Freedom is important in the United States. We are free to speak our minds, to publicly share our ideas, to assemble and protest unfavorable outcomes, and to celebrate a religion of our choosing. We are free to be individuals.

With individuality comes innovation. From how we buy homes to how we protect homes, we are living in an era of technological change. Social media, shopping sites, and analytic services are altering the way we think about our communities. Artificial intelligence and big data have transformed the way we live our lives. As other industries adapt, so should insurance. It’s time for a revolution.

There are a few key drivers for insurance industries to implement the use of big data and big data analytics. Big data can provide insurance firms with valuable insight, and analytics can transform that insight into action.

1. Actuarial work and underwriting are two key areas for big data implementation. As of 2014, 28% of P&C companies and 15% of L&A companies were able to use the technology with success. More data means better predictive analysis. This capability can help actuaries generate more consistent results, helping firms satisfy customers.

2. Claims make up the largest cost for insurers, with 80% of premiums going towards pay-out. Yet, companies can use big data to streamline this area as well. Preparing structured and unstructured historical data can reduce decision-making time and errors.

3. Improved fraud detection capabilities can also save insurance companies money since up to 10% of claims are fraudulent. This adds up to over $40 billion a year for non-health insurance, even though 95% of firms use anti-fraud technology.

Policyholders are willing to share their data with insurance firms for stronger customer relationships, lower premiums, and previously unaffordable coverage. Synthesizing this data can improve the understanding between companies and customers.

The problem is that 90% of that data is unstructured. It is often collected but rarely cleansed, normalized, and integrated for analytics. That is where Inonde can help. Our software automates that process through machine learning, reducing the costs associated with data preparation. A large IT team or a group of data engineers are no longer necessary. We let the community immediately start unlocking and organizing their data without scripting or coding. It’s all about freedom, and freedom means access.

The challenges for insurance firms:

• Maintenance of multiple legacy systems creates high operational expenses.

• Separation of legacy rating systems prevents growth, delays processing due to redundant data entry, and makes new employee training time-consuming and difficult.

• Expanding the pricing range for customers is difficult because firms cannot produce more accurate 360 profiles of customers and their community.

• Re-evaluating risks and running multiple models is a challenge because of limited data insights from siloed systems.

Most insurance companies have collected hundreds, thousands, or even millions of rows of granular data about their business. Yet, IT resources and other factors make it time-consuming and costly to locate and extract.

Inonde can:

• Seamlessly transfer information between underwriting and claims administration

• Increase operational efficiency to impact growth and service strategies

• Rapidly respond to inquiries and efficient progression throughout the claims process

Whether it’s meeting higher customer expectations, reducing costs, or setting yourself apart, Inonde can help you turn an ocean of data into an ocean of pure possibility, pure freedom.