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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Is the GDPR Good or Bad News for Business

The European Union?s General Data Protection Act (GDPR) is a new data authority coming into force on 25 May 2018. It replaces the current Data Protection Directive 95/46/EC, while extending the remit to include the export of personal data outside the EU. It aims to give EU citizens and residents living there more control over their personal information. It also hopes to make regulatory compliance simpler for participating businesses.

The Broad Implications for Business
The GDPR puts another layer of accountability on businesses falling within its remit. It requires them to implement ?comprehensive but proportionate governance measures? including recording how they make decisions. The long-term goal is to reduce privacy infringements. In the short run, businesses without good governance may find themselves writing new policies and procedures.

Article 5 of the European Union?s General Data Protection Act lays down the following guidelines for managing personal data. This shall be ?
? Processed transparently, fairly, and lawfully
? Acquired for specific, legitimate purposes only
? Adequate, relevant and limited to essentials
? Not used for any other, incompatible purpose
? However it may be archived in the public interest
? Kept up to date with all inaccuracies corrected
? Ring-fenced when the information becomes irrelevant
? Adequately protected against unauthorised access
? Stored in a way that prevents accidental loss
Furthermore, affected businesses shall appoint a ?controller responsible for, and able to demonstrate, compliance with the principles.?

Implementing Accountability and Governance
The UK Information Commissioner?s Office has issued guidelines regarding provisions to assure governance and accountability. These are along the lines of the ?don’t tell me, show me? management approach the office has generally been following. In summary form, a business, and its controller must:
? Implement measures that assist it to ensure demonstrated compliance
? Maintain suitable, relevant records of personal data processing activities
? Appoint a dedicated data protection officer if scale makes this appropriate
? Implement technologies that ensure data protection by design
? Conduct data protection assessments and respond to results timeously

Implementing the General Data Protection Act in Ireland
The Irish Data Protection Commissioner has decided it is unnecessary to incorporate the GDPR into Irish law, since EU regulations have direct effect. The office of the Commissioner is working in tandem with data practitioners, and industry and professional bodies to raise awareness in business through 2017. It has produced a document detailing what it considers the essentials for business compliance. Briefly, these pre-requisites are:
? Ensure awareness among key personnel, and make sure they incorporate the GDPR into their planning
? Conduct an early assessment of quality management gaps, and budget for additional resources needed
? Do an audit of personal data held, to determine the origin, the necessity to hold it, and with whom shared
? Inform internal and external stakeholders of the current status, and your future plans to implement the GDPR
? Examine current procedures in the light of the new directive. Could you ?survive? a challenge from a data subject?
? Determine how you will process requests for access to the data in the future from within and outside your organization
? Assess how you currently obtain customer consent to store their data. Is this “freely given, specific, informed and unambiguous”?
? Find how you handle information from underage people. Do you have systems to verify ages and obtain guardian consent?
? Implement procedures to detect, investigate, and report data breaches to the Data Protection Commissioner within 72 hours
? Implement a culture of always assessing the effect on individual privacy before starting new initiatives

So Is the GDPR Good or Bad for Business
The GDPR should be good news for business customers. Their personal data will be more secure, and they should see their rate of spam marketing come down. The GDPR is also good news for businesses currently investing resources to protect their clients? interests. It could however, be bad news for businesses that have not been focussing on these matters. They may have a high mountain to climb to come in line with the GDPR.
Disclaimer: This article is for information only and not intended as a comprehensive guide.

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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

Still Looking For A Way To Consolidate Excel Spreadsheets?

We use Excel spreadsheets everyday. We use them to prepare budgets and reports. We even use them when drafting plans and forecasts. With this ubiquitous office application, entering data and carrying out on-the-spot computations and analysis is quick and easy. However, when it’s time to consolidate Excel data, I won’t be surprised if you wished there was an easy way.

In fact, you were probably looking for a solution before landing on this page, right?

Because budgeting, reporting, planning, and forecasting are normally done by a group of people and not just by one individual, spreadsheets bearing the necessary data can be scattered in different folders, desktops, offices, and, in the case of really large organisations, geographical locations.

How are these data brought together? Through email attachments or by sharing folders in a local area network. Each member of the working team sends out copies of their own spreadsheets to other members, who then review them, make necessary changes, then send back to the source. The files can go back and forth until everyone is satisfied.

With each sending, sharing, and edit, business critical data gets exposed to all sorts of spreadsheet risks. Copy-paste errors, omission of a negative sign, erroneous inputs, accidental deletions, and even fraudulent manipulations can take place. And because each member can end up with multiple versions of a single spreadsheet, the chance of working on the wrong version exists.

So when all the data gets consolidated and finalised, it is possible for the end product to contain significant errors. It may not happen all the time, but it certainly can happen.

But that’s not the only disadvantage of spreadsheets. The entire process of comparing cells and sheets, copy-pasting data, linking cells, writing formulas, and specifying ranges can be very tedious, not to mention time-consuming. With spreadsheets, beating deadlines is always an almost impossible exercise.

What you need is a solution that will no longer require you to consolidate Excel spreadsheets. One that is faster, more reliable, and significantly less error-prone. Denizon has a server-based solution that has all those capabilities and much more.

With a server-based solution, all your data is stored in one place. Everyone is working on the same data source, so consolidation is fast and easy. Everyone becomes synchronised and no one has to worry about working on the wrong version.

Read more about our server-based solution

Spreadsheet Risks in Banks

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Technical Debt Definition

Is there interest on technical debt?

Reasons For Getting Into Technical Debt

Types of Technical Debt

Final thoughts

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