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Calculating IBNR – Process Checklist

IBNR reserve, Unearned Premium Reserve (UPR) & Premium Deficiency Reserve (PDR)

IBNR reserves are a part of claims reserves estimated by insurers for reporting on their financial statements. Claims reserves are estimates of claims that have occurred on or before the financial statement report date but which have yet to be paid. This a current liability that has to be reported regularly on the insurer’s financial statements even though the actual final settlement cost of the claims may be unknown to the entity at that date. Accuracy of these claims reserves estimates is important to the insurer for a number of reasons. It impacts the insurers:

  1. Profitability, financial position, and strength which influences how investors and regulators view
  2. Pricing, underwriting, strategic and financial decisions made by its management

Inaccurate estimates will project an incorrect view of the insurer’s health and may result in investors and regulators taking actions that may be detrimental to the company. The insurer’s own management may take incorrect and possibly adverse action to correct perceived failings or benefit from perceived wellness that erroneous estimates convey.

Claims reserves comprise of two main portions:

  1. Outstanding case reserves for claims incurred and reported as of the financial report date
  2. Incurred but not report (IBNR) claims reserve estimate, as mentioned above, which consists of:
    1. A pure IBNR reserve estimate, that is claims that have incurred but which has not yet been reported to the insurer
    2. Provision for future development of claims already reported to the insurer
    3. Provision for claims that will be reopened in the future
    4. Provision for claims that have been reported but which are not yet recorded in the insurers books

Outstanding case reserves are determined by insurer’s claims department or an independent claims adjuster hired by the insurer while the IBNR reserve estimate is usually determined / advised by an actuary. The focus of this post is on the latter estimate.

In Pakistan, according to the Insurance Ordinance 2000 a non-life insurer is required to hold a liability for the unexpired risk that is valued at not less than the sum of unearned premium reserve and the premium deficiency reserve, where the:

  • Unearned premium reserve (UPR) is the unexpired portion of the premium which relates to business in force at the balance sheet date; and
  • Premium deficiency reserve (PDR) is the amount if any by which the expected settlement cost, including settlement expenses but after deduction of expected reinsurance recoveries, of claims expected to be incurred after the balance sheet date in respect of policies in force at the balance sheet date, exceeds the unearned premium reserve.

 This post is a summarized to-do list and serves as a broad check list when estimating IBNR reserve. A couple of points to review for contiguous UPR & PDR reserve estimations are also mentioned. Some practices are generic by nature and may extend beyond the valuations mentioned here. Please note that it does not provide specific details of IBNR, UPR and PDR calculation methodologies. It is simply a list of questions to pose and ponder on and areas to review before, during and after undertaking such an exercise.

IBNR reserve estimation process

The IBNR reserve estimation process – data collection to report submission



For IBNR estimation at a minimum the data obtained from the client should contain the following:

  • Class of business
  • Product type
  • Policy to date
  • Policy from date
  • Policy number
  • Claim number
  • Claim amount
  • Loss date
  • Intimation date
  • Claim paid dates
  • Claim settlement expense
  • Reinsurance paid – share of claim amount
  • Reinsurance paid – share of claim settlement expenses

In addition for a UPR & PDR reserve estimation exercise the data should additionally consist of:

  • Written, earned & unearned premium by line of business
  • Financial statements – claim, premium, expense, income statements


Data quality is an important factor for the IBNR reserve estimation process as it directly impacts results obtained. Controls should be in place at the company to ensure that all required data is being accurately captured using designated parameters and constraints where applicable.

The data fields should be consistent across the years of claims data. Any changes to headings and labels or parameter fields should be applied consistently to all years’ data being considered. Ideally, a legend should be provided so that fields captured are clearly understood by users of the data.

Current years data should be reconciled with the past years data and movements in the claims data over the year. If more than one source of data is available, the information should be reconciled across sources. Differences should be explained and addressed.

Basic checks should be made such as:

  • Subtotals & Totals should be verified and crossed checked against other sources like the accounts, financial statements, internal MIS, etc.
  • Consistency should exist between loss, intimation & claim paid dates for a particular claim (e.g. loss dates falling after claim paid dates should raise a flag), amounts retained and reinsured (e.g. the sum of amounts cannot exceed the total claim amount), etc.


