Forensic accountingData analytics

Electronic data analysis is not new to CPAs in forensic accounting. But as companies today collect staggering amounts of information, forensic accountants are being increasingly relied on to dig deeper to detect high-risk activities or worse. Jemelyn Yadao finds out how big data is making their jobs both harder and easierIllustrations by Kouzou Sakai

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Forensic accountingData analytics

“ W here’s my cake?” is almost always a harmless question.

But for a team of forensic accoun-tants sifting through emails sent by a trader over two years, this phrase raised eyebrows – especially since it popped up 20,000 times.

“We all know that if you want to commit fraud, you’re not going to write [in an email] ‘I’m about to make an inside trade’,” says Eric Young, Partner of Fraud Investiga-tion and Dispute Services Greater China at EY Hong Kong. As part of an insider trading investigation, forensic specialists at the Big Four firm profiled a trader’s emails to find out the most common words used and checked it against trading system data. They discovered that the times the cake-seeking emails were sent out matched certain time stamps on the trading system. “Every time he made a trade, the email came up,” says Young. “We looked at trading system data, email system data and any other communication system data hap-pening in that investment bank by the trader and others involved. When you put all that together, you find out things that you didn’t know before.”

Until recent years, such subtle code words and phrases might have passed by unnoticed. The rise of big data comes with an increased risk of fraud – it’s harder to detect thanks to the sheer amount of information available. Increasingly, businesses are putting pressure on forensic accountants to better use big data to accomplish their goals and protect them.

Indeed, data analytics as a fraud prevention tool is becoming

the norm for forensic accountants around the world. According to the 2014 AICPA Survey on Interna-tional Trends in Forensic and Valuation Services, most of the CPA respondents who specialize in forensic and valuation services pointed to electronic data analysis, or big data, as the most pressing issue they will face in the next two to five years. Also, 85 percent of respondents expected an increase in the amount of time they spend on electronic data analysis in the near future.

This demand for a high level of data analysis capabilities from forensic accountants was evident in August as prosecutors in the Man-hattan District Attorney’s Office were wrapping up their fraud case against former leaders of the now-defunct global law firm Dewey & LeBoeuf. During the trial, forensic accountants painstakingly pored over the firm’s books for the years leading up to its 2012 bankruptcy. Andrea Gonzales of consulting firm Alverez & Marsal and her team reportedly spent about 1,300 hours on the project, reviewing more than 150,000 line items in Dewey’s accounting system.

In an increasingly global economy, data analytics have become especially vital as compa-

nies expand off-shore operations, which can potentially create new and unfamiliar risks. Companies are actively addressing a need to get data-collecting systems in different locations talking to each other. “The challenge right now is how can we centralize all the data into one location and analyse it globally rather than country by country,” says Young. “Companies are looking into this and that’s why there’s a big talk around big data, which is growing from giga-bytes towards zettabytes (1 trillion gigabytes) from structured and unstructured data.”

100 percent proof While it is well known that big data presents great opportunities for businesses to get actionable insights, experts point out the downsides. “A higher volume of data increases the workload and requires a larger team of forensic accountants, both mak-ing it harder to manage the project,” says Benny K.B. Kwok, Founder of Hong Kong-based independent practice Benny K B Kwok Forensic Expert and a Hong Kong Institute of CPAs member.

Challenges include not only big data being large in terms of volume, but also in variety. “The data to be analysed is typically a combination of structured, semi-structured data and unstructured data,” says Barry Tong, Partner of Advisory at Grant Thornton and an Institute member, who describes structured data as well-defined information such as transactions recorded in the database of a point-of-sales system, date and time of sales, and product names. Examples of unstructured data

“ Big data is growing from gigabytes towards zettabytes rom structured and unstructured data (1 trillion gigabytes).”

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include emails, word documents, social media posts and voice mails.

Time is also an obstacle as it is not easy to quickly obtain an overall picture due to large volumes of data. “Planning on how to mine from the data and accurate execu-tion of the data mining plan could be a challenge to forensic account-ing work,” says Tong.

With new types of data throw-ing up new challenges for forensic accounting professionals, experts agree that it’s crucial for them to embrace data analytics. “Data analysis tools allow you to look at the data from different angles to get to the root cause of fraud. Some of the ways data analysis is being used include trend and pattern analysis to look for indications of diver-sion of funds or theft, behavioural analysis and monitoring of spend-ing trends,” explains Tong.

Many forensic accountants are therefore moving away from traditional statistical sampling methods, which look at only a relatively small amount of data. This is a result of an increasingly sophisticated understanding of the potential of reviewing all informa-tion available. “Now companies are starting to realize that sampling doesn’t work. Clients in Asia have asked, ‘How do I use 100 percent of my data in order to understand where the challenges are in my business?’” says Young at EY.

