Today’s insurance companies are embracing AI to improve profitability, become more efficient and, ultimately, create a better customer experience.

Insurance companies are using machine learning to improve customer service, fraud detection, and operational efficiency. Insurance brands save time and effort using machine learning to assess damage in accidents, identify anomalies in billing, and more. LotusLabs provides insurers with machine learning solutions to optimize their market selection, pricing, and claims management.

Optimized Claims Management

Access state of the art, machine learning algorithms to:

  • Identify potential fraudulent claims.
  • Identify and flag potentially fraudulent claims.
  • Predict claims severity and large loss potentials.
  • Search, categorize and summarize automatically text.
  • Identifies policies that are likely to lapse, and how to approach the insured about maintaining the policy.
  • Identify individuals that may have too much, or too little, insurance. Then, proactively help them get the right insurance for their current situation.
  • Improves the customer experience by offering relevant information about the coverage the insured may need based on life events
  • Uses unsupervised machine learning to discover predictors in claims activity. This information can help set assumptions and feed into activities such as pricing models or risk analyses.

Insurance Case Studies

Machine learning is positively impacting the whole insurance industry. LotusLabs can bring a sustainable, cost-effective, and inclusive strategy within your organization. Here are just a few ways the insurance industry is being transformed.

Reduced churn

Insurers lose money when good customers don’t renew, as lapsed policies need to be replaced with more costly new business. LotusLabs can help you identify customers and incorporate the risk of “churn” into your renewal pricing, leading to reductions in cancellations and non-renewals.

Fraud detection

LotusLabs can help you create machine learning models that detect with high accuracy the ever-evolving methods of fraud. Claims scoring high for probability of fraud can be further investigated, increasing the accuracy of your fraud detection system.

Image Analysis

Given images of a car or property, machine learning algorithms can identify structures on the object and any condition issues. Insurers can proactively help customers schedule repairs by identifying issues or suggest other type of coverage.

Insurance advice and customer service

Consumers expect personalized solutions, and machine learning makes that possible by extrapolating patterns from a customer profile and providing products that are relevant for that customer and that would be the best for them based on set criteria.

Machine learning algorithms play an important role from the first interaction when determining what coverage is best to ongoing customer service. According to Accenture, 74% of customers that interact with chat-bots, would like to receive computer-generated insurance advice.

Insurance claims prediction

Insurance companies are extremely interested in the prediction of the future. Accurate prediction gives a chance to reduce financial loss for the company. A major cause of increased costs are payment errors made by the insurance companies while processing claims. Furthermore, because of the payment errors, processing the claims again accounts for a significant portion of administrative costs. We can help insurers to efficiently screen cases, evaluate them with greater precision, and make accurate cost predictions. See a detailed case study in this article.

LotusLabs can help you in your AI journey

You want to see AI drive value in every corner of your business. But how do you get started? By building together an AI system with reliable day-to-day operations. At LotusLabs we are experts in Machine Learning and AI infrastructure. Our people work with your people, at all levels. Our methods help you find ways to put AI to work. Transform your business into an AI-driven enterprise.