Spreadsheet Fraud

To any company executive or business owner, the mere possibility of fraud can be enough to send alarm bells ringing – for good reason. In a prolonged recession, the last thing investors would want to discover is a huge, gaping hole where supposedly a neat profit should have been. Also to find out that such loss was brought about by deliberately falsified accounting and poor spreadsheet controls only makes the situation even more regrettable.

Why?

Because these losses would not have occurred had there been a stronger risk management program in place and more stringent quality control on critical data to begin with.

But given the nature of a spreadsheet system i.e. its sheer flexibility and easy accessibility, plus the fact that they were never intended to be enterprise-level tools, there are no hard and fast rules for auditing spreadsheets. Also because of the lack of internal controls for end user computing (EUC) applications, in this case spreadsheets, you can’t expect these systems to yield consistently accurate results.

In fact, most managers assume that major spreadsheet errors should result in figures that are blatantly out of touch with how things stand in the real world, making these errors easily detectable.

Well they assumed wrong. You’ll find cases where the losses ran to millions of dollars without anyone being the wiser.

In instances of fraud, the problem becomes more complicated as these errors are deliberately hidden and cleverly disguised, perhaps one erroneous cell at a time. Even if these cover-ups started out with smaller figures that may have had negligible impact on a company?s operation, the cumulative costs of these ?insignificant? errors multiply exponentially as the spreadsheets are reused and utilised as bases for other related reports.

While there is no generally accepted definition of the term ?spreadsheet fraud?, its quite easy to identify one when a case crops up. Fraud arising from spreadsheets are typically characterised by:

Fallacious inputs – correct figures are deliberately replaced with false values.

Erroneous outputs owing to data alteration – hyperlinks are linking to the wrong spreadsheets or cells; use of macros or special lines of code which are understandable only to the person who developed the code.

Concealment of critical information – can be done with easy ?tweaks? such as hidden rows and columns, using the same colour for both the font and the background, or hard coding additional values into a cell.

There is nothing really highly-sophisticated or technical in any of these methodologies. But without internal spreadsheet controls in place, it would take a discerning eye and a thorough review to catch the inconsistencies contained in a spreadsheet fraught with errors. Also, if these errors are knowingly placed there, the chances of finding them are close to nil.

Learn more about our server application solutions and discover a better way to protect your company from spreadsheet fraud.

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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

The Better Way of Applying Benford’s Law for Fraud Detection

Applying Benford’s Law on large collections of data is an effective way of detecting fraud. In this article, we?ll introduce you to Benford’s Law, talk about how auditors are employing it in fraud detection, and introduce you to a more effective way of integrating it into an IT solution.

Benford’s Law in a nutshell

Benford’s Law states that certain data sets – including certain accounting numbers – exhibit a non-uniform distribution of first digits. Simply put, if you gather all the first digits (e.g. 8 is the first digit of ?814 and 1 is the first digit of ?1768) of all the numbers that make up one of these data sets, the smallest digits will appear more frequently than the larger ones.

That is, according to Benford’s Law,

1 should comprise roughly 30.1% of all first digits;
2 should be 17.6%;
3 should be 12.5%;
4 should be 9.7%, and so on.

Notice that the 1s (ones) occur far more frequently than the rest. Those who are not familiar with Benford’s Law tend to assume that all digits should be distributed uniformly. So when fraudulent individuals tinker with accounting data, they may end up putting in more 9s or 8s than there actually should be.

Once an accounting data set is found to show a large deviation from this distribution, then auditors move in to make a closer inspection.

Benford’s Law spreadsheets and templates

Because Benford’s Law has been proven to be effective in discovering unnaturally-behaving data sets (such as those manipulated by fraudsters), many auditors have created simple software solutions that apply this law. Most of these solutions, owing to the fact that a large majority of accounting departments use spreadsheets, come in the form of spreadsheet templates.

