Executive Q&A: Data, Cloud, and the Insurance Industry | Transforming Data and Intelligence

Executive Q&A: Data, Cloud, and the Insurance Industry

From integrating data silos to creating powerful customer experiences, insurance companies are facing many challenges. Venkitesh “Venki” Subramanian, vice president of enterprise resource management at Reltio, spoke with us about the results of the company’s latest survey.

Up front: Let’s start with the history of your research. Who was involved and why did you focus on insurance?

Venkitesh Subramanian: Our Insurance CIO Mega Trends report surveyed 100 leaders from the North American insurance industry. More than two-thirds of respondents represent organizations with revenues of more than $1 billion. The majority of respondents (64 percent) identified as working in information technology and data management within insurance. The report is based on a survey conducted by WBR Insights of 100 technology leaders from the insurance industry in the US and Canada; 29 percent of respondents are C-level executives.

When it comes to technology issues, what are insurance leaders most concerned about?

The survey identified top insurance leaders facing business challenges and key challenges in a variety of areas, including:

  • Changing customer buying preferences
  • Changes in customer loyalty are associated with new product offerings
  • Increased pressure on traditional types of activity
  • Streamlining customer relationships through data increases the security and privacy of personal data
  • The need for increased automation and intelligent services

This poses many technical challenges. However, one of the biggest challenges that insurance companies face is an unstructured and fragmented IT landscape. It’s not uncommon for an insurance company to have dozens of policy, claims management, or other key processes across different businesses, leading to data disparities, inefficiencies, and customer inconsistencies.

Does cloud technology solve these problems?

By 2025, more than 80 percent of businesses will have a cloud-based solution and total investment in cloud technology will exceed $1.5B according to Gartner studies it was released in November 2021. The cloud is not an option but a necessity that goes hand in hand with innovation and providing scalable solutions to support business needs. This adoption of the cloud will lead to further fragmentation of the data landscape, and will also create unique opportunities for organizations to use cloud-based solutions to solve data management challenges. Using cloud-based databases such as Amazon’s DynamoDB or Google’s Cloud Spanner, the combination of cloud availability, data lakes, and machine learning capabilities provides the ability to create highly scalable solutions, in real time.

Reltio has become a trusted partner for insurance companies as they manage customer, policy, and claims information across a variety of history-based systems. Using cloud-delivered SaaS MDM, businesses can unify and clean up multiple, complex issues into a single source of reliable information — in real time. Insurers can better see their customers so they can move from traditional to customer oriented. API-driven integration, easy integration and a collaborative ecosystem allow insurers to launch new services and drive growth faster.

How do master data management (MDM) systems and solutions currently support insurance in particular? Is there an opportunity to upgrade MDM for these factories?

Companies spend a lot of money on digital transformation. It is important for CIOs and CDOs to ensure that this is going well by supporting them with the right technology and data. CDOs are concerned about data issues and the risk of disruption from new Insurtech companies.

Many insurance companies use previous MDM technologies or have developed their own solutions to create a single view of their customer, as well as information about policies such as policies and insurance products. Unfortunately, these systems cannot continue to grow; they cannot provide the data with the speed and accuracy required. Also, they are often inconsistent and expensive. A modern, flexible MDM solution is needed to solve these problems.