Category Archives: Loyalty Accounting

Loyalty Program Liability Budgeting: How to Build a Financial Forecast

It’s too late to ignore loyalty program modeling.  


Whether you manage a local program or an international program, you likely already have thousands (if not millions) of loyalty program members. In fact, data has shown that 30 – 50% of hotel room nights are purchased by loyalty program customers. And international airlines realize as much as 44% of total revenue from frequent flyer programs.


It’s clear that loyalty program liabilities and revenues represent significant balance sheet and income statement accounts. Unfortunately, these financial items are based on member behavior and can be hard to predict and budget.


But as the saying goes, failing to plan is planning to fail.


For example, it’s critical to accurately estimate breakage (the percentage of points that will ultimately go unredeemed) in order to defer the correct amount of revenue for each reporting period.  


Budgeting for your loyalty program draws out important considerations:

  • How will program revenue be recognized over time?
  • How much additional revenue will be deferred this year?
  • How will program revenue impact cash flow?
  • What will be next month’s redemption costs?


The solution is to build a financial forecast for key loyalty program metrics.


A robust model with prudent assumptions allows program managers to quickly run forecast scenarios, where multiple program variables can be estimated or adjusted as inputs. The result is an intelligent, responsive framework with which to examine your loyalty program’s performance under different breakage rates, member growth, and other key variables.  


In this article, we’ll walk you through the steps needed to analyze, build, and assess financial modeling for your loyalty program. These include:

  • Predicting point “runoff” for current members
  • Predicting future point transactions of current members
  • Predicting the URR, CPP, and FVPP of future earned points for current members
  • Predicting point transactions, URR, CPP, and FVPP for future members
  • Bringing it all together


Estimating these metrics not only provides you with a clearer picture of your loyalty program, it helps you better predict your program’s financials. To help you along the way, we’ve developed a model financial forecast, found near the end of this article.


Let’s get started.



Step 1: Predict point “runoff” for currently outstanding points

Loyalty Point Run off


The first step to building a financial forecast is to estimate when current outstanding loyalty program points are expected to be redeemed (or, in some cases, expire). Point “runoff” refers to one of two events:

  1. Points are redeemed
  2. Points expire


The running total of unredeemed and unexpired member points represents your growing program liability. These points will eventually either incur a cost or result in breakage.


Calculating ultimate redemption rate (URR) helps identify what percentage of points will ultimately be redeemed. However, it’s important to accurately estimate the timing of point redemptions.


A projected redemption pattern can help predict the timing of:

  • The cost to the company of fulfilling point redemptions
  • The recognition of previously deferred revenue
  • The expected pattern of point expirations


Robust actuarial analysis can generate a projected redemption pattern which, when summed, equals the URR for those points. The result of this predictive modeling analysis is an estimated runoff schedule of outstanding points – a forecast for when points are expected to be used or expire unspent.


For example, consider you have a program with 100 outstanding points and a breakage rate of 25%.


This means that the URR is 75% and that 75 of the 100 points will be redeemed. While it’s useful to know how many points will be redeemed, it’s ever more helpful to know when they’ll be redeemed.  A runoff schedule will forecast the cadence at which these points are redeemed or expired (e.g., 5 points in redeemed January, 4 points redeemed in February, and so on). The alternative is looking blindly towards the future.


Additionally, the runoff schedule will provide you with an estimate of the percentage of your liability expected to be redeemed within the next calendar year. This split between current and non-current is often reported in company financials, including those for frequent flyer programs and hospitality programs.

Reminder: New standards change performance obligation rules

It’s worth noting, that under the new ASC 606 and IFRS 15 standards, revenue can now only be recognized once the performance obligation has been fulfilled. For example, let’s say a loyalty program member stays 3 nights with a hotel and is rewarded with a free night, as part of the hotel’s promotional deal. Revenue isn’t recognized from the free night until it is actually used by the customer. In other words, transactions associated with the free night remain deferred until the customer utilizes the promotional reward and stays at the hotel.



Step 2: Predict future point transactions of current members

Predict future point transactions of current members


Now that you understand the future utilization of outstanding points as of a given evaluation date, it’s time to predict the outcome of points that have yet to be earned.


Predicting future behavior starts with forecasting the pattern of future points earned by current members for each month, extending out several years. For the best results, these forecasts should be calculated at the individual member level. When paired with an estimate of revenue per earned point, this will produce an estimate of future revenue for each member, which is the first component of customer future value (CFV), a key metric for program optimization.


In the same way, the pattern of future points redeemed and expired for each current member can be predicted. Note that these patterns will include the redemption and expiration of points that haven’t been earned as of the current evaluation date. This is a key difference from Step 1 and provides a fuller picture of the expected future redemption costs.



Step 3: Predict URR, CPP, and FVPP for future points earned by current members

Predict URR, CPP and FVPP for future points earned by current members


Also essential to this analysis is predicting ultimate redemption rate, cost per point (CPP), and fair value per point (FVPP) of the earned points forecasted in Step 2.


When multiplied, future earned points, URR, and FVPP represent the amount of revenue that will need to be deferred in future periods.


The product of future earned points, URR, and CPP equals the expected future redemption cost (the second component in the CFV equation).


Taken together, Steps 1 through 3 provide a strong foundation for loyalty program liability budgeting with existing members. Steps 1 and 2 provide month by month forecasts of point transactions, while Step 3 projects the ultimate outcome of points earned in each of the upcoming periods for current members.



Step 4: Predict point transactions, URR, CPP, and FVPP for future members

Predict point transactions, URR, CPP and FVPP for future members


Ultimately, accurately forecasting your program liability requires two things: (1) understanding current member behavior and (2) predicting future member behavior.


Similar to how we determine current member behavior, predicting future member behavior requires we look at the following:

  • Future member points earned
  • Future member points redeemed
  • Future member points expired
  • Ultimate redemption rate (URR)
  • Cost per point (CPP)
  • Future value per point (FVPP)


It’s no secret that loyalty programs generate large amounts of data. Predictive modeling can help you draw actionable insight into each of these aforementioned metrics, while giving you the required understanding to make important decisions about your program strategy as a whole.


Build your model from the bottom up, taking a member and channel-specific approach:

  1. Segment members by the channel through which they join (e.g., web, offline, partner)
  2. Forecast metrics for the average member who will join via a given channel in a given month
  3. Multiply this by the expected number of members joining through that channel in each month


Segmenting by join channel allows for projecting different scenarios of member growth by channel. Forecasts of member growth by channel are common throughout the loyalty industry, and channel data can provide insights into expected member behavior when transactional data is limited or non-existent.