While it is ideal to have all data discrepancies and inconsistencies addressed prior to the disclosure and regulatory submission of IBNR reserve estimation results, it may not always be possible given time constraints. To handle data that may be incomplete or incorrect, treatment is assigned and results are qualified accordingly with necessary caveats.

If there are multiple sources of data and one source is treated as the primary data source, missing data may be gleaned from other sources.

Each discrepancy identified should have a corresponding treatment implemented and documented. All such treatments have an impact on results to either a lesser or greater extent. Each treatment adds a layer of uncertainty to IBNR reserve estimate. Therefore, the client must be made aware of this and concrete steps need to be put in place to address data quality issues.



The model chosen should be tied to the purpose of the estimation exercise.

If the purpose is regulatory submission, entities follow the rules and methods prescribed by the supervisory authority. Regulators may require insurances companies to periodically estimate their IBNR reserves to assess adequacy. A method is usually prescribed to ensure a degree of uniformity in practice, comparability across entities and a minimum standard or benchmark for the industry. For example, the Securities and Exchange Commission of Pakistan prescribes the Chain Ladder approach for IBNR estimation. Its illustrative example using the volume weighted technique for calculating lag factors using yearly development of claims.

If the purpose is internal reporting, one or more methods may be used to obtain estimation results, such as chain ladder, expected claims, Bornhuetter-Ferguson, Frequency-Severity Techniques, etc. Methods selected may be based on the regulator’s prescribed method or may take into account the nature of claims of a given business line. Does the business line experience low frequency/ high severity claims? Or high frequency/ low severity claims? Years of credible historical experience available may also be considered. Is the business line a new line or for a new target audience or territory? Or is it an established line with years of claims data behind it? Methods should be applied consistently across successive periods so that emerging trends may be evaluated. Internal reporting would likely be on a more frequent basis (e.g. monthly) than regulatory reporting and should ideally be linked to decision making, risk management & capital planning. Development tables may be built independently or incorporated within the entities business intelligence (BI) system and should allow the user to vary parameter selections such as granularity (combinations of business lines and/ or product types), full development year, lag factor calculation approach, etc. Developments factors should be calculated from these development tables but should be editable to consider or exclude data anomalies, reinsurance impact, downward development, stability & smooth progression across development periods, tail factor, etc. Cumulative claims development factors, ultimate claims & IBNR reserve estimated will be determined from the selected claims development factors. Internal IBNR reserve calculators can serve as audits or cross checks against results opined by external independent auditors and actuaries. A significant deviation could be sources of discussion and further investigations between concerned parties.

Appropriateness of the model

Deviations from the regulator’s prescribed methodology may be allowed but will usually need to be supported with sound reasoning. For IBNR reserve estimation for a new line of business, the chain ladder approach may not be appropriate as sufficient data is not available to get credible results. An Expected Claims Technique may be used by the entity instead based on the experience of a similar line with sufficient claims history or the Bornhuetter-Ferguson approach may be used to credibility weigh results from both actual claims data and estimated expected claims data.

In the case of UPR, for example, it may not always be appropriate to use the twenty fourths method commonly prescribed and used to calculate the reserve. The underlying assumptions for the twenty fourths method is that majority of policies have tenors of one year with issue dates that are more or less uniformly spread out over the year. The twenty fourths method would not be appropriate for policies covering seasonal products such as some forms of agricultural insurance with tenors of 6 months or less. Insurance regulations recommend a proportion of gross premium approach based on the ratio of the unexpired period of the policy and the total period, both measured to the nearest day in such instances. Data constraints or data quality issues related to policy period dates may play a role in deciding whether this exact alternate approach or an approximate method is applied.

Model assumptions

Model results will vary based on the data and assumptions used for the estimation exercise such as:

  • Paid claims or reported claims data used
  • Link factor calculation approach – simple, volume weighted, medial average, geometric average
  • Full development year
  • Development factors selected
  • Loss ratios
  • Credibility factors
  • Impact of reinsurance to be included or not 

Versioning & version history

Each model developed should be labeled with version and date. The version ultimately implemented or used for determining results for regulatory submission should clearly be labeled FINAL.

Ideally, each revised version should contain a version history documenting what has been changed since the prior version, why and by whom. If peer reviewed, then the date of review and name of the reviewer may also be recorded.


