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.

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ESOS Guide for UK Manufacturers Available

The Engineering Employers’ Federation (EEF) is the UK’s largest sectoral structure. Its goal is to promote the interests of manufacturing, engineering and technology-based businesses in order to enhance their competitiveness.

EEF has positioned itself in London and Brussels in order to be in a position to lobby at EU and Westminster level. Part of its role is helping its members adapt to change and capitalise on it. When it discovered that a third of UK manufacturers must comply with ESOS (and 49% had not even heard of it) EEF decided it was time to publish a handbook for its members.

According to EEF’s head of climate and environment policy Gareth Stace, For the many manufacturers that have already taken significant steps to improve energy efficiency, ESOS can be viewed as a ?stock taking exercise?, ensuring that momentum is maintained and new measures are highlighted and taken when possible?.

He goes on to add that others that have not begun the process should view it as an ‘impetus’ to go head down and find the most cost-effective ways to slash energy costs. Ecovaro adds that they would also have the opportunity to reduce carbon emissions almost as a by-product.

Firms with more than 250 employees, over 250 million revenue or both must comply with ESOS across all UK sectors. In simplest terms, they must have conducted an energy audit by 5th December 2015, and logged their energy saving plan with the Environmental Agency that is Britain?s sustainability watchdog.

The Department of Energy & Climate Change (DEEC) that oversees it believes that large UK businesses are wasting ?2.8 billion a year on electricity they do not need. Clearly it makes sense to focus on larger targets; however EcoVaro believes those halfway to the threshold should voluntarily comply if cutting their energy bills by 25% sounds appealing.

We are able to assist with interpreting their energy audits. These are often a matter of installing sub-meters at distribution points, and reading these for a few representative months to establish a trend. Meters are inexpensive compared to electricity costs, and maintenance teams can install them during maintenance shutdowns.

Ecovaro helps these firms process the data into manageable summaries using cloud-based technology. This is on a pay-when-used basis, and hence considerably cheaper than acquiring the software, or appointing a consultant.

A Small External Enterprise Development Team is Cheaper than Your Own

Time is money in the application development business. We have to get to market sooner so someone else does not gazump us, and pip us at the post. We increase the likelihood of this with every delay. Moreover, the longer your in-house team takes to get you through the swamp, the higher the project cost to you.

Of course, in theory this should not be the case. Why bring in a team from outside, and pay more to support their corporate structure? Even going for a contract micro team ought not to make financial sense, because we have to fund their mark-up and their profit taking. Our common sense tells us that this is crazy. But, hold that thought for a minute. What would you say if a small external enterprise development team was actually cheaper? To achieve that, they would have to work faster too.

The costs of an Enterprise Internal Development Team

Even if you were able to keep your own team fully occupied ? which is unlikely in the long term ? having your own digital talent pool works out expensive when you factor in the total cost. Your difficulties begin with the hiring process, especially if you do not fully understand the project topic, and have to subcontract the hiring task.

If you decide to attempt this yourself, your learning curve could push out the project completion date. Whichever way you decide to go, you are up for paying advertising, orientation training, technical upskilling, travel expenses, and salaries all of which are going to rob your time. Moreover, a wrong recruitment decision would cost three times the new employee?s annual salary, and there is no sign of that changing.

But that is not all, not all by far. If want your in-house team to keep their work files in the office, then you are going to have to buy them laptops, plus extra screens so they can keep track of what they are doing. Those laptops are going to need desks, and those employees, chairs to sit in. Plus, you are going to need expensive workspace with good security for your team?s base.

If we really wanted to lay it on, we would add software / cloud costs, telephony, internet access, and ongoing technical training to the growing pile. We did a quick scan on PayScale. The median salary of a computer programmer in Ireland is ?38,000 per year and that is just the beginning. If you need a program manager for your computer software, their salary will be almost double that at ?65,000 annually.

Advantages of R&D outsourcing

The case for a small externally sourced enterprise development team revolves around the opportunity cost ? or loss to put in bluntly ? of hiring your own specialist staff for projects. If you own a smaller business with up to 100 people, you are going to have to find work for idle digital fingers, after you roll out your in-house enterprise project. If you do not, you head down the road towards owning a dysfunctional team lacking a core, shared objective to drive them forward.

Compared to this potential extravagance, hiring a small external enterprise development team on an as-needed basis makes far more sense. Using a good service provider as a ?convenience store? drives enterprise development costs down through the floor, relative to having your own permanent team. Moreover, the major savings that arise are in your hands and free to deploy as opportunities arise. A successful business is quick and nimble, with cash flow on tap for R & D.

Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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