For example, in some programs, members who join via offline channels earn fewer points and have a higher breakage rate than members who join through other channels. If a program intends to scale down its acquisition spend for offline channels, program leaders should expect the overall breakage of points earned in the future to decrease.  


Ultimate redemption rate for a given join month should increase over time

Analytics at the individual member level will offer your team key insights into member behavior.


As an example, consider the ultimate redemption rate:


Ultimate Redemption Rate (URR) = Total points that will ultimately be redeemed / Total points issued


URR is weighted by total points. Even a small group of members, if they have have enough points, can have an outsized impact on the overall URR. Members who earn more points tend to have a higher URR. Over time, as these power users earn a larger share of the total points, the overall URR is pushed up.  This phenomenon is known as mix shift.


When members first join, however, the share of points between casual and power users is more evenly distributed.


For example: suppose Larry (a casual user) and Amy (a power user) are the only two members who join in a given month:


Age 1
Age 2
Age 3
Age 4
LarryCumulative Earned Points
Cumulative Earned Points
TotalCumulative Earned Points


Casual versus Power User

Cumulative URR increases over time as power user mix increases


The overall URR for the join month starts at 60%, when both the casual and power user have earned a similar share of points. However, notice how the URR increases over time as Amy, a power user, earns a significant share of the overall points.

Viewed on a larger scale, your program URR should follow a similar pattern.



Step 5: Bring it all together

Bringing it all together


We’ve discussed evaluating current and future member behavior. But to truly see the “big picture” of your loyalty program data, we need to combine current and future earned points — and members — to produce a complete forecast of revenue and costs.

Aggregate estimates

In steps 1-4, we calculated the ultimate redemption rate (URR), cost per point (CPP), and fair value per point (FVPP). These estimates for current and future members serve as inputs for financial statement items and program optimization metrics.

Forecast financial statement items

After forecasting behavior metrics for your loyalty program members, it’s time to turn your attention to the actual financial statement. On public financials, the loyalty program liability receives the most attention. FVPP and URR are key inputs to estimating your financial liability (reported on financial statements), while CPP is essential for estimating your economic liability (actual future costs to your program).

Breakage = 1 – URR

Loyalty program financial liability = Outstanding points x (1 – breakage) x FVPP

Loyalty program economic liability = Outstanding points x (1 – breakage) x CPP

Consider program optimization metrics

Many of the metrics discussed serve as inputs towards calculating your loyalty program liability. Conveniently, optimizing your program relies on many of the same metrics.


Ultimately, you want to be maximize your loyalty program ROI. Customer lifetime value (CLV) is a reliable measurement. If it’s increasing, your program is likely driving increased customer engagement that encourages revenue growth.


Pulling these metrics together into a coherent portrait of your program’s financial future can be daunting, however. Our  downloadable guide provides you with a framework to put the pieces together. It takes you through each step – estimating member growth, projecting the behavior of new members, and forecasting the outcomes for current members – to create a long-term view of key loyalty program cash flows.  Additionally, it allows for scenario testing, giving you actionable insight into the effects of various member acquisition strategies.




Strategizing and reporting reliable loyalty program liability estimates is a complicated undertaking. Reportable deferred revenue relies on accurate actuarial analysis requiring sound estimates for many program metrics.


Bottom-up predictive modeling can build a reliable, robust financial forecast for liability budgeting. It starts with segmenting your members by behavior, calculating relevant program metrics, and considering future member behavior.


To improve your program liability budgeting, take the five steps we’ve outlined in this article:

Step 1: Predict point “runoff” for current members

Step 2: Predict future point-earning behavior of current members

Step 3: Predict the point behavior, URR, CPP, and FVPP for future members

Step 4: Predict point transactions, URR, CPP, and FVPP for future members

Step 5: Bring it all together


Ultimately, the goal is to build an accurate financial forecast of both member behavior and program liability.


But the benefits extend far beyond predicting where your program is headed. Such analysis gives you the insight needed to optimize your loyalty program — not only improving customer engagement, but increasing its ROI.  




KYROS provides sophisticated predictive analytics solutions that help companies optimize the financial performance of their loyalty program. Want to maximize the economic value of your program?  Contact us  for a free consultation.


Your 9-Step Checklist for Loyalty Program Financial Reporting

Year-end means a lot of things for many people. Holiday music, ice skating, pumpkin spiced lattes.


For accountants? The fun starts after closing the year-end books.


With the recent changes in loyalty program revenue recognition standards, this process has come under fresh scrutiny. Loyalty program accountants must now incorporate the new reporting standards ASC 606 and IFRS 15, while still optimizing their financial statements for profitability.


Rather than get lost in the details (as it’s all too easy to do), we’ve compiled a quick 9-step checklist for loyalty program financial reporting. As you enter the holiday season, we hope this will speed up your processes and bring better financial insight to your program.


Step 1: Validate data

Accuracy is everything in accounting.


Naturally, the first step is to ensure your records are accurate and correct. Good data is essential.


Each accounting period should be checked to ensure that individual transactional data matches with the total outstanding point balance used in the liability calculation. Underlying data for breakage estimates must match with data used for the books.


In general, prior period trends should also be consistent. Examine the number of points earned, points redeemed, and points expired each month. Month-to-month point volumes should appear similar when compared to historical years, notwithstanding some exceptions.


A few exceptions to watch out for include:

  • Flash promotions increasing redemptions
  • Temporary grace periods decreasing point expiration
  • New expiration rule increasing point expiration


Step 2: Allocate redemptions to points earned

Accurate breakage estimates require correctly allocating redemptions to actual point earnings.


Loyalty program point allocation has similarities to inventory valuation. As customers use their points, redemption costs should be allocated to specific point earnings. Much like when physical inventory is sold, revenue and costs of goods sold is applied for each unit sold.


The industry standard for loyalty programs is First in First Out (FIFO). Under FIFO, point redemptions are tied to the member’s earliest earned points (first in) that remain outstanding.


Unlike inventory valuation, there is no required method for point allocation. Some programs might find using FIFO isn’t realistic or advantageous:

  • Programs with expiration rules varying by point
  • Programs whose members choose which points to redeem


Regardless of which method you follow, a clean system will tie redemptions to specific point earnings.


Step 3: Update breakage and fair value estimates

update breakage estimates

Breakage lies front and center for loyalty program accounting. Your program is optimized for customer engagement and increasing revenue. Breakage is the variable that balances these two goals.


Breakage drives most of the financial strategy for a loyalty program. With the new standards, it’s more important than ever to land on an accurate estimate.


