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Milliman analytics overview

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Milliman analytics insight

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Article

8 steps to a successful AI adoption strategy for claims departments

Artificial intelligence (AI) is rapidly transforming the insurance industry, streamlining processes, and improving efficiency, particularly in claims management.

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Mortality trend prediction using machine learning

Compared with traditional mortality models, machine learning algorithms can significantly improve the forecasts of future mortality rates.

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Article

Classification of insurance claim emails

Using a hybrid model for health claim email filtering could significantly reduce customer support workload, while maintaining a satisfactory response quality.

Research report

History repeating itself? The return of high inflation and its implications (including modelling) for life insurers

Current inflation rates are likely to be the highest seen for a generation, and the ensuing effects could have a profound impact on life insurers.

Article

Financial modeling — going fast together

With scarce actuarial resources, insurers can adopt lean manufacturing principles to further accelerate the digital transformation of the risk function.

article

Sensitivity analysis for model risk management

In increasing operational complexity within the calculation chain, it has become critical to assess the sensitivity of output results to individual assumptions and inputs involved.

article

Potential data sources for life insurance AI modelling

Big data, combined with the increased usage of machine learning algorithms, allows the life insurance industry to model the surrounding world much more effectively than in the past.

Article

The Rise of Python: Powerful, robust calculation software

Why are actuaries starting to use Python programming? Learn more in this briefing note.

Article

Data analytics: The buy vs. build question

With the abundance of data and analytical resources, how important is it for insurance carriers to develop and maintain those resources in-house? Sheri Scott answers this and other questions in this Q&A.

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Video

Predictive analytics: Uncovering value in the data

Milliman consultants Nancy Watkins, Matt Chamberlain, Peggy Brinkmann, and Sheri Scott discuss how predictive analytics can uncover value in new and expanding data sets, helping improve pricing, underwriting, and profitability.

Article

A case for data science

How Milliman used analytics to develop a predictive app for a transportation provider.

Article

Making predictive analytics work for you

Learn how predictive analytics differ from other approaches to data—and how it can help your business.

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Enterprise risk management: Evolution and transformation

Enterprise risk management is evolving, and as insurance companies have moved through time, there has been greater ability to control information in a more sophisticated way.

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You can own the risk. Or own the consequences.

What does it take to develop a truly resilient risk culture?

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