---
license: apache-2.0
---

# Project 1 Proposal of the Long Term Care(LTC) Aggregated Dataset 

KAO, HSUAN-CHEN(Justin)  <br> 
NetID: hk310

## Dataset Details

The long-term care aggregated dataset, essential for conducting experience studies, is an extensive and valuable compilation of variables central to the analysis and prediction of long-term care (LTC) insurance products. This dataset integrates two critical files: one detailing claim incidence and the other capturing policy terminations. This merger is crucial for valuation purposes, enabling a holistic view of the insurance lifecycle.

The dataset features a broad spectrum of variables, from demographic information such as `Gender`, `Issue_Age_Bucket`, and `Marital_Status`, to more nuanced policy-specific details including `Premium_Class`, `Underwriting_Type`, and `Coverage_Type_Bucket`. Additionally, the termination component enriches the dataset with variables like `Claim_Type`, `Region`, `Diagnosis_Category`, `Claim_Duration`, `Exposure`, `Benefit_Expiry`, `Deaths`, `Recovery`, `Terminations`, and `Others_Terminations`. These elements offer insights into the reasons for policy cessation, whether due to the policyholder's death, recovery from the condition leading to the claim, or other factors leading to the discontinuation of coverage.

By combining the incidence and termination datasets, insurers gain a comprehensive understanding of both the initiation and conclusion of LTC insurance policies. This complete perspective is vital for actuaries and analysts to assess risk, set appropriate reserves, design tailored products, and determine pricing strategies that reflect the true cost of providing LTC coverage. It also aids in regulatory compliance and ensures that insurance products are both financially viable for the provider and beneficial for the consumer. Through careful analysis of this aggregated data, insurers can predict trends, modify underwriting practices, and make informed decisions to manage their portfolios effectively.


### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** SOA Actuarial Practice Modules[https://www.soa.org/sections/long-term-care/long-term-care-resources/]


## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

[More Information Needed]


## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

[More Information Needed]

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[More Information Needed]

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

[More Information Needed]

### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->





## Dataset Card Authors [optional]

[Justin Kao]

## Dataset Card Contact

[justinkao.44@duke.edu]