Updating breakage estimates

Breakage is the percentage of outstanding points that will ultimately go unredeemed. This estimate is used to calculate loyalty program liability.

Breakage = % of points that go unredeemed

Loyalty Program Liability = Outstanding points x (1 – Breakage) x CPP

Cost Per Point (CPP) = Expected cost of each point that will be redeemed

Revenue Recognition Rate = Deferred revenue / future points expected to be redeemed


Breakage estimates are updated with each new period, as new customer data rolls in.


For example:

Last Period:

Deferred Revenue Balance = $900

Points Ultimately Expected to be Redeemed = 1,200

Revenue Recognition Rate = $900 / 1,200 points = $0.75

Points Redeemed in Period = 200

Revenue Recognized in Period = 200 x $0.75 = $150


Next Period:

New Deferred Revenue Balance = $900 – $150 = $750

Remaining Points Expected to be Redeemed Based on Prior Breakage Estimate = 1,200 – 200 = 1,000

Remaining Points Expected to be Redeemed Based on Updated Breakage Estimate = 950

Updated Revenue Recognition Rate = $750 / 950 points = $0.79


Because we now expect fewer points to be redeemed (higher breakage), the revenue recognized with each future point redeemed increases.


The dangers of inaccurate breakage estimates

In an ideal world, your breakage estimate is spot on. As members redeem their points, deferred revenue is recognized and your accounts balance out.


In reality, estimates require continual adjustment. However, if you significantly over or underestimate breakage, significant revisions will be required:

  • Breakage estimate too high and your deferred revenue will be too low, requiring a one-time (potentially) material increase in program liability;
  • Breakage estimate too low and your deferred revenue will be too high, resulting in stuck revenue.


Accurate breakage estimates require predictive actuarial models

The consequences of inaccurate breakage estimates can be avoided with robust actuarial modeling.


Actuaries excel at estimating program liabilities from uncertain cash flows and consumer behavior.


However, traditional actuarial science methods, such as those used in insurance, are not ideal for loyalty program applications; the loyalty program industry is far more dynamic and fluid than the insurance industry.


Predictive analytics and modeling is the best solution for estimating accurate breakage rates. These advanced actuarial models can calculate breakage estimates down to the individual member level.


Fair value per point estimates

Fair value per point (FVPP) is a component of calculating deferred revenue for a loyalty program. FVPP is a dynamic measure that can change with each period.


A number of variables can change FVPP:

  • Changes in utilization distribution
  • Changes in award charts
  • Temporary promotional rewards
  • Changes in foreign exchange rates
  • Inflation
  • Seasonality in standalone value of rewards (i.e. flights, hotel nights)


Assess actual member behavior versus forecasts

Models and estimates are only worthwhile if they are accurate. Each period, assess actual results to your forecasted values for breakage, FVPP, and redemption patterns.


Ask yourself questions such as:

  • How did the volume of points redeemed compare to our model predictions?
  • Did members redeemed their points on the award types our model predicted?


If your answers aren’t quite what you’d hoped, you’ll need to assess and adjust.


In analyzing your model performance, you’ll be able to identify what’s driving changes in your estimates. This is essential to communicate a clear story to your CFO and auditors. A member-level model is particularly useful for constructing a clear narrative.


Step 4: Record accounting entries for reporting periods

record corresponding accounting activity

Each financial reporting period will require updating key loyalty program accounts. The following items will change and require the corresponding accounting activity:

  • Points earned
  • Points redeemed
  • Points expired
  • Updated breakage estimates

Points earned

Any new points earned will require an associated entry to deferred revenue. The value should be based on the relative standalone selling value of the points.


The amount of deferred revenue recognized should incorporate your latest breakage estimate.


For example, if breakage = 10%, each redeemable dollar should result in deferring 90 cents.


Points redeemed

Points redeemed during the reporting period will result in recognizing new revenue and reducing deferred revenue liability.


The revenue recognition rate represents the proportion of deferred revenue realized per every redeemable point.


Let’s take a closer look:


Beginning of the Period:

Deferred Revenue Balance = $900

Points Ultimately Expected to be Redeemed = 1,200

Revenue Recognition Rate = $900 / 1,200 points = 0.75


During the Period:

Points Redeemed =200

Deferred Revenue Recognized = 200 x 0.75 =$150


Points expired

Points expired during the period require no adjustment, as long as the deferred revenue account incorporates point expiration estimates.  


Final adjustments

This list is by no means exhaustive. A few noteworthy additional items to adjust include:

  • Adjust deferred revenue balances with latest foreign exchange rates
  • Breakage estimates (with associated updates to the deferred revenue account)


Member-level predictive analytic models help quantify the magnitude of exchange rate risk, and aggregate results up to a total currency level.


Step 5: Seek an actuarial opinion

Actuarial opinion to certify accuracy

A company’s CFO and auditors are required to certify the accuracy of company financial reporting statements. Given the financial statement ramifications of an inaccurate breakage estimate, actuarial opinions are sought to justify loyalty program liability.


An actuarial opinion is signed by a credentialed actuary as proof of thorough review and vetting of loyalty program liability assumptions, and provides the following:

  • Support for booked breakage estimate to auditors
  • Peace of mind for the CFO (booked liability is materially significant to financial statements)
  • Protection against key material risk factors (inaccurate estimates of loyalty liability or breakage)


The opinion provided will usually be presented as a range of reasonable estimates, any of which are actuarial justified for booking purposes. Often, actuaries will present their analysis to the CFO and auditors verbally, in addition to a physical document.

Step 6: Prepare financial disclosures

financial disclosure reporting

There’s already a long list of required disclosures for loyalty programs. After ASC 606 and IFRS 15, the list has only gotten longer.

Required disclosures Include:

  • Liability change during the year
  • How much revenue recognized in the period is included within opening liability balance
  • When the company satisfies its performance obligations (e.g., when the reward is used)
  • Nature of the goods and services the company has promised to transfer
  • Estimate of the timing to satisfy the liability
  • Significant judgments
  • Method used to determine transaction price and allocate it to performance obligations


A deeper dive (and examples) into the financial reporting requirements is available here.


Step 7: Hedge exposure (optional)

An optional but prudent step is to consider your foreign exchange exposure. If your liability is significantly exposed to foreign exchange risk, your modeling and liability estimate becomes much more complicated.


An effective currency risk management strategy involving forward contracts can minimize and hedge your exposure to foreign exchange fluctuation risks.


