Managing risk is the cornerstone of the insurance industry. For organizations to fully manage risk, analysis of all data at their disposal is crucial. Technology may not make the actuarial and underwriter obsolete, but it can give these professionals the competitive edge in a market where the lowest premium with maximum cover is all that consumers want to see. In an age where data is streaming in from a diversity of sources, simultaneously analyzing and correlating data, often in real time, has gradually slipped out of the human capability.
Business Value From Diverse Data Sources
Big data is the term for the collective information from a variety of sources that is streaming in at variable velocities and has swelled the data stores of organizations. Much of this data is beyond the traditional operational or transactional data gathered by an organization. Big data includes the 80% of data which is semi-structured or unstructured. In the past it could not be correlated with existing structured data to identify meaning relationships and derive knowledge. Hence much of this data was ignored or discarded.
Insurers are inundated with data beyond their traditional archives. It is now streaming in from social media, call center emails, website logs and beyond. Making sense of all this information was not just challenging – it was virtually impossible until now. Big data tools, or analytics, are able to meet this challenge by extracting, transforming and loading data from various sources for better business intelligence and decisions beyond the transactional history of an organization.
Managing Risk With Big Data
The key for insurance organizations is to offer customer-focused solutions while optimally managing risk. A blanket policy cannot apply across different products and for all customers irrespective of individual risk profile. But analyzing data for a more consumer centric approach to cover is time consuming resulting in a lag that can be expensive and frustrating. It is about retaining and growing market share while protecting against future losses.
The insurance industry has no shortage of data, but its value can only be appreciated when it can provide key insights that lead to practical solutions. It requires a deeper analysis of data that on its own is of little use unless it can be integrated into business intelligence solutions. In the insurance industry it means knowing where the risk lies while maintaining a competitive edge. It also means detecting fraud not only after it happens but also predicting and preventing it before the fraudsters can take action.
Big Data For Growth
Big data tools can reduce the time to market by rapidly providing key insights, sometimes even on the fly, for business intelligence. It is not just about managing risk. Big data can extend to better customer service, aid with customer retention and reduce operational expenses with efficient strategies and solutions. Similarly it can play a pivotal role in product cross-selling by offering the right product to the right customer at the right price.
Equally important as managing risk and deploying customer centric solutions is the need to reduce costs in the insurance industry which faces tight margins with ever increasing competition. Profitability has to extend beyond increasing sales and minimizing losses through fraud to more efficient and streamlined operations that adds to the bottom line. Big data can provide the key insights on the fly that can be implemented today while relevant rather than being spotted tomorrow when the market has already changed.