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What is the level of complexity of financial models that a typical IB analyst has to make?

Investment Banking offers dynamic situations and challenges as a regular part of the business. There are no direct guidelines or standards that define the complexity of the financial models that IB analysts are expected to create or update on a regular basis.


Bulge Bracket IB: In case of analysts working in the bulge bracket investment banks which typically have teams covering different industry groups (like CHR : Consumer, Healthcare, Real Estate; TMT: Telecom, Media & Tech etc.), it is expected that an analyst understand the revenue drivers, cost drivers and the other working metrics of the cluster which he/she is a part of and create financial models.

Mid-market/Boutique IB: In this set-up, there are often no such industry based teams and the analyst can be made a part of the transaction based on his availability during that time. So it becomes even more challenging for the analyst to quickly switch hats and research the key levers that work in the industry of transaction under consideration at that given point of time


Keep the Axe Sharp, Always: Having said the above, it is very important for the analyst to always keep his/her arsenal of financial modeling knowledge and relevant application of concepts updated to deliver collaterals on tight deadlines.

It is important that the analyst is comfortable in creating the basic 3-statement financial model which more or less is consistent conceptually across the different sectors, however, the skill lies in understanding the various drivers of the business along with ability to read between lines to extract the logical forecasts. Th research skills play an important part here, running through various sources like 10Ks, investor presentations, call transcripts and also draft prospectus of recently IPO'd companies in the same sector give great insights and direction to make reasonable forecasts and assumptions.

A model is not "complex" but a mere reflection of the transaction structure proposed and designed by the investment bankers and the parties involved. A crucial part here is the availability of data. The analyst can showcase his skillset only if he has sufficient data available on his hands to make meaningful analysis. The granular the data available, the more detailed the model can become.

Apart from the regular financial model, it is important that analyst is comfortable in creating an LBO model, a model where infusion of capital through both debt and equity is demonstrated as most of the transactions in IB would require infusion/divestment of funds and merger modeling. Certain sectors require knowledge of specific treatments to some line items like R&D capitalization for research intensive sectors like pharma and software sectors, treatment and impact of operating leases etc.

The icing on the cake would be good excel skills along with a touch of macros where scenario driven and automated models can be created to perform sensitivity analysis covering multiple situations and outcomes.

To learn more about such detailed financial models and analysis important for investment banking refer the modules offered by Wizenius on

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