Step 8: Assess progress against your financial plan for the year

While Steps 2 through 7 account only for the loyalty program liability, there are additional transactions and measures to track each month. These include:


Cash Flow Implications

  • Points earned bring in revenue
  • Points redeemed carry a cost

Forecasting Implications:

  • Forecast liability and cash flow
  • Anticipate year-end financial position
  • Determine budget availability
  • Plan for the medium- to long-term horizon


Comparing actual transactions and breakage estimates to forecasts will help identify if your program is over- or under-performing. Of course, random fluctuations can be expected, but large variances should be investigated and understood.


Variances can be examined manually, but will be most effectively assessed through drilling down with member-level models.


Over time breakage will shift. As frequent customers accumulate more points, they become “power users” (i.e., customers with a larger share of the overall point distribution). It’s worth noting that these power users will tend to push the overall breakage rate down.


Step 9: Uncover further opportunities to optimize

identify opportunities to optimize

Finally, it’s worth remembering that the financial reporting process highlights many metrics that can be optimized for better overall performance.


Customer lifetime value (CLV) represents another key opportunity. CLV is the present value of all net cash flows expected for each member. This metric can be calculated through implementing a member-level model.


CLV represents a member-specific metric to focus on for maximizing the profitability of your customer loyalty program. The goal should be to increase CLV for each member each month. This is achieved through a mix of driving customer engagement and purchases.


By implementing a CLV model, program managers can also identify and target new members with a high CLV-to-acquisition-cost ratio.


It can be tempting to focus primarily on minimizing your program liability. After all, it’s the only piece of a loyalty program that shows on your financial statements. However, long term profitability and growth depend on maximizing CLV and customer revenue net of cost.



As the year winds down, deadlines get tighter and deliverables become more urgent. When assessing your next reporting period, give this 9-step checklist a try:


Step 1: Validate data

Step 2: Allocate redemptions to points earned

Step 3: Update breakage and fair value estimates

Step 4: Record accounting entries for reporting periods

Step 5: Seek an actuarial opinion

Step 6: Prepare financial disclosures

Step 7: Hedge exposure (optional)

Step 8: Assess progress against financial plan for the year

Step 9: Uncover further opportunities to optimize


As we wind down on 2018 and look ahead to 2019, understanding what goes behind each of these steps will help you continue to improve the accuracy of your financial reporting, and provide valuable insight to your company as it looks for new ways to optimize its financial performance.




Turn insight into action with predictive analytics solutions that help you maximize the economic value of your loyalty program. Contact us  for a free consultation.


New Revenue Recognition Standards to Reshape Liability Accounting

Quarter-end reporting can be an incredibly stressful time for any loyalty program accountant. It goes without saying that accuracy and efficiency in completing reporting requirements is of the utmost importance.  


Add to this the stress of fielding questions from management, completing precise and timely reporting, and ensuring adherence with the SEC and auditors, and it’s easy to see how even the most seasoned accountants can get overwhelmed.  


Understandably so, the balance between accurate loyalty program accounting and the proper recognition of deferred revenue has come under ever more scrutiny with the new revenue recognition standards ASC 606 and IFRS 15.


Compliance with the new revenue recognition standards jointly issued by the Financial Accounting Standards Board (FASB) and the International Accounting Standards Board (IASB) in 2014 is now required for public companies.


No matter what industry your company is in, if it generates a profit from contracts with customers, you need to change the way you account for revenue. This is especially true if your company has a loyalty program, as you’ll need to alter the way you account for program revenue and liability.


The impact this new standard has on your loyalty program will be felt throughout your organization: from greater revenue deferral to alterations in balance sheet liabilities, to additional disclosure obligations in your company’s financial statements.


Shockingly, a significant number of companies are not prepared for the major changes in accounting and business operations required by the new revenue recognition standard.


In this post, we’ll discuss the new standards, their improvements, how this will affect your accounting program and its estimates, and the key focus for loyalty program accountants going forward.  



A history of revenue recognition standards


U.S. GAAP: ASC 605 and SAB 104

Prior guidance with U.S. GAAP originally fell within ASC 605, and was later modified by SAB 104: Revenue Recognition.


For years, ASC 605 was the only guidance for revenue reporting in the U.S. Initially, the revenue recognition guidance was nonspecific. However, it was later clarified by SEC Staff Accounting Bulletin No. 104 (which, coincidentally, was only applicable to public companies; private companies still lacked clear guidance).  


The revenue recognition principle from ASC 605 was simple but vague: recognize revenue once realized or realizable and earned.  


SAB 104 established the criteria list. When all four criteria were met, revenue could be recognized:

  1. Persuasive evidence of an arrangement exists (e.g., written contract or electronic evidence)
  2. Delivery of goods or services has been completed
  3. Seller’s price to the buyer is fixed or determinable
  4. Collectibility is reasonably assured


Because these guidelines offered no specifics for loyalty programs, the FASB formed an Emerging Issues Task Force (EITF) to develop guidance that led to two dominant modeling methods:

  1. The incremental cost model, where companies recognize revenue at time of purchase and a liability is recorded to cover the cost of future point redemption; and
  2. The deferred revenue / multiple element model, in which companies defer the portion of revenue directly related to the earning of loyalty points until the customer redeems them, or the points expire. The deferral amount is calculated using a fair value approach.  


Still, despite these piecemeal improvements, U.S. GAAP guidance had two primary shortcomings:

  1. Revenue recognition concepts remained too broad
  2. Over 200 industry-specific guidelines were excessive



International accounting standards followed a more specific approach under interpretation IFRIC 13, issued in reporting year 2008. This provided guidance to entities that grant loyalty rewards points to customers that can be exchanged for goods or services.


While its focus was on the treatment of loyalty program liabilities, IFRIC 13 provided additional guidance for the treatment of deferred revenue by introducing two key concepts:  

  1. Deferred revenue / multiple element model:  Revenue related to the sale of a good or service is recognized immediately; revenue allocable to the value of the loyalty points must be deferred until points are either redeemed or forfeited.  
  2. Deferred revenue must be based on the fair value of points to the customer or relative fair value (this was previously optional with ASC 605).


In comparison to the old U.S. GAAP and IFRS standards, IFRIC 13 is more closely aligned with the new standards — though it lacks the prescriptive deferred revenue valuation.  

The new standards, summarized

For over 16 years, the IFRS and FASB have worked together to create the newly developed standards, ASC 606 and IFRS 15. Fundamentally, these new standards require companies to accurately recognize revenue as the value anticipated to be received from the transfer of goods or services.


