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Spreadsheet Risks in Banks

No other industry perhaps handles such large volumes of critical financial data more than the banking industry. For decades now, spreadsheets have become permanent fixtures in the front-line reporting tool sets of banks, providing organised information when and where needed.

But as banks enter into a period of heightened credit risks, elevated levels of fraud, and greater regulatory scrutiny, many are wondering if continued reliance on spreadsheets is a wise decision for banks today.

The downfall of Lehman Brothers which eventually led to its filing for Chapter 11 bankruptcy protection on September 15, 2008, served as a wake up call for many institutions across the globe to make a serious examination of their own risk management practices. But would these reforms include evaluating the security of user developed applications (UDAs), the most common of which are spreadsheets, and putting specific guidelines as to when they can – or cannot be – used?

Banks and Spreadsheet Use

Banks have been known to utilise spreadsheets systems for many critical functions because most personnel are well-acquainted with them, and the freedom of being able to develop customised reports without needing to consult with the IT department offers flexibility and convenience. In fact, more than having a way to do financial budgeting and analysing customer profitability, even loan officers and trade managers have become reliant on spreadsheets for risk management reporting and for making underwriting decisions.

But there are more than a few drawbacks to using spreadsheets for these tasks, and the sooner bank executives realise these, the sooner they can adopt better solutions.

General Limitations

Spreadsheets are far from being data base systems and yet more often than not, they are expected to act as such, with figures constantly added and formulas edited to produce the presumably right set of reports.

In addition, data integrity is always a cause for concern as most values in spreadsheets are entered as manual inputs. Even the mere misplacement of a comma or a negative sign, or an inadvertent “edit” to a formula can also be a source of significant changes in the outcome.

Confidentiality risk is also another drawback of the use of spreadsheets in banks as these tools do not have adequate access controls to limit access to only authorised individuals. Pertinent financial information that fall into the wrong hands can lead to a whole new set of problems including the possibility of fraud.

Risks in Trading

For trading transactions, spreadsheets can prove to be of immense use – but only for small market volumes. As trade volumes increase and the types vary, spreadsheets are no longer a viable solution and may likely become more of a hindrance, with calculations taking longer in the face of bigger transaction amounts and growing transaction data.

And in trading, there is always the need for rigorous computational functions. Computing for the Value at Risk (VaR) for large portfolios for instance, is simply way beyond the capabilities of spreadsheets. Banks that persist in using them are increasing the risk of loss on those portfolios. Or, they can be opening up opportunities for fraud as Allied Irish Bank (in the case of John Rusnak – $690 million) learned the hard way.

Risks in Underwriting

Bankers who use spreadsheets as their main source of information for underwriting procedures also face certain limitations. Loan transactions require that borrowers’ financial data be centralised and easily accessible to risk officers and lending officers involved in making decisions. With spreadsheets, there is no simple and secure way of doing that. Information can be pulled from different sources – individual tax returns, corporate tax documents, partnership documents, audited financial statements – hence there is difficulty in verifying that these reports adhere to underwriting policies.

Spreadsheet control and monitoring

Financial institutions which are having difficulty weaning themselves from the convenience and simplicity that spreadsheets offer are looking for possible control solutions. Essentially, they want to find ways that allow them to continue using these UDAs and yet somehow eliminate the spreadsheet risks and limitations involved.

Still, the debate goes back and forth on whether adequate control measures can be implemented on spreadsheets so that that the risks are mitigated. Many services have come forward to herald innovative solutions for better spreadsheet management. But at the end of the day, there really is no guarantee that such solutions would suffice.

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Disadvantages of Spreadsheets – Obstacles to Compliance in the Healthcare Industry

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Most of the regulatory compliance issues we talked about concerning spreadsheets have been related to financial data. But there are other kinds of data that are stored in spreadsheets which may also cause regulatory problems in the future.

In the US, a legislation known as HIPAA or Health Insurance Portability and Accountability Act is changing the way health care establishments and practitioners handle patient records. The HIPAA Privacy Rule is aimed at protecting the privacy of individually identifiable health information a.k.a. protected health information (PHI).

Examples of PHI include common identifiers like a patient’s name, address, Social Security Number, and so on, which can be used to identify the patient. HIPAA covers a wide range of health care organisations and service providers, including: health plan payers, health care clearing houses, hospitals, doctors, dentists, etc.

To protect the confidentiality, integrity, and availability of PHI, covered entities are required to implement technical policies such as access controls, authentication, and audit controls. These can easily be implemented on server-based systems.

Sad to say, many health care organisations who have started storing data electronically still rely on spreadsheet-based systems. Those policies are hard to implement in spreadsheet-based systems, where files are handled by end-users who are overloaded with their main line of work (i.e. health care) and have very little concern for data security.

In some of these systems, spreadsheet files containing PHI may have multiple versions in different workstations. Chances are, none of these files have any access control or user authentication mechanism whatsoever. Thus, changes can easily be made without proper documentation as to who carried out the changes.

And because the files are normally easily accessible, unauthorised disclosures – whether done intentionally or accidentally – will always be a lingering threat. Remember that HIPAA covered entities who are caught disclosing PHI can be fined from $50,000 up to $500,000 plus jail time.

But that’s not all. Through the HITECH Act of 2009, business associates of covered entities will now have to comply with HIPAA standards as well. Business associates are those companies who are performing functions and services for covered entities.

Examples of business associates are accounting firms, law firms, consultants, and so on. They automatically need to comply with the standards the moment they too deal with PHI.

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

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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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