AI chatbots (also referred to as smart agents or virtual support assistants) powered by advanced machine learning are increasingly dominating customer service industries – think Apple Siri and Amazon Alexa as two examples.
These intelligent bots assist customers by providing step-by-step instructions to place orders, while others increase the average order value by cross-selling products that complement existing items in customers’ carts.
1. Identifying Trends
Artificial Intelligence (AI) is revolutionizing stock trading by automating processes and tasks and making human traders less vulnerable. Chatbots powered by AI are capable of collecting and processing data faster and more accurately than humans do, helping predict trends and identify opportunities more accurately than humans could ever hope.
AI stock trading assistants provide an effective way for traders to save time and focus on higher value activities, while improving customer experiences, cutting costs and increasing productivity.
Many companies use chatbots to answer customer inquiries quickly and direct them towards relevant resources, like bank’s AI virtual assistant can. Unfortunately, even the best chatbots cannot always meet user needs or unexpected queries; providing an alternate channel of communication and smooth handover to agents will prevent user frustration. Startups such as Imbee, Sentimer and Bitext prioritize interactions in natural language while using contextual metadata to customize conversations and deliver more pertinent information.
2. Identifying Opportunities
Chatbots offer brokers time savings by automating many tedious, time-consuming tasks that traditionally required human labor – like monitoring customer data or assessing risks. In stock trading context, chatbots can identify opportunities by constantly monitoring customer records; additionally they can assist them in assessing risks. By automating such tasks for them, chatbots free brokers from doing these jobs themselves manually and save valuable hours per broker per transaction.
As a result, they can become more efficient and productive, freeing up human capital to focus on higher value activities. The more information the chatbot gathers, the better it becomes at understanding user queries and responding appropriately.
There are various kinds of chatbots, each created to serve a particular function. From retail bots that assist with picking up groceries to weather bots that offer detailed forecasts for tomorrow or next week.
AI technology has also been adopted by the securities industry to enhance communications between customers and investment processes as well as operational functions. BBVA, for instance, implemented an AI virtual voice assistant named Blue to assist its clients with queries about shares or investments; this tool analyses news articles and social media to offer predictions that enable users to improve trading performance.
3. Identifying Risks
AI chatbots that can predict trends can provide more informed trading decisions and lead to reduced investment risk and greater profits. It is important, however, to be mindful of both risks and opportunities associated with using AI to trade stocks.
Task-oriented chatbots like Apple’s Siri and Amazon’s Alexa are currently the most widely-used type of bot. These use rule based, NLP, and machine learning to respond quickly to specific inquiries in an automated fashion.
Problems arise with these chatbots due to their inability to accurately gauge the context, particularly when handling PII that requires explicit user consent under GDPR.
Data-driven and predictive chatbots may offer an effective solution, learning from past interactions to become more capable, personalized and sophisticated – improving customer experiences in turn. However, such approaches may present potential security risks with open domain chatbots which collect personal information (PII).
4. Identifying Opportunities
AI Chatbots as virtual trading assistants can assist businesses by helping identify and process leads that generate qualified sales opportunities, managing appointments such as work meetings or interviews, sending reminders for appointments, canceling sessions if needed and even scheduling new sessions if necessary.
eCommerce brands can use chatbots to reduce customer support costs by diverting calls away from costlier channels, with chatbots handling routine queries while connecting users with human agents for complex or unexpected inquiries. This helps decrease churn and enhance user experience.
Equbot is an AI-powered stock market bot that scans your portfolio tickers in real time to identify trading opportunities based on real time patterns. Equbot provides comprehensive features including paper exchange simulation and integration with multiple brokers such as Interactive Brokers. Furthermore, Equbot can predict market shifts using historical price data analysis as well as social media analysis; making it an indispensable asset for traders looking to boost returns.