This involves a five-step process:

  1. Identifying the contract with the customer
  2. Defining the performance obligations in the contract
  3. Determining the transaction price
  4. Allocating the transaction price to the performance obligations
  5. Recognizing revenue when (or as) the entity satisfies a performance obligation


In other words, companies will have to defer revenue for most loyalty programs.


This means that not only will companies that previously used the incremental cost model see later revenue recognition, but that the new model has made certain concepts of loyalty program accounting identical for both the U.S. GAAP and IFRS.



New standard ASC 606: Revenue from Contracts with Customers

Accounting Standards Codification (ASC) 606, titled “Revenue from Contracts with Customers”, became effective for public company reporting periods beginning after December 15, 2017. For 2018, the new standards are applicable and must be reported. The effective date for all other entities begins after December 15, 2018.

Objectives & improvements

The new standards aim to improve the financial reporting of revenue from contracts with customers. Previously, highly specific industry guidelines made comparability difficult, which have been simplified with ASC 606.


The standard now provides guidance on many transactions — specifically service transactions — that were previously lacking (non-public entities had to rely on the SEC and other entities for guidance).  


The new scope applies to contracts with customers, which are defined as:

“A party that has contracted with a company to obtain a good or service that is an output of the company’s ordinary activities in exchange for consideration.”


Exceptions include:

  • Lease Contracts
  • Insurance Contracts
  • Financial instruments


Goals of the new standard are more comprehensive:

  • Remove inconsistencies in revenue reporting
  • Create a more robust framework for addressing recognition issues
  • Improve comparability of revenue recognition practices across reporting entities and industries
  • Provide more useful financial statement information
  • Simplify financial statement preparation


Recognition & measurement guidance

This applies the new accounting standards to any business that recognizes revenue with the transfer of goods or services in exchange for consideration.  


Specifically, if a company enters contractual agreements with a customer (such as through a loyalty program), the company makes a promise of performance obligations. These obligations must now be accounted for separately, and quantified at an estimated or actual transaction price. As the company satisfies its performance obligations, revenue is recognized in an amount equal to the performance obligation.  

New disclosure requirements

ASC 606 requires additional disclosure obligations for customer contracts, including:

  • Revenue recognized from customer contracts (and categorized appropriately)
  • Contract balances (contract assets and liabilities)
  • Performance obligations and program rules
  • Significant judgments


New standard IFRS 15: Revenue from Contracts with Customers

The International Accounting Standards Board (IASB) first issued IFRS 15 Revenue from Contracts with Customers in May 2014, after collaboration with U.S. GAAP. The mandatory date for adherence was January 1, 2018. Its focus: developing a high-quality global accounting standard for revenue recognition.

Objectives & improvements

Due to the collaboration with the FASB, the IFRS 15 standard objectives are very similar to ASC 606:

  • Address inconsistencies with and weaknesses in prior standards
  • Improve inadequate disclosure requirements
  • Improve the comparability of contract revenue reporting
  • Provide more clear and comprehensive guidance for revenue recognition issues
  • Enhance disclosures for consumers of financial information

Revenue recognition model

The model establishes a thorough framework for determining when to recognize revenue and how much to recognize:  

“An entity should recognize revenue to depict the transfer of promised goods or services to customers in an amount that reflects the consideration to which the entity expects to be entitled in exchange for those goods or services.”


To implement this framework, companies should apply a five-step process:

  1. Identify the contract with the customer
  2. Define the performance obligations in the contract
  3. Determine the transaction price
  4. Allocate the transaction price to the performance obligations
  5. Recognize revenue when (or as) the entity satisfies a performance obligation

New disclosure requirements

In the interest of providing more relevant information to investors, additional quantitative and qualitative information is required:

  • Revenue recognized from customer contracts (and categories)
  • Contract balances (including assets and liabilities)
  • Performance obligations
  • Significant judgment in applying standards
  • Assets recognized from costs to obtain/fulfill customer contracts



How will these standards affect loyalty program liability accounting?

Breakage and Accounting Standards

For loyalty programs, the key issue becomes one of allocating revenue between the initial transaction in which the customer earned the points or rewards, and the standalone selling price of the option to acquire goods or services in the future through the redemption of the loyalty reward obligation.  The standalone selling price is representative of deferred revenue.


The underlying purchase and the subsequent transaction involving the redemption of points for products or services are separate performance obligations, and the recognition of revenue from those separate obligations will be separate in substance (and timing).


Specifically, the sum allocated to the loyalty rewards is recognized as a contract liability, and revenue will need to be deferred and recognized when the rewards are redeemed or expire.


Each loyalty program has different nuances. A simple method for identifying deferred revenue, on a monthly basis is reflected in the following:

Monthly Deferred Revenue = [Points earned in a month] x (1 – [continuing breakage]) x FVPP

Fair Value Per Point (FVPP) = expected fair value of each point that will be redeemed


While the change brought by the new revenue recognition standards might result in more short-term financial decision making, the long-term economics of loyalty programs should see no effect.  



New revenue recognition standards increase the importance of accurate breakage estimations

Determining the standalone selling price of the points or rewards necessary for compliance with the new standard can be a challenging exercise.


A standalone selling price is the price at which a company would sell a promised good or service separately to a customer.


In the context of rewards programs, determining this price will involve some degree of estimation that takes into consideration potential customer discounts, variability or changes in costs, and most critically, breakage.


When businesses estimate too much breakage, they fail to defer enough revenue. Conversely, when companies underestimate breakage, they will defer too much revenue and depress it more than they need to.


Deferring too much revenue can build up to a significant pile of “stuck revenue.”


Stuck revenue occurs when breakage estimates are insufficient. An excess of deferred revenue becomes “stuck”, remaining allocated in loyalty program liability accounts.


Only by updating breakage estimates can this be corrected. However, many companies rely on vintage-based models (e.g., join year development models) with simplistic forecasts. This leads to underestimating actual levels of breakage, potentially leaving millions in revenue locked up in liability accounts.


An ideal breakage estimate model incorporates:

  • Predictive analytics
  • Comparison of monthly breakage actuals versus forecasts
  • Quicker updates
  • Quantifies model estimation uncertainty


Don’t leave millions stuck in accounting limbo.  



Are you prepared for the new revenue recognition standards?

For companies that currently account for their loyalty reward revenues using the multiple-element model, the new standard may not change current practices all that much.


However, those businesses that use an incremental cost model under GAAP standards will likely see later revenue recognition for a portion of the transaction price when the new rule is applied.


