Claims Intern

Fort Wayne, IN, US

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We are seeking a motivated and analytical senior in college to join our team for a summer internship in the life insurance industry. This role will provide hands-on experience in analyzing industry data, exploring AI applications in claims processes, and understanding the dynamics of life insurance operations. The intern will work closely with experienced professionals, gaining valuable insights into the claims function and the broader insurance landscape.

 

Interns@SwissRe is our comprehensive internship program designed to provide students with a valuable combination of on-the-job training and off-the-job learning opportunities, all while benefiting from our company's global perspective. By joining our program, you'll have the chance to immerse yourself in the dynamic and fast-moving world of a leading risk knowledge organization.

 

Our internship program is carefully crafted to offer impactful project work, engaging social and philanthropic activities that foster team building, industry-relevant training, and networking opportunities. We believe that a Swiss Re internship can be much more than just a temporary job; it can be your first step towards a rewarding and successful career.

 

If you're a highly motivated student pursuing a bachelor's or master's degree, we invite you to apply to our 2025 interns@SwissRe program! The program spans 12 weeks over the summer and is available at multiple office locations across the United States.

 

About the Role: 

Key responsibilites include: 

  • Data Analysis & Benchmarking:

    • Analyze public industry data to create benchmarks related to Key Performance Indicators (KPIs) for claims functions

    • Identify trends, patterns, and insights that can inform strategic decision-making

  • AI in Claims Processes:

    • Assess the potential use of AI in the life insurance claims process

    • Research and develop case studies on current AI applications in both life and Property & Casualty (P&C) insurance globally

    • Provide recommendations on where AI could enhance efficiency & accuracy in claims handling.

  • Stakeholder Analysis:

    • Map out the universe of stakeholders involved in the claims submission process for various types of life and health insurance business

    • Analyze stakeholder pain points/motivations to identify opportunities for process improvements

  • Operational Insights:

    • Examine the operations of life insurance carriers from a claims perspective, including trends, common practices, technology platforms, and HR structures

    • Identify common challenges and opportunities for improvement within these operations

    • Determine which types of business are most costly to run from a claims perspective and provide insights on cost management strategies

 

What You'll Gain:

  • In-depth knowledge of the life insurance industry and claims functions

  • Exposure to cutting-edge technologies like AI in insurance

  • Experience in stakeholder analysis and understanding operational dynamics

  • Networking opportunities with industry professionals

  • Practical experience that will enhance your resume and career prospects

 

About You: 

 

  • Bachelors or masters degree preferred in Actuarial Science, Data Science, Business Analytics, Economics, Finance, Risk Management & Insurance, or Operations Management

  • Strong analytical and research skills

  • Proficiency in data analysis tools such as Excel, Python, R, or similar

  • Ability to interpret and synthesize complex data into actionable insights

  • Knowledge of AI applications and their potential in business processes

  • Excellent written and verbal communication skills

  • Strong organizational skills and attention to detail

  • Ability to work independently and collaboratively in a team environment

 

For Armonk, the base salary will be $20-$30 per hour, depending on location, qualifications, projected graduation year and/or highest degree held. 

 

 

About Swiss Re

 

Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. We cover both Property & Casualty and Life & Health. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.

If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.

Swiss Re is an equal opportunity employer. It is our practice to recruit, hire and promote without regard to race, religion, color, national origin, sex, disability, age, pregnancy, sexual orientations, marital status, military status, or any other characteristic protected by law. Decisions on employment are solely based on an individual's qualifications for the position being filled.

During the recruitment process, reasonable accommodations for disabilities are available upon request. If contacted for an interview, please inform the Recruiter/HR Professional of the accommodation needed.
 

Keywords: 
Reference Code: 131667 

 

 

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Category: Deep Learning Jobs

Tags: Business Analytics Data analysis Economics Excel Finance KPIs Python R Research

Perks/benefits: Flex hours Insurance Team events

Region: North America
Country: United States

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