Rohit was on his way back from work when he bumped into his former classmate -Sushant at a metro station. Both were delighted to see each other after a long time and decided to spend the evening chatting over a cup of coffee. Rohit was a sector analyst with a leading brokerage company in India, while Sushant was working in the Financial Planning & Analysis department at an MNC. While discussing work, Sushant informed Rohit that their company was laying huge emphasis on learning Financial Modeling software and automating major portion of the task. This left Rohit worried. He still used traditional excel spreadsheets for his daily models. “Will my skills become extinct? Will I loose my job in the long-run?”, he thought.


Not only Rohit, but many analysts are going through this apprehension. Technology seems to have an answer to everything today. Traditionally financial modeling had been done on excel spreadsheets, but today there are many Business Intelligence Tools and software that can be used for financial modeling. Oracle BI, Business Objects, Hyperion, Operis, IBM Cognos & Quantrix are some of these tools which have gained popularity in recent times. However, can they replace excel as the ultimate basis for financial modeling?

Let us find out various factors that differentiates between the two:

Customization: Excel being operated by human modelers gives immense scope for customization. The model can be built on scratch, structured in the way one pleases and formatted according to the requirement of the situation. There can be various company specific or asset specific factors that need to be addressed exclusively in a particular model. This can only be possible in excel spreadsheet. On the other hand, a financial modeling software is pre-programmed and there is limited scope for any such customization.

Structured outcome: A financial modeling software is best suited for a definite structure of a model. These tools are programmed towards error prevention, hence the possibility of human error is minimal. An excel model, however, is quite prone to various degrees of human error. So, when it comes to standardization and accuracy, financial modeling software is the best bet.

Development of Analytical skills: If one has to understand the complexities of business and build the assumptions then working on excel financial model is the most appropriate way to do so. Building the model from scratch allows the analyst to develop critical thinking skills and add a personal touch to the model. On the flip-side, a financial modeling software, being automated, does not provide the opportunity to break the problem into parts and analyse issues at a granular level.

Risk Analysis (Monte Carlo Simulation): Risk Management is an important part of financial planning and analysis. Excel financial models have limitations on this front. Though a sensitivity analysis can be run on excel, it will be completely manual. In this case, a financial software is better equipped. Sensitivity Analysis and Monte Carlo Simulation can be easily performed on a software with a higher level of precision.

Logical interpretation: Financial Modeling is an application of logic, which is possible only in excel. Excel allows the modeler to trace the input, make assumption, study its linkage with the output and evaluate the formula. It is imperative to find inter-dependency of variables for establishing logic in financial modeling and it is difficult to do so in a software. The business intelligence tools for financial modeling has in built logic and it is difficult to analyse the flow of operations there.

Visual Representation: Visual representation is an integral part of financial modeling. We have already discussed the essentials of a visually appealing model in our previous post. Most of the Business Intelligence tools lack the visual representation effect. However, certain software like Operis and Analytica score on this front.

Handling diverse and complex data sets: While excel scores on most of the fronts, one cannot deny that it has certain limitations when it comes to huge data sets. The financial modeling software can handle multidimensional and extensive data sets. Most of them also allow flexibility to create and change the rows and columns layout of the model according to the goal of the problem at hand.


The above pointers tell us where the financial modeling software scores over the excel spreadsheet and where it doesn’t. It is evident that these softwares cannot replace the conventional excel spreadsheet in the current scenario. Automated results have their limitations and financial modeling skills in excel will continue to be in demand. These tools, however, may evolve to accommodate few more features in times to come. Hence, we cannot ignore it totally. One must keep up with the latest trends and learn these business intelligence tools for the certain benefits it has to offer.

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