In other words, the new revenue recognition standards will change the landscape of loyalty program accounting, reducing the amount of revenue received at the moment of transaction and making it necessary for companies to insure against the coming wave of member redemptions with reasonably estimated deferred revenue.




Looking to maximize the economic value of your loyalty program? Contact us for a free consultation.


3 Things Every Accountant Should Know About Loyalty Program Liability

Ever since the roll-out of new accounting standards, ASC 606 and IRFS 15, accounting departments have had to change the ways in which they deal with loyalty program liability. The primary shift in procedure has been that accountants must now defer revenue to cover the liability upfront, and recognize it only at the point of redemption.


The easiest way to visualize the role of an accounting department in managing loyalty program liability is to consider the following parallel: If loyalty program liability were a fire, accountants would be the firefighters tasked with putting it out. Wielding deferred revenue as a firefighter would a hose, it’s the job of accountants to carefully select just how much to defer. If they defer too little, the flames of the liability will burn through the company’s income. Deferring too much, however, will flood the company with “stuck” revenue.


Fortunately, there are ways for accounting departments to correctly forecast how much revenue they’ll need to set aside in order to mitigate incoming liability without creating a trail of stuck revenue in their wake. Read on to discover the three things every accountant needs to know about accounting for loyalty program liability.



1. There are new standards to keep in mind

international accounting standards


The rules regarding revenue recognition have changed. In a collaborative effort between the International Accounting Standards Board (commonly known as IASB) and the Financial Accounting Standards Board (FASB), an updated method of revenue recognition has been created that eliminates discrepancies between both organizations’ guidelines. This new, conjoined set of accounting standards is known as Accounting Standards Codification (ASC) Topic 606: Contracts with Customers, or, in its short form, ASC 606/IFRS 15 Accounting Standards.


How will these new protocols affect Accounting for loyalty programs?

In addition to replacing a variety of prior regulations, this latest standard outlines a five-part model that’s widely considered to be more thorough and prescriptive than earlier statutes. ASC 606/IFRS 15 Accounting Standard addresses the following elements:


  • Contract Identification
  • Identification of Performance Obligations
  • Determining Transaction Cost
  • Allocation of Transaction Cost to Performance Obligations
  • Recognition of Revenue


One of the biggest changes the new standard will introduce is the elimination of viewing contracts as singular transactions. In the context of loyalty programs, this will signify that both the upfront delivery of a good or service, as well as the fulfillment of any accompanying loyalty point redemptions will be considered distinct events for which accounting must occur.


Moving forward, accounting departments will have to consider the performance obligation as their basic unit of account. Performance obligations are typically defined as promises by a company to confer either goods, services, or a combination thereof upon a customer.


How will fragmenting the performance obligations within a contract change accounting practices? Principally, it means that companies now must carry out the following:


  • Identify distinct performance obligations, and allocate revenue accordingly. Separate margins must be applied for each individual performance obligation identified.
  • Pinpoint the event that corresponds to the eventual recognition of revenue for every individual performance obligation. Depending on the situation, revenue will either be recognized at the point of completion, or once a given interval of time has elapsed (such as when loyal rewards expire). Which of the options will be exercised is a function of how the precipitating service or good is transferred to the client, or the exact verbiage of the governing contract.


Equally as important as knowing which parts of a contract to recognize separately is knowing when to recognize them. As they say, timing is everything, and under the new standard, when revenue deferred for mitigating loyalty program obligations can be recognized will be more tightly controlled.



2. Accurate breakage estimates are essential

loyalty program


Now that companies must defer revenue to cover the costs of incoming loyalty points, being able to correctly anticipate breakage is more important than ever. How much revenue a business must defer corresponds significantly to its predicted breakage rates, so it’s essential that accounting departments have a reliable model of how redemptions will unfold.


The formula below demonstrates the role of breakage in anticipating loyalty program liability:


Liability = Outstanding Points * (1 – Breakage) * Cost Per Point

Outstanding Points = Points that have been issued but not yet redeemed or expired

Breakage = Percent of outstanding points that will ultimately go unredeemed

Cost Per Point = Expected cost of each point that will eventually be redeemed


When accounting for loyalty programs, it’s important to note that deferring the wrong amount of revenue can have unfortunate results, and both over- and under-estimations of how much to set aside can place a company in peril.


Companies that set aside too much revenue risk setting the stage for an outcome known as “stuck revenue.” This creates an unnecessary depression in revenue, and keeps the “stuck” funds from being applied in more effective ways.


In contrast, deferring too little revenue can lead to companies being forced to restate their income as a consequence of not having enough tucked away to cover the incoming barrage of redemptions. Income volatility is something neither companies nor shareholders want, and it’s easily preventable by using reliable breakage models.



3. Actuarial opinions are useful for justifying booked liability

Accounting for Breakage


In much the same way that a company would hire a general contractor to oversee the construction of a new wing for their headquarters, so too should they consult with experts before proceeding with loyalty program accounting predicated upon an ongoing breakage assumption. While redemption rate modeling can be accomplished to a high degree of accuracy, doing so involves taking a constellation of massive, interwoven data sets into consideration and distilling  them into a lucid picture of individual-level member behaviors. Actuaries have the expertise necessary to interpret this data and mine from it the answers your company needs in order to make breakage estimates you can trust.


Despite the informal-sounding nature of their title, actuarial opinions must be backed up by a full-scale report featuring graphs, exhibits, and texts that outline how the actuary arrived at his/her calculations. Having a nuanced, granular-level outline of member behavior crafted by actuarial experts wielding potent AI-driven analytics software is an important step towards justifying your company’s booked liability to regulators and auditors.


The bottom line

The new standard will bring divergent regulations into alignment and require that companies no longer view transactions as singular contracts.


Instead, companies will be expected to defer revenue until all performance obligations have been met or enough time has passed to bring the outstanding liability to a point of expiration.


Deferring the wrong amount of revenue can lead to highly undesirable outcomes, so it’s important that your company inform its deferral decisions using breakage estimates constructed using robust, analytics software that gleans future individual-level predictions from big data. An actuarial opinion is a reliable way for your company to obtain this information, and move forward with confidence in its decisions. How will your company ensure its booked loyalty is correct?




Turn insight into action with predictive analytics solutions that help you maximize the economic value of your loyalty program. Contact us for a free consultation.


New Accounting Standards Increase Importance of Accurate Breakage Estimation

Recent changes by both the Financial Standards Accounting Board (FSAB) and the International Accounting Standards Board (IASB) are making companies reexamine the way they record and interpret revenue from customers enrolled in loyalty rewards programs.


