By Diane Robinette, CEO of Incisive Software
A digital transformation is well underway in the banking industry as financial institutions further evolve their internet and mobile banking services. In the mid- and back-office, manual technology and processes are being replaced with newer digital technology to support customer-facing systems and to modernize and streamline processes. Artificial intelligence (AI) and machine learning technology are also becoming increasingly more common for their ability to provide greater insight into needs and trends.
Significant strides have been made over the years, but the digital transition has been slow—until the pandemic. Worldwide pandemic-related shutdowns showcased the speed at which large-scale implementations can be completed when necessary. As banks move forward with digital technology transformations in 2021 and beyond, it is important that data integrity and risk management not be overlooked. Otherwise, they will expose themselves to financial and reputational risk.
According to a 2021 EY Financial Services report, How Bank Directors Govern Technology Transformation, CIOs and bank directors agree that top priorities for future technology must include deriving value from data and de-risking IT within the organization. As detailed in the report, generating value from data has been an increased area of focus as banks embrace a transformation agenda that’s defined more by business objectives than regulatory scrutiny. Better data integration and management are key to unlocking the business value of data. Yet, today, relatively few banks can comprehensively and accurately assess the quantity and quality of all their data, which is necessary to effectively govern it. The report further states such lack of visibility may compromise management decision-making and reporting and increase financial and non-financial risks and costs for the organization.
A technology evolution
Successful banking and financial institutions are built on a foundation of accurate data. Confidence in the results they generate from complex models is essential to make shrewd business decisions— determining the value of a potential acquisition or investment, budgeting and forecasting, analyzing profitability and determining risk. These decisions, based on data assumed to be accurate, lead businesses to succeed or fail. More often than not, these critical business decisions rely on data imbedded in complex and highly-specialized spreadsheets. Yet just one poorly managed spreadsheet, fat finger error, incorrect formula or missed reference can open up an organization to operational risk that has the potential to cause significant financial and reputational loss, even lawsuits.
As organizations look for opportunities to modernize their processes and infrastructure with new digital technologies, software vendors vying to replace Excel are quick to call into question Excel’s long-term viability in a digital transformation.
In response to Excel’s vulnerabilities regarding risk management, Microsoft has released some major updates that bring new life to this time-tested technology. The most notable development, announced just this past December, is LAMBDA, a new feature that allows users to create custom functions based on Excel formulas. In principle, users can write any computation in the Excel formula language. Prior to LAMBDA, finance professionals had to go outside of Excel to do these calculations or, in a best-case scenario, perform the calculations in a complex macro. Both scenarios make validation difficult because of the lines of code. And, because calculations are taken outside of Excel, this is another point of failure and added level of complexity.
Powered by machine learning and artificial intelligence (AI), Analyze Data is another new capability. It automatically detects and highlights patterns significantly faster than a single human could. The new data analytic function helps users highlight spreadsheet data and offers several different ways to express that data visually. These are a few of several new capabilities Microsoft has introduced that modernize Excel, making it relevant in a vastly changed digital landscape.
Excel is unrivaled in its ability to handle complex models and calculations where data is continuously changing—it is here, when dealing with dynamic models, where its true value shines through. These spreadsheets are used for credit models, pricing models, underwriting models, tax provisions, tax reserves and more. Most recent capabilities added to Excel (and more on the way) are a noteworthy example of how this time-tested technology can adapt to evolving technology and business processes.
Even with thoughtful and deliberate advancements, some of the risks associated with Excel remain. All spreadsheets require some level of manual input and management, which puts the burden of accuracy and consistency back on the user. Alone, Excel provides no way to validate numbers or identify risks. Nor does it offer transparency or version control. The pandemic has made version control increasingly difficult to manage, as many work-from-home users plagued with bandwidth issues copy spreadsheets to local drives. Of course, the larger the model the more difficult it is to understand how that spreadsheet is built, including how it is connected to data sources and where those data sources are located.
Excel continues to be a powerful tool, and its use remains prevalent across organizations worldwide. Financial institutions that learn and use Excel’s evolved capabilities should remain mindful of risks including data integrity. Automated spreadsheet risk management technology ensures that data from which users base their analysis is accurate and complete. This technology is not a replacement for Excel. Rather, it complements Excel by addressing aforementioned risks while allowing organizations to benefit from its strengths. Spreadsheets combined with risk management technology provide valuable insight into potential risk and errors hiding in spreadsheets. Most importantly, automated spreadsheet risk management technology empowers finance professionals by ensuring the data from which business decisions are made is accurate and consistent.
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