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.

More Spreadsheet Blogs


Spreadsheet Risks in Banks


Top 10 Disadvantages of Spreadsheets


Disadvantages of Spreadsheets – obstacles to compliance in the Healthcare Industry


How Internal Auditors can win the War against Spreadsheet Fraud


Spreadsheet Reporting – No Room in your company in an age of Business Intelligence


Still looking for a Way to Consolidate Excel Spreadsheets?


Disadvantages of Spreadsheets


Spreadsheet woes – ill equipped for an Agile Business Environment


Spreadsheet Fraud


Spreadsheet Woes – Limited features for easy adoption of a control framework


Spreadsheet woes – Burden in SOX Compliance and other Regulations


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Server Application Solutions – Don’t let Spreadsheets hold your Business back


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Failure Mode and Effects Analysis

 

Any business in the manufacturing industry would know that anything can happen in the development stages of the product. And while you can certainly learn from each of these failures and improve the process the next time around, doing so would entail a lot of time and money.
A widely-used procedure in operations management utilised to identify and analyse potential reliability problems while still in the early stages of production is the Failure Mode and Effects Analysis (FMEA).

FMEAs help us focus on and understand the impact of possible process or product risks.

The FMEA method for quality is based largely on the traditional practice of achieving product reliability through comprehensive testing and using techniques such as probabilistic reliability modelling. To give us a better understanding of the process, let’s break it down to its two basic components ? the failure mode and the effects analysis.

Failure mode is defined as the means by which something may fail. It essentially answers the question “What could go wrong?” Failure modes are the potential flaws in a process or product that could have an impact on the end user – the customer.

Effects analysis, on the other hand, is the process by which the consequences of these failures are studied.

With the two aspects taken together, the FMEA can help:

  • Discover the possible risks that can come with a product or process;
  • Plan out courses of action to counter these risks, particularly, those with the highest potential impact; and
  • Monitor the action plan results, with emphasis on how risk was reduced.

Find out more about our Quality Assurance services in the following pages:

Which KPI?s to Use in CRM

Customer relationship management emerged in the 1980?s in the form of database marketing. In those tranquil pre-social media days, the possibility of ?managing? clients may have been a possibility although Twitter and Facebook took care of that. Modern managers face a more dynamic environment. If you are one, then what are the trends you should be monitoring yourself (as opposed to leaving it to others).

If you want to drip feed plants, you have to keep the flow of liquid regular. The same applies to drip-feed marketing. Customers are fickle dare we say forgetful. Denizon recommends you monitor each department in terms of Relationship Freshness. When were the people on your list last contacted, and what ensued from this?

Next up comes the Quality of Engagements that follow from these efforts. How often do your leads respond at all, and how many interfaces does it take to coax them into a decision? You need to relate this to response blocks and unsubscribes. After a while you will recognise the tipping point where it is pointless to continue.

Response Times relate closely to this. If your marketing people are hot then they should get a fast response to sales calls, email shots and live chats. It is essential to get back to the lead again as soon as possible. You are not the only company your customers are speaking too. Fortune belongs to the fast and fearless.

The purpose of marketing is to achieve Conversions, not generate data for the sake of it. You are paying for these interactions and should be getting more than page views. You need to drill down by department on this one too. If one team is outperforming another consider investing in interactive training.

Finally Funnel Drop-Off Rate. Funnel analysis identifies the points at which fish fall off the hook and seeks to understand why this is happening. If people click your links, make enquiries and then drift away, you have a different set of issues as opposed to if they do not respond at all.

You should be able to pull most of this information off your CRM system if it is half-decent, although you may need to trigger a few options and re orientate reporting by your people in the field. When you have your big data lined up speak to us. We have a range of data analysts brimming over with fresh ideas.

Monitoring Water Banks with Telemetrics

Longstanding droughts across South Australia are forcing farmers to rethink the moisture in the soil they once regarded as their inalienable right. Trend monitoring is an essential input to applying pesticides and fertilisers in balanced ratios. Soil moisture sensors are transmitting data to central points for onward processing on a cloud, and this is making a positive difference to agricultural output.

Peter Buss, co-founder of Sentek Technology calls ground moisture a water bank and manufactures ground sensors to interrogate it. His hometown of Adelaide is in one of the driest states in Australia. This makes monitoring soil water even more critical, if agriculture is to continue. Sentek has been helping farmers deliver optimum amounts of water since 1992.

The analogy of a water bank is interesting. Agriculturists must ?bank? water for less-than-rainy days instead of squeezing the last drop. They need a stream of online data and a safe place somewhere in the cloud to curate it. Sentek is in the lead in places as remote as Peru?s Atacamba desert and the mountains of Mongolia, where it supports sustainable floriculture, forestry, horticulture, pastures, row crops and viticulture through precise delivery of scarce water.

This relies on precision measurement using a variety of drill and drop probes with sensors fixed at 4? / 10cm increments along multiples of 12? / 30cm up to 4 times. These probe soil moisture, soil temperature and soil salinity, and are readily re-positioned to other locations as crops rotate.

Peter Buss is convinced that measurement is a means to the end and only the beginning. ?Too often, growers start watering when plants don’t really need it, wasting water, energy, and labour. By monitoring that need accurately, that water can be saved until later when the plant really needs it.? He goes on to add that the crop is the ultimate sensor, and that ?we should ask the plant what it needs?.

This takes the debate a stage further. Water wise farmers should plant water-wise crops, not try to close the stable door after the horse has bolted and dry years return. The South Australia government thinks the answer also lies in correct farm dam management. It wants farmers to build ones that allow sufficient water to bypass in order to sustain the natural environment too.

There is more to water management than squeezing the last drop. Soil moisture goes beyond measuring for profit. It is about farming sustainably using data from sensors to guide us. ecoVaro is ahead of the curve as we explore imaginative ways to exploit the data these provide for the common good of all.

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