Insurance analytics unlocks profound insights for insurers to make sense of their data. Without analytics, insurance professionals spend many man hours pouring over a combination of excel spreadsheets and may still rely on gut decisions when making changes to the business.
WaterStreet Company offers Business Intelligence for insurers to apply data analytics. The solution brings insurance data together across silos of the business, offering advanced learnings to empower the company’s decision making within one unified solution.
What is Insurance Analytics?
Insurance analytics is the practice of deriving insights by visualizing complex insurance data. Insurers are able to make predictions on where the data is headed and decisions are dedicated to improving bottom line profits. Many roles in the insurance business have reason to access insurance analytics, from claims and accounting managers to executives and product managers.
Without an analytics solution, insurers have far too much data to manually understand. Experts in understanding this data are required to spend countless hours reviewing historical performance, comparing against daily performance in a painstaking effort that requires intense time and comes with inefficiencies. Even the most experienced insurance data expert can feel overwhelmed recommending decisions and many businesses still today respond impulsively to positive and negative news, steering the business into an unknown territory.
It’s important for insurers to use a specialized solution for insurance analytics. Without the necessary dashboards and reports developed by a solution provider experienced in the insurance industry, insurers may spend excess resources customizing the analytics solution. This is why WaterStreet Business Intelligence is built by insurance professionals for insurance professionals with all the necessary planning to correctly interpret insurance data.
What is Insurance Big Data?
Insurance Big Data is an industry term which describes data sets that are too complex for people to review in a siloed method.
When a carrier gathers data across thousands of policyholders and over several years, it becomes too much to digest without advanced analytical features. The carrier’s underwriters, accountants, agencies, and many other shareholders access this data throughout the policy lifecycle, making use of it according to each job function.
For carriers to make the most of the data, they must have the ability to store the data in un-siloed ways. Gathering data within a single unified solution opens up new possibilities to analyze the data through reporting functions and identify gaps in your data where third party providers can help offer context.
Uses of Insurance Analytics
Insurance data analytics expands across the company. The power behind a company’s Big Data can be unlocked in structured, thoughtful ways.
- Identify inefficiencies in the quote to policy process and staffing issues.
- Identify bound policies with the amount of days bound outstanding to progress to next steps.
- Review policy cancels to spot trends in why cancellations may increase and address pending cancels to better manage retention rates.
- Review quotes outstanding when the business experiences growth to monitor the performance of new products.
- Review the quote to bind ratio for tracking goals with close rates.
- Easily monitor and see changes in claims activity for specified time periods.
- Measure the causes of losses and exposures to determine what is driving the loss ratio, greatly saving time determining which products have experienced losses.
- Easily filter and sort through expense summaries to quickly filter and represent claim payment transactions.
- Gain a snapshot of earned premium and losses per agency to gauge how each is performing.
- View the key qualitative measurements across agencies to compare year over year.
- Review counts and ratios for policies quoted and bound over chosen time ranges across agencies.
- Prepare to discuss performance with agencies by easily pulling transaction activity counts for current year, prior year, growth rate, cancellation rate, renewal retention ratio, cancel counts and more.
- Gain a detailed analysis of written premiums for all transactions in force for desired date ranges.
- Review breakdowns and subtotals for specific items at the state level and product level.
- See directly where revenue is coming from across all transactions.
- Compare seasonality and annual growth to review trends across the year.
- Identify and track goals across various factors, including earned vs unearned premiums, coverages, perils and fees.
- Review ledger transactions by type of premium, fee, and tax within desired time ranges to validate ledger transactions.
- Stay on top of aging homes and roofs to re-order inspections, adjust replacement costs and manage risk exposure.
- Review maps to explore concentrations of risk by city, county and state lines while comparing the data by coverage limits, agency and property location.
- Review the total insured value to compare pricing between different counties, proximity to coast lines, urban vs rural properties and more against the bound total insured value.
Insurance Analytics Trends
Insurers today are turning towards cloud software. Cloud solutions are updated over time for flexible and constant improvements, enhancing the usability of visualizations and catering to exactly what your insurance business needs to grow.
Underwriting has evolved to take many factors into account when assessing risk. Trends data in measuring risk once relied on ZIP codes, but now drills down much deeper to customer behavior. Insurers today are turning towards the Internet of Things to better understand the risk of one’s home and auto behavior as well.
Insurers are also becoming more adept at identifying fraud through insurance analytics. By comparing claims and underwriting trends in visualizations, managers are able to better spot suspicious activity and many solutions provide algorithms for automatically flagging anomalies.
Insurance Big Data In Action
Insurance Big Data has many uses. Binding a policy is a common practice that pulls data together and can be improved with P&C Insurance Technology.
Before binding a policy, the policyholder has filled a detailed application and awaits final approval, possibly requiring an inspection.
Third party real estate data is commonly used when binding for home insurance. Telematics pertains to data offered through communication technology, such as with GPS data for auto insurance. As the insurance industry evolves, more data will become available through third party vendors for offering greater context to the binding process.
All carriers today gather this data, but not all put it to use at its full potential. Big data is the premise that your data has become too “big” for average employees to understand without the help of advanced features that can combine all data into one manageable location.
WaterStreet Insurance Analytics
The WaterStreet Business Intelligence Platform improves management capabilities across the business through a collection of tools that work together to turn your data into clean, coherent, interactive visuals.
We know the challenges that carriers face in managing business because we come from the insurance industry.
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