Benefit of Artificial Intelligence in Finance Industry

Artificial intelligence can benefit the financial sector and even transform the field permanently. This is how artificial and financial intelligence can make a difference.

Artificial intelligence (AI) has already been associated with the video game industry, but financial institutions are beginning to realize that this technology can do much for them. Perhaps the most common use of artificial intelligence modules in the banking industry involves calculating interest rates and residential values. Smart software can request, through historical price charts, the development of a model that more accurately predicts the financial future, taking into account several factors. It is these additional factors that indicate that artificial intelligence can benefit the financial sector.

Mining of Big Data Banks

Historically, pricing models have considered, for example, the seasonal demand to determine the future value of any commodity. Banks have been collecting much more information than this for some time, but only a recent boost to data monetization has forced developers to look at countless other factors. 

Solutions based on artificial intelligence determine the value of physical and investment products, noting the following:

•   As demand for one type of product influences another
•  The price fluctuations of the different investment products among each other.   
• Thegeographical location of consumers making financial decisions
•  Commercial allocation preferences of different investors
•  The trade patterns that shape hourly prices
•  The volatility of prices traded on an open exchange
•  The relative costs of goods and services in different markets

Banks and brokerages have compiled this information for decades, but so far have not had many ways to analyze it. AI modules are carrying large data elements like these and looking for opportunities. In addition, new IoT devices installed at ATM stations help identify patterns of how consumers deposit and withdraw funds. This can help reduce the risk of cash collapse caused by an excess of sudden withdrawal orders granted to the individual physical bank.

AI and the world of creditors

Most consumers are already familiar with the concept of checking their annual credit score. Each time an institution decides to see the credit score of an individual, it leaves a mark called search. Companies can get someone's score when they are applying for a loan or applying for a job.

Soft benefits, such as when a consumer makes an annual credit check while making their taxes, have little influence on a person's overall score. Difficult queries, such as those caused by a person applying for a new mortgage, are much more serious. While sophisticated mathematical models exist to determine the severity of any credit drawdown, they are often left to a high degree of interpretation.

Credit agencies are progressively introducing new scorecard technology, which takes into account potential risk and past performance, to apply their own rules more fairly to consumers. To avoid extending a credit line to someone who can default on a loan, financial institutions, in turn, are building credit risk models based on artificial intelligence. These models use predictive thinking along with self-learning neural networks to determine the total risk of any specific loan.

Neural networks learn the same way people do. Using a database stored in a virtualized file system, risk models can prevent the repetition of past errors. Consumers can receive better rates if a database does not find indications that it is a risky investment.

Simplifying compliance tasks

News services continue to report on these trends in the financial sector. However, computer security experts believe that regulatory and compliance tasks will be the area in which AI algorithms will further change the financial industry. To provide operators with value, any IA needs to have a secure digital backbone network. The data collected for the analysis should also be anonymous in many jurisdictions.

New laws such as the General Data Protection Regulation (GDPR) require that companies be much more open about how they are using customer data. AI software can optimize the process of erasing any personally identifiable information from stored data while automating the reporting process.

From the consumer's point of view, the biggest change will probably come in the form of greater account protections. The same predictive analytics technology that is extracting big data storage systems for actionable financial patterns will also occasionally notice irregularities. As these programs continue to undermine, they will improve by detecting problems and alerting consumers to any errors in their accounts. As a result, regular banking customers will soon be able to take advantage of the benefits of AI technology as well as the institution.

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