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

GAAP

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

 

IFRS: IFRIC 13

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.

 

 

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

 

3 Things Every Marketer Needs to Know About Loyalty Program Liability

Every marketing professional wants to engage their customers and inspire lifelong brand loyalty. But in order to develop marketing campaigns that strike a chord with clients, marketers need to understand the needs, expectations, and predispositions of their target demographics.

 

One of the most effective strategies for both engaging customers and gaining key insight into their behaviors and expectations is to instate a customer loyalty program. Whether you’re giving away free coffee, points that can be redeemed for prizes or discounts, or other incentives, customers love loyalty programs — and they play a key role in driving both customer satisfaction and brand loyalty.

 

However, the success of a loyalty program depends not only on its design, but on its execution. This includes safeguarding against accompanying financial risks.

 

Chief amongst these risks is a phenomenon known as loyalty program liability, or the cost incurred by companies once all outstanding rewards points have been redeemed.

 

If correctly anticipated, companies can defer the necessary amount of revenue required to absorb the incoming liability without sustaining any financial injury. To do so, however, they must first know two things: the cost of redeeming each outstanding point, and the percentage of outstanding points that will ultimately be redeemed.

 

What do marketers need to know about loyalty program liability, and what metrics should they focus on in order to best understand the financial risks (or rewards) facing their company? Read on to learn more!

 

A brief overview of loyalty program liability

loyalty program liability overview

 

The simplest way to uncover the cost of your company’s loyalty program liability is to use the following formula:

 

Total Number of Outstanding Points x URR x CPP

 

URR, or ultimate redemption rate, refers to the percentage of outstanding points (or whatever other form of currency your company disperses to loyalty program members) that will eventually be redeemed. The cost per point, or CPP, is the cost the company incurs during the redemption of each point.

 

Once you’ve figured out the values for both of these indices, you can unearth you company’s loyalty program liability by multiplying the total number of outstanding points by the URR and multiplying the resulting amount by the CPP.

 

Revenue should be deferred upfront

deferred revenue

 

So, when should companies concern themselves with the financial impact of these points? Though it may seem counterintuitive, domestic and international regulations prescribe that revenue used to satisfy obligations to program members be deferred at the moment of issuance — not at the point of redemption.

 

This need to defer revenue can lead to three potential scenarios. The first is that not enough revenue is deferred, culminating in your company being forced to restate its income levels. The second scenario is that your company defers too much revenue, leading to a phenomenon known as, “stuck revenue.”

 

The third, and ideal, scenario at which companies can arrive is one in which just the right amount of revenue has been deferred.

 

Knowing how much revenue to defer is critical to contending against loyalty program liability, and can be best accomplished by using granular-level measurements that capture the future actions of individual members. After all, acquiring correct estimates for URR is entirely hinged upon knowing the way customers will behave in the future.

 

Without salient URR or breakage estimates, your company will not be able to generate an accurate forecast of its upcoming liability, and won’t be able to defer the corresponding portion of its revenue.

 

By crafting loyalty programs that incentivize customers to make purchases with company cards or other devices that monitor spending patterns, marketers can cultivate an abundance of  harvestable data. In this respect, marketers can shine, because this data allows their company’s finance and accounting teams to better predict the behaviors of individual customers.

 

Though extracting insights from such large swaths of information may seem like a monumental challenge, the good news is that recent developments in the field of predictive analytics and artificial intelligence have made unlocking the secrets submerged within Big Data a reality.

 

Loyalty programs are advantageous for finance, too

 

Without question, loyalty programs are tremendously helpful for marketers. They provide concrete incentives for customers to continue engaging with a company, and give the marketing team a renewed series of opportunities to keep clients abreast of emerging offers.

 

Moreover, they produce data that allows marketing to calculate the customer lifetime value (CLV) of individual members. CLV denotes how much free cash flow a particular person will generate for the company throughout the course of their time with the company.

 

By gathering an aggregate of the individual CLVs of loyalty program members, marketing can provide their finance counterparts with a clear window into the financial value of their customer loyalty program.

 

CLV can also help marketing teams target those customers with the most value. One of the greatest inefficiencies that besets modern companies is the amount of money that’s wasted on failed attempts to engage disinterested clients. By understanding a member’s cumulative lifetime value, you can know whether the return generated from their engagement justifies the cost of engaging them.

 

The company can then reinvest the money saved from not targeting less lucrative members to drive up the frequency of purchases made by their most engaged members. Thus, a strong CLV estimate may just lead to the conservation and expansion of company revenue.

 

Simply stated, well-designed loyalty programs drive up sales and increase a company’s bottom line, making them an invaluable strategy for marketing and finance departments alike.

 

The bottom line

Loyalty program marketers have a tremendous opportunity to increase brand loyalty while helping drive company revenue. Not only do they have detailed insight into their members, but they can provide critical information to finance about loyalty program liability, helping their company optimize its customer engagement strategy.

 

Loyalty program liability can be combated using precise estimates of user behavior drawn from granular-level information. This information will give your company the data it needs to construct an accurate model of its program liability, and draw the insights needed to generate a real return on its loyalty program investment.

 

 

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Looking to 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.

 

 

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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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