Do the results make sense?

  • Reconcile current year results with prior year results.
    • What are the expected changes?
      • What is the growth in premiums since the last results?
      • What is the growth in incurred claims since the last results?
    • How do you explain unexpected changes?
      • Are there any anomalies in the claims development patterns? What are the reasons for these anomalies? Are they due to systematic changes or idiosyncratic one-off events?
      • Have there been any changes in methodology and assumptions?
      • Have there been any changes in underwriting practices since the last valuation?
      • Have there been any changes in claims administration procedures since the last valuation?
      • Has the method for estimating outstanding claims reserve changed over the preceding years?
      • Was the IBNR estimated in prior years for a given business line adequate based on the actual claim development of that line to date?
  • Simple cross checks such as claim ratios and ratios of IBNR reserve to claims incurred of similar business; or applying development of the latest fully developed accident year to recent accident years’ data to get a crude IBNR estimate, etc. may give some insight or a broad picture view of result appropriateness.
  • Consistency between results with and without the impact of reinsurance
    • Development factors for net and gross claims should have a reasonable relationship
    • Caps may be set so that net IBNR reserves in each accident month/year do not exceed gross IBNR reserves
  • Treatment for unexpected changes
    • Discuss development pattern anomalies with the client and understand their impact. Should claims contributing to these anomalous patterns be excluded and treated as outliers or are they indicative of a new normal and to be considered in the calculations?
    • Should calculations go more granular versus less granular in terms of estimation by business line/ subline/ product? The degree of granularity impacts results and needs to be considered carefully:
      • More granular – One impact, particularly in the case of PDR is that increased granularity leads to increased PDR especially for less mature lines with sparse data. The following may need to be considered when reviewing granularity:
        • Is there sufficient data to go more granular?
        • Is there a need to revise IBNR reserve estimation methodologies for certain sublines (from the prescribed method)?
      • Less granular – combining certain product types or sublines (presumably with similar characteristics) for IBNR estimation may
        • lead to a distortion of overall results or
        • mask important trends or risk in certain sublines or
        • lead to cross subsidization of loss bearing/ risky business sublines with profitable sublines

Caveats & disclaimers

Caveats, disclaimers, and qualifications should be added along with the results if:

  • there are deviations in methodologies from prescribed regulations and standards or
  • if the data was subject to simplifying treatment because of unresolved data discrepancies,

A further analysis, a sensitivity study of sorts, may be included to show how results would be impacted if data & assumptions were revised.


Continuous & Detailed

Documentation is a vital and continuous process that begins from the time the assignment is confirmed to the time the FINAL report is submitted and approved. It should be sufficiently detailed to allow for replicability, understanding, and review by an independent peer reviewer or auditor.

Documentation consists of

  • Emails received and sent
  • Data – characteristics, discrepancies & treatments – this will be particularly useful and allow for easy review and revision to the dataset if the discrepancy is addressed in a timely manner prior to report submission
  • Methodologies considered and implemented
  • Queries and concerns raised & subsequent responses
  • Minutes / key points from internal meetings and meetings with clients
  • The final report submitted (see the section below) 


The report formally documents and discloses for the intended audience, the process followed and the IBNR reserve results obtained. The process should be sufficiently detailed to allow another actuary to replicate the results. Recommendations and concerns will also be highlighted.

Standard format & audience

In general, the report should follow the standard order listed below with the audience of the report dictating which section receives greater focus and weight.

  • Executive Summary
  • Scope & introduction
  • Data
  • Methodology & Assumptions
  • Results
  • Recommendations & conclusion
  • Annexures (including EXCEL annexures)

Reports to senior management should focus on results, concerns, and recommendations. Items that could potentially detract from this focus, such as details on data discrepancies and treatment should be relegated to a separate communication or included as an annexure to the report.

An iterative process

Allow time for review and challenges of the results by the client to keep the process transparent and foster buy in of numbers and results. Such a review could reveal reasons for development pattern anomalies, internal company practices and policy characteristics that could lead to a review of methodologies, assumptions, data and results. Maintain versioning and version history to keep a track of drafts and final submissions. The list above is by no means comprehensive but is a basic go-to for us. What would you add to the mix?


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