When discussing Artificial Intelligence (AI) and Automation, your first thoughts may head towards the manufacturing industry. And you wouldn’t be wrong to do so.
AI and Automation have been used for a long time already in factories and has allowed companies to produce products at a faster rate, for longer, and with fewer errors.
This great success then led other industries to take note of the potential in their own sectors. And they began testing whether software solutions can emulate their own workers’ tasks.
It didn’t come as much surprise when testing was successful. Which then paved the way for hi-tech companies to create more advanced systems that can provide a virtual workforce of robots to complete tasks. By combining AI with Machine learning (ML) and other technologies, the current models are more than capable of analyzing enormous data sets to detect fraud, recognize patterns of behavior and much more.
Automation using RPA and AI
Robot process automation (RPA) is the magic behind the automation of tedious and repetitive tasks. The software is designed to mimic the actions of the user and replicate it as many times as needed. Kyron is one such company whose software has been used by Microsoft to cut down processing times for 3rd party payments by 2900%.
AI software differs because it’s designed to solve problems using cognitive processes such as learning, self-healing and pattern recognition, by using older data sets already processed.
Combining the two technologies together, allows for software that can not only perform the tasks required but also mimic cognitive processes to problem solve and make forecasts.
Transforming The Financial Sector
The financial sector is more than just Wall Street traders buying and selling stocks. Many departments are working together to provide the services required. Let’s take a look at some of the use cases for automation in this sector.
Deciding to grant credit to a customer requires a risk assessment of the borrower. Accounts must be checked, and numerous factors must be taken into consideration, which can be time-consuming, especially when multiple accounts are used, and all the data must be extracted and correlated for the user.
Furthermore, not all potential borrowers have an extensive credit history available. By using AI-powered algorithms, banks can use alternative data to evaluate the potential eligibility of the customer using more sophisticated rules and data.
As a bonus, an AI cannot be biased towards the race, gender or any other factor which may subconsciously swing the decision to grant credit or not.
AI has become better at detecting financial fraud as ML continues to develop and close the gap between financial institutions and criminals.
Credit card fraud has been rampant for a long time and has grown in recent years due to the size of e-commerce and online shopping.
AI fraud software can analyze a credit card owners location and buying history to develop a behavior model, which can then trigger an alert if a transaction happens outside of the regular pattern. Such as a purchase in a foreign country, or a product that’s expensive and doesn’t fit previously purchased models, such as jewelry or perfume.
Cyber attacks are on the rise as data records are increasingly becoming one of the most sought after commodities. One of the biggest drains on a security teams resources are false positives, which look like an attack or intrusion but turn out to be non-threatening.
But security teams must still investigate and report on each attack which can be time-consuming. Automation can provide automatic responses which investigate, report, and if relevant, escalate for an employee to act upon.
Trading with AI
Many trading and investment companies are utterly reliant on AI software for their data management. By analyzing historical patterns for trends and utilizing machine learning capabilities, data scientists are outperformed at predicting future market values. AI’s are also able to perform the tasks within minutes or even seconds.
For day traders, AI’s can be used to provide suggestions on outcomes and analyze the current market conditions, helping to decide whether to invest or not.
If you’re still in doubt about the usefulness of AI and the financial industry we’ve barely even scratched the service. AI programs can also be used for customer service teams, sales and retention efforts, as well as compliance, which is why most finance businesses are investing in their own automation efforts.
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