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How AI Can Turn Traditional Businesses Into Stand-Out Enterprises

DZone 's Guide to

How AI Can Turn Traditional Businesses Into Stand-Out Enterprises

Look at growth strategies in finance industries and see how AI can turn traditional businesses into stand-out enterprises.

· AI Zone ·
Free Resource

Artificial Intelligence is emerging as a key factor within the finance industry, toward increasing revenues, and toward achieving business goals. From providing value-based business strategies, improved customer experiences, increased revenue generation, and reduced costs, AI is establishing itself as a significant technological advancement to achieving business success. Top management is now viewing AI to assess business areas that are poised to substantially benefit through advanced analytics and deploying it to achieve the desired outcomes.

The natural evolution of technology for business benefits that took us from paperwork to the internet is now swiftly transforming toward AI, and the Finance industry is no exception. The heavy volumes of data involved in the finance sector make this technology a primary resource toward business benefits. The process of pattern establishment and identification is a key advantage that has attracted increasing attention toward the analytical capabilities of this technology. Although AI comes with innumerable benefits for the finance industry, there are also some concerns with regard to trust, bias, and regulatory compliance, hence it is prudent to view the technology as a means to assist human endeavors rather than the replacement of human involvement.

Classifying Artificial Intelligence

AI can be categorized into two broad categories: narrow AI and strong AI.

Narrow AI

This type of Artificial Intelligence is a specialized form of technology that looks into a particular area of the business and fulfills a specific duty. The process is highly specialized, and the deployment of the technology offers only those specific solutions. The tasks assigned to AI are narrow, and they adhere only to their set protocol. An example of narrow AI is "Appleā€™s Siri." This intelligent technology is designed to gather information from the internet and hold meaningful conversations with a human. However, the technology is very specific and narrow in its approach, wherein it is only designed to address the specific demands of its system. Any requests that go above and beyond to offer holistic solutions cannot be accomplished.

Strong AI

As the name suggests, this version of Artificial Intelligence is more holistic in nature with a wider purview and the ability to offer solutions that are all-rounded and meaningful. Its capability and functionalities are more encompassing and of a higher standard. It is geared toward offering analytics that extend beyond specific areas by collecting information from various arenas to offer an overall solution. Strong AI is a close replication of the human mind and is capable of conducting analysis in an error-free fashion.

 

Through the use of chatbots, personal assistants, machine learning, and cognitive computing, artificial intelligence can be specifically beneficial within the following sectors of the finance industry:

  • Stock Trading
  • Regulatory Intelligence
  • Financial Planning Services
  • Banking
  • Accounting
  • Lending and Loan Management
  • Financial Security
  • Customer Service
  • Sales and Financial Products
  • Hedge Funds 

AI in Stock Trading

There was a time when stock trading was a manual business that was done without the use of computers. Over the years, the trading business has evolved through computerization and it is now being revolutionized through AI.

The Challenges Before Artificial Intelligence

With standard technologies that lack innovative capabilities, the stock trading industry has been facing challenges such as:

  • Lack of identification of patterns: Human involvement makes identification of patterns a fairly sub-standard phenomenon. This is usually done in special case scenarios and even then is prone to slips and errors. Unprofitable transactions are rarely examined and identified.
  • Dependency of Operational Transactions: Unfortunately, the dependency of operational transactions on human execution restricts timely operations and sometimes results in a loss of large sums. The availability of stock traders is another factor that hinders swift trading.
  • Difficulty of Fundamental Analysis: Human attempt at fundamental analysis to identify the strength and weaknesses of the market is usually undertaken in a sporadic and inefficient manner due to the large volumes of data required to analyze. This leads to market misconceptions and high rates of emotionalism.

 The Solution AI Offers

With markets shifting at the speed of light and gigantic volumes of calculations, there can be no doubt that AI has limitless potential toward improvisation in this sector. This technological innovation is geared to transform stock trading as we know it.

  • Pattern Identification through Machine Learning (ML): Machine Learning is one tool of artificial intelligence that can create brand new systems to swiftly spot patterns and notice traction with suggestions for improvisation through its financial applications. This further includes the identification of unprofitable transactions.
  • Operational Performance through AI: The deployment of AI techniques can completely control operational transactions with no need for human intervention. This eliminates the dependencies and delays that are caused by human execution.
  • Predictive Analysis Capabilities: AI technologies can further predict patterns and offer suggestions toward the same. This is done through automated and extensive research from social media and other online platforms that are cumulatively analyzed to gauge market feelings and trends. These automated research tools can then make forecasts about likely market movements.
Topics:
artificial intelligence ,finance ,banking ,startups ,business ,strategies ,ai ,fintech ,stock trading

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