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Artificial Intelligence in Insurance - use cases

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Artificial Intelligence in Insurance - use cases

Machine Learning can support Insurance companies with supporting their bottom lines through gaining competitive advantages, reducing expenses and improving efficiency. They can optimize all areas of their businesses, starting from risk analysis to dynamic pricing, to make data-driven decisions that lead to increased profitability.

1) CLAIM DEVELOPMENT MODELING
Machine Learning allows insurance companies to predict the ultimate claim amount based on its characteristics.
PROBLEM:
The amount of a claim can vary between the initial filling and the full payment. It is important to predict the final claim amount, as it makes a significant impact on financial statements.
SOLUTION:
Our solutions, like Pattern Finder and the Information Extraction System, give you the accurate tools you need for predictions that lead to a better understanding of how much a claim will cost. You can have confidence in how much to reserve for Incurred But Not Reported Loss Amounts.
WHY LONSLEY:
We make your business simple and effective with Machine Learning-based predictions about the real costs of claims. We also extract the text features and correlate them with different parameters to give you true insights about claim adjustment. You don't have to be an AI expert - that’s our job.

2) CONVERSION MODELING
With the predictions of conversion from a quote to a policy, insurance companies can optimize their pricing and marketing actions to make better, data-driven business decisions.
PROBLEM:
Insurance companies want to know the conversion rates based on new pricing plans. How do you achieve higher profitability without driving your existing customers away? You need to predict the likelihood of converting a quote to a policy.
SOLUTION:
Our cutting edge solutions with extremely accurate algorithms, like the Data Driven Sales Optimization System, can predict the likelihood of a quote becoming a policy. Using this information, you can easily optimize your spending, especially expenditures on marketing to reach out to many more customers that may be more likely to buy, without making any steps that can push your customers away. Our solutions also project the retention rate to allow you to give valuable information to shareholders and prepare the company for the future.
WHY LONSLEY:
We use Machine Learning to give you the most accurate information about predicted conversion rates to help you make proper pricing and marketing decisions, get insights about what your customers want and increase conversion rates. You don't have to be an AI expert - that’s our job.

3) CLAIM PAYMENT AUTOMATION MODELING
Time is money, not only for your business, but for your customers as well. Predict which claims should be auto-paid based on their characteristics at the time of filing to drive costs down and customer satisfaction up.
PROBLEM:
Manual inspection is required to assess the damage in insurance claims, which leads to a very long wait for payment. This may result in a visible drop in customer satisfaction and retention rate.
SOLUTION:
Our systems, like Pattern Finder and the Information Extraction System, determine which claims need to be manually inspected. With auto-paying claims you can close them more quickly and increase customer satisfaction, making costs lower at the same time.
WHY LONSLEY:
We use the power of Machine Learning and Deep Learning to give you the perfect predictions about claims to allow you to save money and build a great customer experience. You don't have to be an AI expert - that’s our job.

4) DIRECT MARKETING
To build a successful business in the insurance industry, the key is to maximize ROI. You can do this by boosting marketing response rates and minimizing misdirected communication. Current state-of-the-art algorithms give the best results, but they also require a specific, deep domain (subject-matter) expertise in Machine Learning.
PROBLEM:
Marketing to prospects is expensive and is going to be more difficult with the coming of GDPR regulations. There is no point in using default schemas for direct emails and telemarketing, as it is not going to help you target the right customers. Incorrect targeting hurts your brand and makes your prospects feel like they are being spammed, resulting in low response rates that lead to a high cost-per-lead.
SOLUTION:
Our cutting edge algorithms included in Data-Driven Sales Optimization System can deliver information about which people are most likely to purchase your product or service, yielding higher ROI. To achieve your goals, maintain a favorable image of your company with targeted communication to save time and money.
WHY LONSLEY:
Our Machine Learning systems will make your marketing campaigns effective. You don't have to be an AI expert - that’s our job.

5) FRAUDULENT CLAIM MODELING
Insurance companies can lose a lot of money due to fraudulent claims. Reduction of fraudulent payouts helps your business save money and deliver your customers a better customer experience.
PROBLEM:
Fraudulent claims are costly. Even if they are expensive, it is even more expensive to check every single claim for fraud and takes a lot of time. Investigation of innocent customers leads to a very poor customer experience and may cause clients to leave your business.
SOLUTION:
Efficient and extremely accurate predictive models that identify likely fraudulent activities. This allows you to investigate only those incidents that are likely to require it. It results in a better utilization of your resources - focused on where they bring the greatest return on the investigation. We allow you to build a better customer experience and protect customer accounts at the same time.
WHY LONSLEY:
Our systems automate predictions of the likelihood that a specific claim is fraudulent or not. You don't have to be an AI expert - that’s our job.

6) INSURANCE PRICING
If you want to stay at the top of the insurance industry and have a profitable business, you must have a refined pricing strategy. To do this, you need to have a highly accurate predictive models.
PROBLEM:
Many Property & Casualty companies are seeing lower underwriting results. Due to the current situation on the insurance market, people can compare many companies instantly, mostly choosing the lowest price. Smaller insurance carriers are being exposed in the areas where they mispriced to make a sale. Mostly, the low price makes the business underpriced relative to the risk, which results in costing a company a huge amount of money.
SOLUTION:
Using the algorithms we provide with the Data Driven Sales Optimization System, you can be totally confident in the prices you charge. We automate the process of exploration of cost versus risk to increase your profitability - to make sure any risk you consider taking on is priced appropriately.
WHY LONSLEY:
We build efficient Machine Learning models and select the best ones to help you save a significant amount of money and assure you that the final result is the best for you and your business. You don't have to be an AI expert - that’s what we do.

7) LIFE INSURANCE UNDERWRITING FOR IMPAIRED LIFE CUSTOMERS
Unless a reinsurance company covers the risk, typically insurance companies do not underwrite life insurance for people who suffer from a serious disease or are otherwise physically limited. Reinsurance companies try to predict which customers are insurable and have positive health prospects.
PROBLEM:
As the medical assessment processes takes so long and requires a lot of money, insurance companies typically do not underwrite customers who have suffered and survived from diseases like cancer.
SOLUTION:
We have built a solution for reinsurance companies to allow them to process historical medical data and current information to predict the risk of underwriting a serious disease survivor. The company can work on the identification of customers with good health prospects to underwrite them directly without a very long medical assessment. This leads to the reduction of medical costs and a larger number of customers.
WHY LONSLEY:
Our solutions use Machine Learning to inspect medical variables and identify rules to segment patients who need the further medical assessment, potentially high-risk patients. You don't have to be an AI expert - that’s our job.

Thursday, 10 January 2019