bankers use these cognitive systems to make strategic decisions. 
</p>
</li>
<li>
<strong>Cost Reduction 
</strong>
<p>
Cost reduction is a significant benefit of the integration of Al in the financial service industry. In the next few years, banks will save billions of dollars due to the application of Al. Banks will further save on time and revenue spent to identify, digitize, and onboard document templates through the automation of the process by Al technology. 
Human error is a leading cause of financial data breaches. Unfortunately, mistakes are costly and inevitable. Considering that Al is much better at managing unstructured data, there's a reduction in error rates and, subsequently, saving the cost to resolve the errors. 
</p>
</li>
<li> 
<strong> Artificial Intelligence and Risk Management </strong>
<p>
The impact of Al in financial services cannot be readily estimated when it comes to risk management. Enormous processing power allows the handling of vast amounts of data within a short period. Cognitive computing supports the management of both structured and unstructured data, a task that would take far too much time if done by a human. Algorithms analyze the history of risk cases and identify early signs of potential future issues. 
In an era of instant payments, the idea of waiting for a purchase to "clear" will soon seem as antiquated as an abacus. Increasingly, consumers expect their accounts to reflect when they buy something instantly. At the same time, cybercriminals are laboring to find the latest, most effective way of stealing someone's sensitive bank data. 
Banks are using Al to improve both speed and security to combat cybercrimes. 
Artificial Intelligence is changing the norm of financial services, weakening the bonds that have held the parts of incumbent financial institutions, and opening doors to entirely new operating models. Al will empower banks by automating its knowledge labor force and make the automation process intelligent enough to eliminate cyber risks. Al will enable banks to make use of human and machine efficiency optimally to drive operational and cost-effectiveness, and deliver personalized 
services. 
</p>
</li>

</ul>