How advanced analytics is a boon for insurance companies.

Prediction is at the core of the insurance industry characterized by its high- risk activity profile. Due to its highly competitive nature and consumers´ behavior, small and big insurance companies must invest in more accurate and effective ways to predict their customers´ behavior and minimize operational risk.

Here is where predictive models and Big Data come into play. These methodologies and technologies will enable insurance companies to offer new products and pricing adapted to their customers and consequently, make their business more scalable. In other words, predictive models and Big Data are both used to maximize the insurance activity.

A myriad of fields in the insurance sector will benefit from advanced analytics-based methodologies, particularly: the prevention of fraud and cyber-attacks and customer- brand relationship. But, let´s look into it in more detail:

Risk evaluation

The increasing number of connected devices (smartwatches, cars, health apps, etc.) along with exogenous data such as road conditions, meteorology, urban security, consumption habits, etc., allow insurers to predict the probability of each insured person of being involved in a car accident, or having their car stolen or any other eventuality.

For example, some health insurance companies offer promotional packages in exchange of data from customers´ wearables and health apps. This would enable them to evaluate customers´ health risks and detect vulnerabilities among their customers like the risk of suffering from diabetes or any other type of disease associated with living habits.

However, the use of health data by insurers involves people´s awareness of ethical issues and data protection derived from the use of connected devices that are not linked directly with insurers, arising ethical dilemmas still unsolved today. On the other hand, the use of predictive models based on Big Data help companies to reduce operational risks and offer better insurance policies options to their customers.

Cybersecurity

Due to the increasing number of data sources and the maximum protection demanded by many sectors (health and finance), the main concern of insurance companies is their own security. 53% of insurance companies state they are “thinking” of preventing cyberattacks. According to a survey carried out by EIOPA ‘Understanding Cyber Insurance – A Structured Dialogue with Insurance Companies‘, the deep understanding of the challenge cyber risk detection entails to the European insurance sector.

Predictive models based on Machine Learning enable cyber-attacks prevention and minimization of associated risks.

Fraud detection

Many industries have realized how a data-driven approach has helped to prevent fraud, and without any doubt, the banking and insurance sectors have benefit the most.  Along with the banking sector, insurance companies using predictive models for the prevention of criminal activities or fraud, will be able to detect mismatches between the insured and third parties involved in the insurance claims, even in online activity, through predictive modeling and advanced analytics. Thanks to this technology, insurance claims fraud will be detected.

Improve customer relationship experience

Certainly, it would not be the first time we hear complaints about a rude or unprofessional customer service of insurance companies. Do not pay on time, do not repair claim settlements etc., etc. which makes customer rotation very high in this sector.

Big Data analytics allows Marketing and Sales departments to offer personalized products to their customers. In other words, to offer them the perfect insurance policy fitted to their risk profile and needs. Analyzing consumers´ voice is key to customer satisfaction and loyalty enhancement. For example, in the U.S. insurance companies are using different Deep Learning techniques for sentiment analysis to understand customers´ voice tone on calls to an insurance call center. Thanks to these techniques, it will be possible to know if a customer is upset or annoyed and to respond accordingly: to offer better services to solve the problem that was the reason for the call.

Ultimately, insurers change customer churn or loss due to poor service and create a greater Brand relationship. Thanks to advanced analytics, the insurance industry makes customers feel they really care for them and reduces churn.

The great advantage of using advanced analytics is offering insurers more accuracy in their financial decision making.