AI News, Self artificial intelligence

The Growing Impact of AI in Financial Services: Six Examples

Just as many other technological advancements, Artificial Intelligence came to our lives from the pages of fairy tales and fiction books (think of the Tinman from The Wizard of Oz or Maria from Metropolis).

Also, AI makes it possible to provide personalized suggestions for desired dates, routes, and costs, when we are surfing airplane or hotel booking sites planning our next summer vacation.

Image analysis and various administrative tasks, such as filing, and charting are helping to reduce the cost of expensive human labor and allows medical personnel to spend more time with the patients.

Digital banks and loan-issuing apps use machine learning algorithms to use alternative data (e.g., smartphone data) to evaluate loan eligibility and provide personalized options.

Enormous processing power allows vast amounts of data to be handled in a short time, and cognitive computing helps to manage both structured and unstructured data, a task that would take far too much time for a human to do.

US leasing company, Crest Financial, employed artificial intelligence on the Amazon Web Services platform and immediately saw a significant improvement in risk analysis, without the deployment delays associated with traditional data science methods.

For a number of years now, artificial intelligence has been very successful in battling financial fraud — and the future is looking brighter every year, as machine learning is catching up with the criminals.

Fraud detection systems analyze clients’ behavior, location, and buying habits and trigger a security mechanism when something seems out of order and contradicts the established spending pattern.

Intelligent Trading Systems monitor both structured (databases, spreadsheets, etc.) and unstructured (social media, news, etc.) data in a fraction of the time it would take for people to process it.

The predictions for stock performance are more accurate, due to the fact that algorithms can test trading systems based on past data and bring the validation process to a whole new level before pushing it live.

Voice-controlled virtual assistants powered by smart tech like Amazon’s Alexa are also gaining traction fast, which is no surprise: boasting a self-education feature, they get smarter every day, so you should expect tremendous improvements here.

The biggest US banks, such as Wells Fargo, Bank of America and Chase, have launched mobile banking apps that provide clients with reminders to pay bills, plan their expenses and interact with their bank in an easier and more streamlined way, from getting information to completing transactions.

Artificial intelligence-enabled software verifies data and generates reports according to the given parameters, reviews documents, and extracts information from forms (applications, agreements, etc.).

Employing robotic process automation for high-frequency repetitive tasks eliminates the room for human error and allows a financial institution to refocus workforce efforts on processes that require human involvement.

This will make managing personal finances exponentially easier, since the smart machines will be able to plan and execute short- and long-term tasks, from paying bills to preparing tax filings.

We can also expect to see better customer care that uses sophisticated self-help VR systems, as natural-language processing advances and learns more from the expanding data pool of past experience.

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