For many of the financial reporting questions of the day, the right way forward is self-evident and direct. “Build it and they will come,” I say.
But far too often, policy makers allow themselves to be bogged down by executive-class luddites and their minions who will say or do almost anything to preserve the advantages conveyed to them by the status quo.
The resistance to XBRL is a prime example. I will grant that a good-faith exchange of ideas can take place about how to “build” the XBRL disclosure system; but the “will they come?” question is a no-brainer that has to trump the cavils of the luddites.
Similarly, the FASB should take it as a given that XBRL will be a game changer for accounting standards. For example, the question of “net income” versus “other comprehensive income” fades to insignificance so long as an analyst can make her own pro forma reclassification that automatically flows through to ratios and valuation models – with just a few clicks on a web page.
Another policy implication is that the FASB should be ensuring that users have access to enough quantitative data to unwind a stinky accounting treatment and/or to obtain a more profound understanding of reported earnings and changes in financial position. I have mentioned on more than one occasion that detailed reconciliations (roll-forwards) of balance sheet accounts combined with XBRL data tagging would be just the ticket for shedding light on financial results — without having to resort to manual deciphering of obscurantic narrative disclosures. If the FASB does not put XBRL front and center in its disclosure framework project, then it is doomed to fail miserably.
Journalists in search of controversy where none should exist have reported on how financial professionals have found little use for XBRL, but that was before companies like Thinknum came on the scene. I get about one email each week from a start-up company that offers to write a blog post for me – about their product. For them, I have made an exception, because they seem to be among the first real players to step on the field of dreams that is XBRL.
By way of background, Thinknum founders Justin Zhen and Greg Ugwi met at Princeton but went their separate ways after graduation; Greg to Goldman Sachs and Justin to a hedge fund. After learning with some chagrin that the financial analysis tools available to them as professionals could be vastly improved, they left their jobs and used their savings to start Thinknum. Current paying customers now include traders at bulge bracket wall street firms. To give you an idea of how they use XBRL data in the cash flow and time series analysis tools, here’s a brief excerpt from an interview they did with the CFA Institute:
“We collect market data from exchanges, company filings on XBRL EDGAR, and macroeconomic data from government agencies like FRED, EUROSTAT, Ireland’s CSO, and others. These agencies are independent, often territorial, and have little incentive to ensure their data releases play well to [sic] each other. By bringing all these diverse data sources together on one platform, Thinknum enables investors to make interesting connections.”
The following text and graphics was provided to me in response to examples that readers of the Accounting Onion would appreciate:
For example, Thinknum has developed the Plotter, an application that allows users to plot data from corporate filings over time by clicking on a label in the financial statements. The plotter makes over 70 basic valuation ratios readily available, and more importantly, we allow users to create ratios on the fly by simply using mathematical expressions. For example, to view Google’s financial leverage you can type total_assets(goog)/total_equity(goog). This app has become enormously popular with our users and would not have been possible without XBRL.
A major pain point for most analysts is spending hours building and updating models in Excel. These models are used to project a company’s earnings and hence that company’s valuation. We have watched investment bankers and traders spend countless nights poring over PDF documents to update their spreadsheet models. Using XBRL, we designed software that enables analysts to build cashflow models that are updated as soon as a company’s filings are released. Our clients have applied these models across hundreds of companies, greatly adding leverage to an analyst’s work. Automating these tedious tasks affords analysts the opportunity to focus on making better judgments about the quality of the numbers reported and other economic factors that are critical to successful fundamental investing.
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If these two smart guys have actually built the robust, user-friendly XBRL-based analysis package that they claim to have built, then the policy implications for the SEC and FASB are self-evident: build in more XBRL data; and more uses will come.