You can easily find free downloadable spreadsheet templates that apply Benford’s Law as well as simple How-To articles that can help you to implement the law on your own existing spreadsheets. Just Google “Benford’s law template” or “Benford’s law spreadsheet”.

I suggest you try out some of them yourself to get a feel on how they work.

The problem with Benford’s Law when used on spreadsheets

There’s actually another reason why I wanted you to try those spreadsheet templates and How-To’s yourself. I wanted you to see how susceptible these solutions are to trivial errors. Whenever you work on these spreadsheet templates – or your own spreadsheets for that matter – when implementing Benford’s Law, you can commit mistakes when copy-pasting values, specifying ranges, entering formulas, and so on.

Furthermore, some of the data might be located in different spreadsheets, which can likewise by found in different departments and have to be emailed for consolidation. The departments who own this data will have to extract the needed data from their own spreadsheets, transfer them to another spreadsheet, and send them to the person in-charge of consolidation.

These activities can introduce errors as well. That’s why we think that, while Benford’s Law can be an effective tool for detecting fraud, spreadsheet-based working environments can taint the entire fraud detection process.

There?s actually a better IT solution where you can use Benford’s Law.

Why a server-based solution works better

In order to apply Benford’s Law more effectively, you need to use it in an environment that implements better controls than what spreadsheets can offer. What we propose is a server-based system.

In a server-based system, your data is placed in a secure database. People who want to input data or access existing data will have to go through access controls such as login procedures. These systems also have features that log access history so that you can trace who accessed which and when.

If Benford’s Law is integrated into such a system, there would be no need for any error-prone copy-pasting activities because all the data is stored in one place. Thus, fraud detection initiatives can be much faster and more reliable.

You can get more information on this site regarding the disadvantages of spreadsheets. We can also tell you more about the advantages of server application solutions.

2015 ESOS Guidelines Chapter 6 – Role of Lead Assessor

The primary role of the lead assessor is to make sure the enterprise?s assessment meets ESOS requirements. Their contribution is mandatory, with the only exception being where 100% of energy consumption received attention in an ISO 50001 that forms the basis of the ESOS report.

How to Find a Lead Assessor

An enterprise subject to ESOS must negotiate with a lead assessor with the necessary specialisms from one of the panels approved by the UK government. This can be a person within the organisation or an third party. If independent, then only one director of the enterprise need countersign the assessment report. If an employee, then two signatures are necessary. Before reaching a decision, consider

  • Whether the person has auditing experience in the sector
  • Whether they are familiar with the technology and the processes
  • Whether they have experience of auditing against a standard

The choice rests on the enterprise itself. The lead assessor performs the appointed role.

The Lead Assessor?s Role

The Lead Assessor?s main job is reviewing an ESOS assessment prepared by others against the standard, and deciding whether it meets the requirements. They may also contribute towards it. Typically their role includes:

  • Checking the calculation for total energy consumption across the entire enterprise
  • Reviewing the process whereby the 90% areas of significant consumption were identified
  • Confirming that certifications are in place for all alternate routes to compliance chosen
  • Checking that the audit reports meet the minimum criteria laid down by the ESOS system

Note: A lead assessor may partly prepare the assessment themselves, or simply verify that others did it correctly.

In the former instance a lead assessor might

  • Determine energy use profiles
  • Identify savings opportunities
  • Calculate savings measures
  • Present audit findings
  • Determine future methodology
  • Define sampling methods
  • Develop audit timetables
  • Establish site visit programs
  • Assemble ESOS information pack

Core Enterprise Responsibilities

The enterprise cannot absolve itself from responsibility for good governance. Accordingly, it remains liable for

  • Ensuring compliance with ESOS requirements
  • Selecting and appointing the lead assessor
  • Drawing attention to previous audit work
  • Agreeing with what the lead assessor does
  • Requesting directors to sign the assessment

The Environment Agency does not provide assessment templates as it believes this reduces the administrative burden on the enterprises it serves.

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