Siloed Data is a major issue for Insurance companies, data that is scattered, unstructured and unleveraged. Data Silos can create conflicting versions of truth which is even more alarming in the Insurance industry. These disparate data sets come up as a major hindrance in unraveling the true potential of big data and advanced analytics such as machine learning, deep learning and artificial intelligence.
A recent survey conducted by PwC highlighted a few key issues in the current day Insurance industry -
- Lack of technological innovation
- Stringent Regulations
- Constantly decreasing premium rates
- Mild interest rates
- Varying customer behavior
- Increasing competition from newbies in the market
Insurance companies need to leverage the "Power of Data" to transform and drive profitability. Data strategies require investments and need to be revamped to thrive in tomorrow's markets.
Breaking down data silos
Many insurance companies have multiple data silos spread across different departments of the business. This usually happens due to the independent operations of departments, product teams, lines or businesses which focus mainly on their own data needs.
Data owners usually place barriers in terms of sharing different data, using slow and cumbersome processes which hinder growth and development of the company effecting its inefficiency.
Data carriers should focus on how to break such silos and look at the aggregated view of various aspects of the business by creating a modern data management architecture.
The proper data pipeline helps in –
- Data teams act like leaders and enablers, focusing on the proper sharing and use of data.
- Centralized business analytic teams create their own databases unique to their needs and demands, to derive faster and more accurate insights which they can use, further.
The need to aggregate
Data silos create a gap between the data architecture of an organization making coordination between different departments an arduent task. They prevent data carriers from gaining an overall perspective on risk assessment, customers, product performance and other spheres.
According to a survey conducted by Willis Tower Watson in the year 2016, it was revealed that the deployment of big data varied greatly in different parts of insurance. The survey concluded that three areas had the maximum potential for growth-
- Pricing and underwriting
- Potential losses and claims
- Understanding customers
Developing the process of underwriting
The process of underwriting is being developed faster due to the rapid shift from employment of underwriters to development of analytical teams. New technology is bringing new insights to the industry and is being highly accepted.
Efficient use of new technology
It is not enough for a company to just provide its workforce with new and developed technologies. Innovation would prove to be of no use if the maximum output cannot be derived effectively. The workforce should be trained in a way that they are able to comprehend and work with the extensive tools provided to them.
Disadvantages of tight security
The large number of regulations governing the insurance industry sometimes hinder the development of a company. For an effective implementation which benefits both parties (government and businesses), data science should be incorporated into the thought process of such regulations. It is important to have good security solutions but a solution that hinders the effective sharing of data will hamper the organization’s progress.
XcelPros works with the large insurance providers and applies Data Science to solve major issues. Talk to our experts today to learn more.