AI Articles and Analysis about Customer service

Chatbots are one of the most talked-about uses of natural language processing (NLP) software in business. Some of the most common application areas for chatbots include customer service, healthcare, and financial advisory.

Speech recognition is an AI technology that can allow software programs to recognize spoken language and convert it to text. A subset of speech recognition is voice recognition. Voice recognition is an AI-enabled capability that enables a software algorithm to match the identity of a customer to their voice. 

Artificial intelligence is transforming a variety of banking functions and allowing tech startups to compete with some of the largest banks for market share of key services, including lending and wealth management. Business news and media sites have been heralding the downfall of the banking industry as we know it because fintech companies are going to feel comfortable leveraging AI long before banks.

Credit card companies could make use of AI applications across multiple business areas. AI-based fraud detection is among the most widely discussed AI applications in the financial sector, and it seems to work for credit cards similarly to how it works for banks. Additionally, credit card companies and financial institutions could use AI software to improve customer service and develop customer-targeted marketing campaigns.

Many business processes in retail banking are ripe for automation with AI. All types of banks may appreciate the use-case of payment processing automation and fraud detection, but retail banks may also benefit from automated credit scoring and customer service chatbots.

The financial sector has been an early adopter of AI. It is likely that the use of algorithms in trading and the fact that most large financial firms already have teams of software developers aided the transition into data science and AI applications in the industry.

Machine learning has far-ranging applications in the finance space broadly from document digitization to document search, chatbots to fraud detection. The insurance space in particular, however, stands to benefit from AI and machine learning applications in a few unique ways. They could help insurance firms with a challenge that’s at the forefront of the insurance world: attracting and meeting the needs of millennial customers.

In recent years, there seems to be a sense of urgency for banks to go digital and expand into new communication channels. In ten years time, physical brick and mortar banking might not be the preference of the majority of customers. To attract younger millennial customers, banks seem to be realizing the need to understand their preferences and interact with them in the way they want to be communicated with.