AI Articles and Analysis in Finance

Along with the rise in popularity of chatbots and simple conversational interfaces, there is growing interest around other natural language processing (NLP) capabilities in the banking, finance, and insurance industries.

When it comes to the possibilities for AI in the insurance space, it may seem like machine vision is an inevitable choice for any insurer looking to have as much information on the insured property, car, or people as possible. However, this may still yet to be the case for many insurers. The insurance space has a relative lack of case studies for this type of AI software. This may indicate a lack of demand from the insurance industry or a lack of traction on the part of the technology's use in insurance.

The applications of natural language processing (NLP) have been increasing as more companies find uses for their text data. This includes insurance companies with large stores of data from claims and customer support tickets.

Health insurance fraud may prove especially pressing due to the opioid epidemic, and thus routing out fraud could be of greater importance in the coming years.

The conversation surrounding machine vision can sometimes feel dominated by facial recognition, especially for banking. Banks are necessarily concerned with security and customer service, so it follows that facial recognition, which could help with both, would prove of interest to them. 

The insurance sector is highly competitive, and there seems to be a consensus among experts that customers in the industry favor insurance products that are tailored to their unique needs. Large insurance firms could deliver personalized customer experiences and improve their operational efficiency by adopting AI.

Banks and investment organizations usually have large research teams that are tasked with investigating and monitoring events that might affect financial trading markets. Investment research is a business function in these firms and is a fundamental part of what is required from analysts, equity managers, investors, and traders.

The insurance industry is making use of various artificial intelligence applications to solve business problems, but perhaps the most versatile is predictive analytics. The ability to aggregate data from disparate sources for business intelligence allows business leaders in insurance to inform important decisions across departments.