“They can analyse 20 percent of their data, which is structured, but are unable to manage the remaining 80 percent, which is unstructured,” Young adds. While unstructured data is the most difficult to handle, the answers forensic accountants are looking for often lie within it.

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Forensic accountingData analytics

With the increased complex-ity of engagements, Y.L. Cheung, Partner of Financial Advisory at Deloitte and an Institute member, has witnessed his team go through an abrupt transformation. “We didn’t used to have a dedicated data analytics team within the forensics team until just two years ago,” he says. The task of catching out any standout patterns, anomalies or relationships between different databases was also unimaginable. “Many years ago, we couldn’t dive into the details of employee data or suppliers’ data to find anything that might indicate a strong connection between a particular employee and a supplier,” he adds. “It was basically impossible for humans to do this.”

Thanks to new technologies and forensic technology labs embedded in firms, some forensic CPAs are now used to dealing with tasks that require a higher level of data analy-sis. As an example, Tong at Grant Thornton cites a recent merger and acquisition case involving a China-based retail chain, which appointed the firm to verify the revenue and net profit of the target. The firm performed the once-impossible task of analysing millions of sales transactions. In the end, further investigation revealed fictitious sales that resulted in an overstate-ment in the target’s revenue of 20 percent. “By applying data analytic techniques we were able to pin-point the exact cause of irregularities in a timely manner.”

Reading between the linesBig data, over the next few years, will create new opportunities for

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forensic accountants to take a more proactive role in organiza-tions. It forces them, says experts, to develop new skills not only in analytics, but even in areas such as linguistics.

“We leverage a group of lin-guistic PhDs within EY to define phrases or ‘slang’ words that are used. Fraud can be described in ‘fraud triangle’ analytics tests,” says Young. The framework of a fraud triangle, as Young puts it, includes three areas – opportunity, pressure and rationalization – that explain the reasoning behind what drives a person to commit fraud.

“You can look at all this unstructured data, tap into the type of wordings used and how they represent the person’s current state of mind and behaviour,” he says. For example, he explains, phrases such as “my wife just delivered our baby” or “I just bought a house” potentially represent that the person is under pressure, whereas phrases like “I think it’s OK” or “let me give it a try,” could indicate that the person is rationalizing in his mind the act of cheating. “If you put all three [stages] together and then profile it, you may realize that whenever this person is aggres-sive or is emotionally unstable, his trading is aggressive. To a company that is a big risk.”

The use of important mathemat-ical tools is also increasingly taking place within forensics teams. “We have been applying advanced analytics, statistic modelling, into forensic data analytic solutions. You take all the population data, apply it to your statistic models with mathematic calculations and translate it into a risk number,”

says Young. This number churned out from huge amounts of data represents high risk, medium risk, low risk, allowing top-level management to understand and use it in decision-making. “A human mind can’t comprehend 1 billion transactions that a trading company makes everyday, but if you can summarize all that into a number, people will be able to know where the risks are.”

Science and artThe ability to collaborate closely with statisticians, mathematicians and IT specialists is also essential, particularly as forensic accountants move towards providing a new and critical service: making big data smaller. “To make big data useful, forensic accountants have to distill information into insights in a timely manner,” explains Tong at Grant Thornton.

Some forensic teams currently work with a business intelligence team to create user-friendly, easy-to-understand “dashboards” that graphically represent the data. “We divided the data sets into five categories: who, what, where, why

and how – This is combining sci-ence and art, better understanding the data sets through graphically structured format,” says Young. “The dashboard may look easy to the viewer but it’s actually derived from a million transactions, and data sets that don’t represent an issue or risks to the senior manage-ments are removed.”

Observers foresee forensic accountants becoming more future-facing, focusing on methods that leverage on previously recorded data, and identifying patterns to predict potential future behaviour or trends. This is so-called predic-tive modelling.

“During an analysis, we put that behaviour into the database so that next time that behaviour happens again, we can see that, ‘Here’s potentially an issue that happened in the past’,” says Young.

The drawback is that at the moment, in many cases, forensic accountants are still required to input this data manually. “Input-ting from scratch means the risk of more clerical errors, and the process would be more tedious and time-consuming, which may cause undue delay,” explains Kwok, the forensic practitioner.

Despite these challenges, many believe forensic accountants will continue to take up the oppor-tunity, offered by big data, to reinvent themselves. “The skills and expertise of forensic accoun-tants can be effectively applied to a more strategic role,” says Kwok. “While the traditional role of forensic accountants is to serve as an expert witness and investigator, now we’re moving beyond that.”

“ You can look at all this unstructured data, tap into the type of wordings used and how they represent the person’s current state of mind and behaviour.”

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