Artificial intelligence (AI) and machine learning have come a long way, both in terms of adoption across the broader technology landscape and the insurance industry specifically. That said, there is still much more territory to cover, helping…

Artificial intelligence (AI) seemingly has been discussed everywhere over the last few years, and now it’s made its way into the commercial insurance industry. Organizations are using AI and machine learning for everything from streamlining operations to offering more personalized care and better customer service. There is an increasing sense of urgency about getting started on the AI journey. The question is how. Do they develop a custom solution in-house or purchase a third-party solution…

The insurance industry – one of the least digitalized – is not surprisingly one of the most ineffective segments of the financial services industry. Internal business processes are often duplicated, bureaucratized, and time-consuming. As the ubiquity of machine learning and artificial intelligence systems increases, they have the potential to automate operations in insurance companies thereby cutting costs and increasing productivity. However, organizations have plenty of reasons to resist…

The insurance industry is regarded as one of the most competitive and less predictable business spheres. It is instantly related to risk. Therefore, it has always been dependent on statistics. Nowadays, data science has changed this dependence forever.

Now, insurance companies have a wider range of…

This post highlights a number of important applications found for deep learning so far. It is well known that 80% of data is unstructured. Unstructured data is the messy stuff every quantitative analyst tries to traditionally stay away from. It can include images of accidents, text notes of loss adjusters, social media comments, claim documents and review of medical doctors etc. Unstructured data has massive potential but has never been traditionally considered as a source of insight before.…

 Consistency is critical to business since it ensures results that can be tangibly seen. In insurance industry, the policy is profitable for the insurer only when the policy persists within the insurers’ portfolio for a certain period of time. Typically Life insurance has a longer persistency period to recover the costs and become profitable compared to a general insurance portfolio.…

As part of a deeper dive into domain specific analytic careers, we are exploring the Insurance industry. The below data & charts gives context & explains the opportunities for an analytics careers in Insurance.

Our first examination involved analyzing the top insurance companies hiring for analytics related positions.  The below chart shows the open job postings where the title was “Data Science” or “Analytics” or “Actuary” & plural or related word. We found a total of 185…

Relationships are built on trust and mutual understanding – if a company wants customers to trust them with their data, the company must foster that trust. Data governance and sensitivity about your customers’ data must be enforced internally and communicated externally – to your customers.

When…

Relationships are built on trust and mutual understanding. Building a 360 degree customer data profile facilitates the marketers’ understanding of their customers.  This in turn, helps marketers provide their customers the best experience and service, target product offerings, and produce relevant communications. The key to building a 360-degree customer profile is aggregating as much relative data as possible.  Centralizing the 360-degree profile in an easily accessible and robust…

Excellent customer communications is now a recognized component to drive sales and give Insurance companies the competitive advantage. Here are some tips when utilizing analytics to solve marketing solutions while keeping the customer in mind:

• Create a single profile of the customer. Use big data and data management strategies, such as refining existing platforms to provide the ability to…