“Much of the innovation in the insurance industry in recent years has been about creating new products that are delivered in old ways. Digital is the missing link. By combining the possibility of digital with the desire to innovate, insurers can create new revenue streams — serving new customers in areas that were previously inaccessible,” according to the Boston Consulting Group.
This sentiment underscores that the mere presence of the right staff, organizational processes, and technology don’t automatically drive change. Rather, it is when insurance companies take a strategic approach to implementing each of these three segments in a thoughtful way that fosters alignment and collaboration will they truly be able to undergo digital transformation and accelerate innovation.
To succeed, insurance companies need to master more intangible concepts, like agility, in order to respond to the ever-evolving competitive landscape with flexibility and speed. It also enables teams to adapt to meet the rapidly changing needs of customers and move from project development to production with ease.
In order to sustain meaningful change when it comes to improving operations and customer service, reducing fraudulent claims, and optimizing sales and marketing, insurance companies need a collaborative data science platform to help support the aforementioned initiatives. Here are a few ways that Dataiku helps support insurance companies from a people, process, and technology perspective. Dataiku:
People
- Empowers both coders and non-coders alike to access and develop a stronger understanding of data and how it can improve their workflows
- Enables key stakeholders (e.g. different analysts across pricing, claims, fraud, underwriting, and other business units, as well as actuaries, data scientists, data engineers, IT specialists, and team leaders) to collaborate seamlessly to minimize information bottlenecks and handovers
- Enables business users to develop and productionize projects with automated scenarios through an end user computing environment (with limited IT support)
Process
- Offers an alternative to spreadsheets so data exploration and analysis can more easily be scaled up to more sophisticated machine learning projects
- Allows actions to be logged and data pipelines to be viewed in a transparent way, enabling regulatory compliance to be monitored more real-time (which is helpful to avoid surprises during an audit)
- Automates processes on central servers using time-based triggers or changes in the underlying data, expediting execution times and removing key person risk associated with end user computing solutions
Technology
- Provides a safe, collaborative development environment with the key tools to implement advanced enterprise capabilities in a governed and controlled way, which is key in the highly regulated insurance space
- Enables teams to avoid duplicate work by offering functionalities from world-class open source projects
- Helps insurance firms execute on their AI strategy by including capabilities for the entire development life cycle, from data wrangling to monitoring models in production
According to Gartner, “Throughout the COVID-19 crisis, the majority of organizations have been maintaining or even increasing their investments in artificial intelligence (AI), according to polling results from a Gartner webinar in May 2020.”* For insurance firms, not investing in data science capabilities now could be a costly mistake, reducing their ability to understand and adapt to market needs. Not only will the investment open the door to improved levels of productivity via automation, but it can simultaneously help cut costs, improve security and governance efforts, and generate high-quality, innovative projects.
*Gartner: Debunking Myths and Misconceptions About Artificial Intelligence, 2021, Saniye Alaybeyi, Pieter den Hamer, 10 September 2020