The newly-developed standards demand that companies defer revenue generated at the time that loyalty points are accrued, and that they reintegrate that revenue into their income statement once points are redeemed.


The final tally of how much revenue is deferred (and recognized at a later point) is, in large part, a function of the anticipated amount of breakage. As a result, it’s important that companies correctly forecast the way breakage will affect them in the future.


When companies predict too much breakage, they fail to defer enough revenue. Conversely, when they underestimate breakage, they defer too much revenue and depress it more than necessary.


Many companies employ methods and models for estimating breakage that tend to underrepresent how much breakage will actually occur. This, in turn, results in deferring more revenue than appropriate. Doing so establishes the groundwork for a phenomenon known as “stuck revenue.”


I’ll explore stuck revenue in greater detail later in this post. But first, let’s review how breakage affects your company’s loyalty program liability.  


How to calculate loyalty program liability

Loyalty program liability is the cost of open obligations a company has to members of its loyalty program.  

Accounting for Breakage


Whenever a loyalty program member receives a point or mile , they become holders of a currency. This currency, be it a Starbuck “star”, a hotel loyalty point or any other type of organization-specific currency, represents a cost that the company will eventually have to absorb upon redemption. Because they can culminate in a cost for the company, a loyalty point is seen as a liability.


Commonly known as loyalty program liability, its impact is a direct function of breakage. The simplest formula for calculating loyalty program liability is:

Liability = Outstanding Points * (1 – Breakage) * CPP

Breakage = % of outstanding points that will ultimately go unredeemed

Cost Per Point = the expected cost of each point that will eventually be redeemed


In this model, breakage, or the percentage of outstanding points that will ultimately go unredeemed, must be correctly identified, or else loyalty program liability will be misrepresented. Breakage in this context is sometimes referred to “liability breakage,” as it represents the average breakage rate for all points previously issued.


Understanding breakage is a prediction problem. It requires the ability to predict how members will redeem their points during their lifetime with the program.


Companies frequently believe that they won’t be able to zero-in on breakage rates properly, but with today’s machine learning and computing capabilities, sorting through the massive wake of data produced by individual customers is now a possibility. By analyzing the behavioral patterns of individual members, companies can begin to understand member behavior at a micro-level, and gain a grasp on breakage levels within the program.



How the new accounting standards work

New accounting standards have made it so that most loyalty programs must defer revenue from loyalty program customers until it is “earned” upon the redemption of points.  

New accounting standards


For the past 16 years, the FASB and the IASB have sought to develop a uniform, principles-oriented standard to which all industries should adhere. Citing differences between the stipulations of generally accepted accounting principles (GAAP) in the U.S. and those of the IFRS, the board decided to make a set of amendments that would see improvements to both sets of protocols.


The chief issue with GAAP was that they prescribed a broad variety of industry-specific regulations for transactions that were economically similar; conversely, the IFRS saw a signature lack of specificity that got in the way of application and integration.


Originally, the guidelines outlined in the U.S. GAAP that addressed revenue recognition were SAB 101: New Revenue Recognition Guidelines and SAB 104: Revenue Recognition. In both of these sections, revenue was recognized as soon as a transaction was completed, and neither section provided guidelines for accounting for loyalty programs.


Eventually, FASB’s Emerging Issues Task Force, known as the EITF, delivered an outline on accounting for loyalty programs. The new guidelines contained the following approaches for revenue recognition:


Incremental Cost Model

Using this model, companies log-in revenue at the moment of purchase. Simultaneously, they incur a corresponding liability to the cost of redemption.

Deferred Revenue or Multiple Element Model

Some corporations prefer to employ this alternate approach, which views the rewarding of points as a distinct transactional element. Using this method, companies defer the recognition of revenue that is associated directly to the accrual of loyalty points to a time in the future in which either the customer redeems them, or they expire. In contrast to the incremental cost model, this model calculates the deferral amount using a fair value approach.


Regardless of which of the two models a company may have opted for, under the new guidelines, revenue will have to be deferred for most loyalty programs. Therefore, the emerging standard is most similar to the deferred revenue model. This will result in lower immediate revenue, where only when redemptions actually occur will the revenue be recognized. The liability becomes a statement of value in a way, as it produces a statement of income for when consumer redemptions actually transpire.


Of course, this is in significant contrast to the incremental cost approach, which lacks redemption-based income statement benefits. If one were to analyze this difference from the perspective of short-term finances, it could have an influence on how program finances are managed. However, those evaluating the way these rules affect the overarching economics of a loyalty program in the long-run will be pleased to discover that they are not actually affected.


Deferred revenue and breakage

There is a simple method for identifying the amount of revenue that will be deferred over the course of a month, reflected in the following formula:

Amount of Revenue Deferred Monthly = [Points earned in a month] × (1- [continuing breakage]) × FVPP

Fair Value Per Point (FVPP) = expected fair value of each point that will be redeemed


(Note that this formula is not an exact roadmap to the actual quantity of revenue deferred each month, due to minor nuances caused by the integration of “Relative Stand Alone Selling Price”)


This model makes the assumption that (1- [continuing breakage]) is reflective of how many of the points earned in the month will eventually be redeemed. This is different than [liability breakage], which represents the overall average breakage rate for all points previously issued.


An easy example of this principle in action is to imagine a local pizza chain called “Dough My Gosh.” For every slice a customer purchases, they accrue 10 “Doughllars.” After a customer has earned 50 Doughllars, they can redeem them for a free slice of cheese pizza, valued at $2. Each month, the succulent slices sold by Dough My Gosh generate nine thousand Doughllars, at a cost of four cents per Doughllar.


Assuming that Dough My Gosh has a breakage rate of .15, the amount of deferred monthly revenue can be calculated in the following manner:

Amount of Revenue Deferred Monthly = [9000] × (.85) × .04.

Thus, the final sum for Dough My Gosh’s deferred monthly income is $306.


Stuck revenue and its risks

As we’ve learned, upon the redemption of points, the recognition of revenue occurs. At this juncture, one of three potential situations are likely to unfold:


1. The original estimate for breakage was accurate. In the case of our hypothetical pizza company, the $306 that had originally been deferred will now be able to be considered “earned,” and will be eligible to enter the revenue stream.


2. The breakage was overestimated. In a situation like this, the entirety of the deferred revenue is recognized, but it isn’t sufficient to absorb to the impact of redemptions. This results in companies potentially seeing negative hits to income levels caused by the disparity between the amount of now-recognized deferred income and the expense of fulfilling point obligations.


3. The breakage estimate was insufficient. In this case, the company creates a pool of stuck income resulting from the excess of deferred revenue remaining in the liability. This can only be resolved by updating the breakage estimate.


