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


Spreadsheet Risk Issues


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


Why Spreadsheets can send the pillars of Solvency II crashing down

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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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Introduction to Matrix Management

A leader is responsible to empower his people and get the best out of them. Yet an organisational structure can either help or hamper performance. Worst, it can make or break success.

Looking at the fast-changing world of the global economy, whatsoever slows up and obstructs decision-making is a challenge. Hierarchical management is rather unattractive and functional silos are unlikable. Instead, employees desire to create teams equipped with flexibility, cooperation and coordination.

Recognising that companies have both vertical and horizontal chains of command, the matrix model is created. The concept of this principle lies in the ability to manage the collaboration of people across various functions and achieve strategic objectives through key projects.

Consider this scenario:

Ian is a sales executive of a company. His role is to sell a new product under the supervision of a product manager. The manager is expert about the product and she is accountable to coordinate the people across the organisation, making sure the product is achieved.

Moreover, Ian also reports to the sales manager who oversees his overall performance, monitors his pay and benefits and guides his personal development.

Complicated it may seem but this set-up is common to companies that seek to maximise the effect of expert product managers, without compromising the function of the staffing overhead in control of the organisation. This is a successful approach to management known as Matrix Management.

Matrix Management Defined

Matrix management is a type of organisational management wherein employees of similar skills are shared for work assignments. Simply stated, it is a structure in which the workforce reports to multiple managers of different roles.

For example, a team of engineers work under the supervision of their department head, which is the engineering manager. However, the same people from the engineering department may be assigned to other projects where they report to the project manager. Thus, while working on a designated project, each engineer has to work under various managers to accomplish the job.

Historical Background

Although some critics say that matrix management was first adopted in the Second World War, its origins can be traced more reliably to the US space programme of the 1960’s when President Kennedy has drawn his vision of putting a man on the moon. In order to accomplish the objective, NASA revolutionised its approach on the project leading to the consequent birth of ?matrix organisation?. This strategic method facilitated the energy, creativity and decision-making to triumph the grand vision.

In the 1970’s, matrix organisation received huge attention as the only new form of organisation in the twentieth century. In fact it was applied by Digital Equipment, Xerox, and Citibank. Despite its initial success, the enthusiasm of corporations with regards to matrix organisation declined in the 1980’s, largely because it was complex.

Furthermore, the drive for motivating people to work creatively and flexibly has only strengthened. And by the 1990’s, the evolution of matrix management geared towards creation and empowerment of virtual teams that focused on customer service and speedy delivery.

Although all forms of matrix has loopholes and flaws, research says that until today, matrix management is still the leading approach used by companies to achieve organisational goals.

Energy efficiency- succeed and benefit

Energy is neither created nor destroyed; it is only transformed. This being the law of conservation of energy, and given that the process of transforming energy is inefficient resulting in loss of usable energy in the process of transforming one form of energy into another form, Energy Efficiency finds a home.
Talking of Energy efficiency, think of how much useful energy can be obtained from a system or a particular technology. It is also about the use of technology that requires a lesser amount of energy to carry out the same task.

Energy efficiency is the responsibility of both demand side and supply side. Supply-side energy efficiency refers to a set of actions taken to ensure efficiency through the electricity supply chain. Supply side efficiency measures are about efficiency in electricity generation; be it operation and maintenance of existing equipment or upgrading existing equipment with state-of-the-art energy-efficient generating equipment.

The demand side energy efficiency on the other hand refers to the actions taken to use less/demand less energy. Think of less energy usage in relation to improvement of energy efficiency in buildings, solar water heaters, energy efficient lighting systems such as Compact Fluorescent Lamps, conducting energy audits to identify potential energy saving opportunities, efficient water heating systems and the list is endless.

Success of energy efficiency is a win ? win to YOU-ME-US – the energy consumers, to THEM the energy producers and suppliers and to our precious ENVIRONMENT.
Gain to energy suppliers: – Less energy usage and better energy usage patterns among consumers consequently reduces the customer load which reduces losses on the supply side. Less energy loss creates capacity on the system to serve more customers.

Gain to you-me-us: – Less energy usage and better energy usage patterns Benefits the customer through reduced Electricity bills / $ savings through lower bills.

Benefits to the environment: – Usage of less energy reduces use of fossil fuels, hence reduction in GHG emissions hence conserving our environment. Companies look at means to make rational use of their least efficient generating equipment. The objective is to improve the operation and maintenance of existing equipment or upgrade it with state-of-the-art energy-efficient technologies. Some companies have on-site electricity generation alternatives and thus tend to consider the supply side in addition to demand-side energy efficiency.

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