Insurance

Harness data to meet customers’ changing needs while effectively assessing and protecting against new horizons of risk.

how to create a website

Why AI Now

Getting it right in insurance is harder than ever. The complexity of risk is rising due to climate change, terrorism and cybercrime. Smart homes and autonomous vehicles are creating a complex, new industry dynamics and unprecedented considerations when crafting policies. The analytics behind today’s underwriting, valuation and fraud detection need to be re-invented to be lightning fast, laser accurate and adaptable to changing demands. Failure to deliver means, at best, lower profit and dissatisfied customers. At worst, it exposes insurers to massive losses. RapidMiner enables insurance companies to harness their data to meet customers’ changing needs while effectively assessing and protecting themselves against new horizons of risk.

Insurance Industry Use Cases

Mobirise

Drive Revenue

1. Optimize pricing to price                   sensitivity by geography and           individual clients

2. Understand customer                       segments to expand                         multichannel strategies

3. Assess the long-term value of       each customer to personalize         service

Mobirise

Cut Costs

1. Streamline claims processing by     automating data-dependent           steps


2. Use business process mining to      find opportunities to be more          effective


3. Streamline underwriting to              achieve real-time speed,                  cutting costs and delivering            better service

Mobirise

Avoid Risks

1. Immediately identify fraudulent     and unwarranted claims or               policy applications

2. Reduce risk & ensure                         compliance with precise and           efficient scoring

Business Value

A European property and casualty provider used data available from aggregators to predict competitors’ pricing, and made adjustments to win more customers.

A life insurance provider was able to stake out a market position as a premium provider based on the accuracy of its conversion predictions.

A vehicle insurance provider analyzed driver log data and created differentiated pricing based on the safety of drivers, increasing profit.

A diversified US insurance company used claims data to determine the best course of action in litigation scenarios, increasing the rate of successful outcomes.

A life insurance provider increased the precision of its actuarial models, better predicting risk for senior policies and increasing long-term profit.

A Medicare auditor determined early indicators of fraud and used them to find bad actors more quickly.

A health insurer identified potential medication safety issues for at-risk patients and reduced unnecessary, excessive and risky opioid prescriptions.

A health reinsurer used predictive scoring to more profitably underwrite special diseases and other risky candidates.

Let's talk about how data science can help you adapt to new horizons and meet new demands to drive revenue, cut costs, and avoid risks.

CONTACT US