Overcoming Data Management Challenges in Outwards Reinsurance

In today's business landscape, data has become a crucial asset, particularly in the insurance industry, where it is estimated to double in volume every two years. Managing this influx of data presents a complex task, especially for outwards reinsurance/Retro teams dealing with various internal (actuarial, capital management, finance, underwriting) and external stakeholders (rating agencies, regulators, brokers, reinsurers/retrocessionaires). This article addresses the practical challenges that data poses for these teams and explores potential solutions for effective management.

Understanding data challenges in reinsurance operations

Manual data manipulation: Outwards reinsurance teams within most organisations still rely on manual workarounds involving data, to a large extent:

  • They work with numerous large spreadsheets of data to produce different reports like large attritional loss reports, CAT losses, renewal packages, and limit profiles among others.
  • Increased reporting requirements due to various regulations are resulting in teams needing to process more data than before, which may not be readily available in legacy systems.

Although the extent of these activities may vary from one organisation to another, they pose the common risk of decreased productivity and being prone to human errors.

Multiple sources of truth: Sophisticated organisational structures arising from recent mergers and acquisitions, or other operational factors can lead to a data environment that produces competing facts. We often see the same data repetitively fed into multiple systems by teams working in silos, resulting in redundant and less reliable data.

Data definitions: The reinsurance industry deals with a unique set of jargon that has varied interpretations not just among different organizations but also between different departments internally. Naturally, this confusion can lead to errors especially when manual work is involved. Some common terms that are understood differently across organizations are Net Written Premium, Net of Commissions, Net of Cessions etc.

FX calculations: Global reinsurers deal with policies, contracts, and claims in multiple currencies, which can complicate financial calculations. Additionally various FX conversion methods such as fixed rates, monthly averages, or daily rates may apply to contracts. All these factors could lead to incorrect currency conversions and inaccurate financial reporting.

Reporting: Inaccurate data is forcing reinsurance operations and finance functions to close their accounts much earlier by taking estimates and adjusting them with the actual numbers in the following cycles. However, these estimates are what is being passed on for other calculations such as reserving among others, causing ripple effects across other departments.

The long-term impacts of inadequate data management

The challenges mentioned above are those that are commonly observed but aren’t exhaustive. The bigger picture indicates data quality as a primary issue for most teams. Going beyond outwards reinsurance, inadequate data management within this domain can have an impact on broader business functions as well. For example,

  • Insufficient access to timely inwards data diminishes the underwriter’s ability to actively steer the portfolio to maximise ceded coverage and avoid breaching any PML (possible maximum loss) thresholds.
  • Inability to accurately/timely track the protected inwards book of business prevents teams from automatically creating adequate reserves for - future expected premium adjustments, profit commissions, etc.
  • Suboptimal data quality in renewal packages and especially those with older/less up-to-date data (due to manual ETL) may lead to uncertainty charges and an overall higher cost for reinsurance protections.
  • Getting favorable quotes during renewals may be difficult due to the inability to correctly create an “as if” data set using historical data that showcases the impact of the recent change in underwriting strategy.
  • Optimized claims recoveries for events with a 48h/72h window (such as CAT claims) can only be achieved with sufficient data quality and depth.
  • Inefficient data can additionally lead to claims leakage when they are not allocated to the correct treaty.

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Effective strategies for addressing data challenges

Over the years, many surveys have shown that organisational leaders are increasingly acknowledging the importance of streamlining their data practises to ensure success. While the implementation of a Data Management framework is a growing trend within the financial services sector, here are some of the most prominent options for reinsurers to consider:

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Effective data management has become a critical success factor for modern organisations and outwards reinsurance is no exception. Schedule a call with our experts today to have an exploratory conversation about the challenges that your team is facing currently.

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