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3 Ways Sentiment Analysis Dataset Can Help the Insurance Industry

Jan 18, 2019

As we move into 2019, the only thing that is certain about the insurance industry is the level of uncertainty about where it will be at the end of 2019! Recent insurance industry trends, which have challenged insurers in 2018, will continue to influence the industry, but with a fresh set of trends arriving, companies in the insurance industry will face many uncertainties. Recent regulatory changes, such as Brexit and GDPR, are also expected to influence the industry. Furthermore, changing consumer behavior patterns, the growth of autonomous devices, and the rising threat of cyber-attacks are posing numerous challenges for companies in the insurance industry.

Going forward, the interface between insurance companies and the customer is going to be one of the key battlegrounds, not just in the trivial sense of chatbots and online portals, but rather as the ability of insurance industry players to make every part of their operation work for the customer. Therefore, insurers will need to take the help of measures like developing a sentiment analysis dataset to tackle such challenges.

Facing trouble leveraging the right customer analytics solutions for your business? Request for more information to know how Quanztig’s data scientists can help.

At Quantzig, we understand the impact that a sentiment analysis dataset can have on your business. And to help insurance companies prosper amidst the growing competition, our team of experts has highlighted three promising ways in which a sentiment analysis dataset can manage risks more effectively to maximize ROI and gain a competitive advantage in the market.

How Can a Sentiment Analysis Dataset Help Companies in the Insurance Industry?

Fraud Detection

Recent reports show that insurance companies lose between 8,000 and 12,000 million euros per year due to fraudulent claims. Additionally, the insurance industry estimates that between 5% to 10% of the compensations paid by the insurance companies in the previous year were due to fraudulent reasons, which could not be detected due to the lack of predictive analytic tools. Developing a sentiment analysis dataset allows companies to analyze the patterns in insurance claims, settlement notes, etc. Additionally, a sentiment analysis dataset can help in quick decision making by using the proper KPIs (Key Performance Indicators). This helps prevent fraud and increases profits. In this sense, text analytics, at times through dashboards, provide vital information to make quickly well-justified decisions.

Investing in smart and tailored insurance solutions may seem premature and expensive. But with the right guidance, sentiment analysis model, and industry know-how, it can lead to significant cost savings. With over 15 years of industry experience, Quantzig’ s insurance industry experts can help insurance companies to better understand customers’ credit behavior through sentiment analysis to create individualized and relevant policies to suit and benefit customers, determine the level of risk in claims, and identify key indicators that provide insights into risks and quantify predicted loss severity from claims and loans. Request for more info to know more!

With the growing trend of advanced analytics, the insurance industry faces the challenge of cost-cutting, boosting margins, and reducing litigation costs. Request a free proposal to combat these challenges with Quantzig’s analytics solutions.

Helps Analyze the Customers’ Voice Through Social Media Sentiment Analysis

Customer experience is a vital element for achieving commercial success in the insurance industry. Companies in the insurance industry are trying to understand their customers and opinions by means of satisfaction surveys and social networks. Social media sentiment analysis allows users to classify interactions based on the marketing channels used, the products or services being offered, the operations being employed, etc. Additionally, automatic opinion and social media sentiment analysis datasets help identify the polarity about specific aspects or issues of a channel, product, or procedure. When this type of analysis is applied to comments in open social networks, it becomes easy to detect the industry trends, identify the brand perception, provide early warning of possible reputational crises and qualify the corporate reputation of the brand.

Sentiment Analysis Datasets Improve Claims Management

The analysis of claims and complaints is another natural area for the use of sentiment analysis datasets. Complaints can be classified automatically according to the products, services, or operations of insurance companies regardless of the inbound channel to direct the customers to the appropriate agents so that they receive the appropriate treatment in each case.

Benefits that Sentiment Analysis Datasets Provide to the Insurance Industry

  • Reduces the workload of customer service centers
  • Shortens the response to clients’ time
  • Helps in easy detection of fraud and fraudulent customers

Value Provided by Social Media Sentiment Analysis Datasets to the Insurance Industry

  • Social media sentiment analysis datasets help boost customers’ and employees’ degree of satisfaction
  • It improves client recommendations and retention
  • Social media sentiment analysis also enhances the vision of the market scenario
  • It helps in reducing indirect costs

Ready to Harness Game-Changing Insights?

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