The chances of revenue becoming “stuck” are high

Stuck revenue is a likely outcome that should be diligently avoided. Estimating breakage is no simple task, and a lot of companies attempt to gauge it using simplistic models. In fact, many companies still rely on historical breakage models. Also known as “vintage-based models,” they tend to generate estimates that under-represent the level of breakage. In an upcoming piece, I’ll discuss the pitfalls of these types of models in more detail.


In some instances, I’ve seen the breakage estimate dip below 20-30% of the actual rate. Depending on the scale of your program or company, this could result in tens of millions in revenue stuck in accounting limbo.


This phenomenon culminates in many businesses not recognizing the amount of stuck revenue they hold, as they cannot detect the biases in their breakage models until they develop more accurate, unbiased alternatives.


How to avoid creating stuck revenue

Without question, the simplest way to reduce the chances of creating stuck revenue is to better calibrate breakage estimation models. Here’s what one should expect from an ideal model:

Leverages predictive analytics and actuarial science: Understanding breakage is fundamentally a long term prediction problem. Actuarial science provides the toolbox to predict over long horizons, while modern machine learning and predictive modeling gives the toolbox to leverage the vast amounts of data produced by loyalty programs. All this leads to more accurate and insightful breakage estimates.   

Monitors breakage at an Earn Month level: Using this information, companies can track breakage for points accrued in a particular month and ensure the congruence of initial breakage assumptions with the behavior of actual breakage. By aligning these two data sets, businesses can diminish the possibility that revenue will end up stuck.

Is easy to update and updates frequently: This permits companies to increase the speed with which they recognize revenue and decrease the amount of time it takes to discover stuck revenue.

Demonstrates the uncertainty in breakage estimates in quantifiable terms: Frequently, companies prefer to err on the side of caution with regards to their breakage models. They believe this helps them prevent circumstances in which they fail to defer enough revenue to cover costs. By quantifying the degree to which their estimates are uncertain, companies can more prudently decide how much revenue they should recognize, versus how much they should maintain in a fund intended to serve as a buffer in the event estimates change in the future.


Bottom line

The changes in IFRS regulations will change the landscape of loyalty program accounting. They will lower the amount of revenue that companies receive at the moment of a transaction and will make it a necessity for corporations to insure against the coming wave of member redemptions with stores of deferred revenue.


Deferring revenue does not need to negatively impact the economics of a company and won’t do so if proper breakage estimates are used. However, if companies fail to use accurate, flexible models with the ability to evolve, they run the risk either overestimating breakage, which results in deferred revenue that is too low, or underestimating breakage, which leads to stuck revenue. Many companies have stuck revenue, and fail to realize it due to inadequacies in their breakage models.


In my future posts, I’ll get into the specific strategies companies can use to improve their breakage estimations. Make sure to check these out for valuable insights into how to correctly calibrate your breakage estimations with the realities of your business.




Turn insight into action with predictive analytics solutions that help you maximize the economic value of your loyalty program. Contact us  for a free consultation.


Accounting for Loyalty Programs: The Challenges & Opportunities

In my previous articles, we talked about the challenges faced by both loyalty program finance professionals and loyalty program marketers as they seek to create revenue-driving loyalty programs.

Now, we turn our attention to accountants, who face significant obstacles towards accurately accounting for loyalty program liability.

In this article, we’ll examine the role of accounting for loyalty programs, the frequent challenges encountered by accounting professionals, and the opportunity available to ensure a smoother close process.


The loyalty program accountant

Quarter end is often a stressful and hectic time for any accountant. They’re racing to close the books under tight deadlines, and auditors and senior leaders are asking tough questions about the company’s financial performance.

It shouldn’t come as a surprise that accountants strive for a smooth and efficient closing process; no surprises along the way, no excessive reporting.   


When it comes to loyalty programs, accountants are responsible for booking an accurate liability or deferred revenue estimate on the balance sheet, while ensuring that the organization is following the latest accounting standards and that auditors will sign off.

This means that not only do they face those tough questions from auditors and senior management, but they must also deal with managing unexpected changes in the company’s loyalty program liability.

Let’s take a closer look.


Asking tough questions — and expecting the right answers

The size of the loyalty program’s liability is an important consideration for accountants. In fact, it’s common for the program’s liability to be one of the largest on the company’s balance sheet. Consequently, loyalty program liability will draw scrutiny from auditors and senior leaders. Often, this leads to tough questions that many accountants struggle to answer, such as:

  • Why is the liability changing?
  • How confident are you that the estimate is correct?
  • How might we influence the liability to manage to our financial plan?

Unlike more tangible liabilities (e.g., accounts payable), these questions are complicated because loyalty program liability is an uncertain estimate. Answering questions about liability require the ability to predict redemption behavior over a long period of time, and convince stakeholders that your predictions are indeed accurate.


Managing unexpected changes in loyalty program liability

Unfortunately, these questions can get even more complex when there are unexpected changes to program liability.

Loyalty program liabilities are frequently in the hundreds of millions to several billion dollars. At this scale, even a small change in liability will end up having significant financial impact.

Seeing a quarter’s profits wiped out because of an unexpected increase in liability is not something anyone would want to deal with.

The challenge for accounting is having an accurate and reliable liability estimate. The estimate should be on par with the expectation, without any surprises. It should come complete with all the backup support and data necessary to satisfy auditors and any other stakeholders with questions. And, it should come quickly after quarter’s end to ensure more time for analysis.


The opportunity

Everything that an accountant booking loyalty program liability needs hinges on one core capability:  the ability to predict redemption behavior over time, while convincing stakeholders that the estimate model is reasonable. While predicting the future is never easy, there are tools in place to help you.

Sophisticated analytics, for example, helps you accurately predict redemption behavior. Imagine being able to point to actuarial backup that tracks the assumptions behind the liability estimate to prove that the data is emerging as expected.

You could confidently present your liability estimates to senior leaders and auditors, knowing that you have the right data to answer their probing questions. A sophisticated analytical model not only predicts today’s liability, it looks into the future to give you accurate estimates for what you’ll see at the close of the quarter.

What’s more, these analytic models can be continually refreshed, giving you updated liability estimates within days, and allowing you plenty of time to run the books and analyze the impact.

Suddenly, accounting for loyalty programs doesn’t seem quite as difficult, and quarter close becomes a little less stressful for everyone involved.



Turn insight into action with predictive analytics solutions that help you maximize the economic value of your loyalty program.  Contact us for a free consultation.

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