Additional reinsurers information

  1. OTHER ITEMS

Apart from the data requirements detailed above reinsurers may request additional information as given below. However, this is not an exhaustive list.

  • Primary rate changes – particularly for coverage on classes exposed to catastrophe perils as reinsurers would be concerned with the adequacy of primary rates on underlying catastrophe exposures particularly with climate change impacting catastrophe events.
  • List of special risks – A list of risks that require special acceptance by reinsurers as they don’t generally meet all terms and conditions specified in reinsurance contracts.
  • Business plans – Ideally a high-level summary of business plans to provide reinsurers with a view of the direction insurers are heading.
  • Maximum Retentions – details on the retained maximum sum insured value by the insurer for risk by classes covered in non-proportional reinsurance arrangements.
  • Structures – current (or expiring) structures of proportional and non-proportional reinsurance arrangements.
  1. CHALLENGES WITH DATA QUALITY

Based on our experience dealing with insurers, particularly in less developed and emerging markets for their reinsurance coverage requirements, the following are some common challenges faced by insurers in providing good quality data.

  • Legacy systems that are unable to accommodate evolving data requirements.
  • Lack of dedicated resources to maintain data and perform data extractions properly.
  • Lack of knowledge on data requirements by reinsurers for their analysis.
  1. POSSIBLE ACTION TO IMPROVE DATA QUALITY

The following are some of the remedial actions insurers can take to improve data quality.

  • Train staff on data requirements for reinsurance to overcome the lack of knowledge and raise awareness on the benefits of improving data quality. Brokers can play a pivotal role in raising awareness of the importance of data quality. Brokers can provide data templates, train insurers on data requirements for reinsurance, and raise awareness of how poor data quality can impact insurers’ reinsurance requirements in terms of cost and the availability of coverage.
  • Add dedicated/additional resources for data management.
  • Good collaboration between IT teams and teams handling reinsurance is also important as in some cases data extractions are performed by IT staff who require a good understanding of data requirements.

Based on our experience, insurers providing good quality data are viewed positively by reinsurers. These insurers are knowledgeable about data requirements, and also tend to have dedicated staff for data management. Furthermore, some tend to be more responsive to concerns and requests from reinsurers in the past regarding data issues.