Summary
Work History
Education
Skills
Timeline
Generic

Sivenathi Manyela

Johannesburg (Open to relocate)

Summary

Detail-oriented and highly skilled professional with dual expertise as an Automated Underwriting Specialist and Property Reinsurance underwriter. Experienced in ensuring data accuracy, integrity, and compliance when implementing automated solutions to streamline data management and underwriting processes. Proficient in leveraging advanced data analysis tools to clean, format and standardize large datasets. Adept at collaborating with cross-functional teams to align data with business and regulatory objectives.

Seeking to apply expertise in data analysis, automation, and data quality assurance to support data-driven decision-making.

Work History

Facultative Property Underwriter

Munich Reinsurance Company
Johannesburg
02.2023 - Current
  • Automated Underwriting Specialist: Spearheaded the design, implementation and maintenance of automated underwriting system; streamlining the collection and processing of client data; resulting in an additional gross written premium of ZAR8 million.
  • Property Underwriter: Managed complex reinsurance portfolios, evaluating large sets of client and risk data, ensuring accuracy, and identifying potential risks for underwriting purposes.
  • Applied advanced Excel functions to clean, format and standardize underwriting data, ensuring integrity and completeness.
  • Created detailed automated reports and dashboards tp provide business insights into underwriting performance, claims trends and data quality.
  • Collaborated with team and clients to ensure alignment of underwriting data with compliance regulations and business objectives.

Facultative Property Underwriting Trainee

Munich Reinsurance Company
Johannesburg
02.2022 - 01.2023
  • Regularly reviewed and assessed property underwriting data to identify inconsistencies, errors, and missing information. Ensure all data captured aligned with underwriting guidelines and risk assessment requirements.
  • Analyzed property risk data to identify patterns and trends that could affect risk pricing.
  • Assisted in the creation of data reports to track underwriting performance and identify any data quality issues, ensuring accurate data for renewal pricing.

Education

Bachelor of Science - Mathematics and Applied Mathematics

University of Cape Town
03.2017 - 11.2021

Skills

  • Data Analysis
  • Client Management
  • Strategic planning
  • Change management
  • Excel
  • R
  • Python
  • SQL


Timeline

Facultative Property Underwriter

Munich Reinsurance Company
02.2023 - Current

Facultative Property Underwriting Trainee

Munich Reinsurance Company
02.2022 - 01.2023

Bachelor of Science - Mathematics and Applied Mathematics

University of Cape Town
03.2017 - 11.2021
Sivenathi Manyela