Benefits of structured financial data

The costs, complexities and inefficiencies related to analyzing, monitoring, auditing and reporting on business and financial data are significant. They impact businesses and nonprofits, software developers that create and maintain solutions in this space, and consumers of business and financial data such as regulators, banks, accountants, and auditors.

All these activities require the creation of different, specialized views on the same underlying raw business data. Business data is the normal output of day-to-day business operations: invoices, payments, carbon credits, accounting entries and other transactions. These documents, entries and transactions are the language that businesses and nonprofits use every day.

When it comes to enabling internal management to assess the performance of their company though, this day-to-day business language must be translated into aggregated amounts and KPIs that make immediate sense to them.

Another example is the language used in Government compliance. This could not be more different from business language. Tax returns, financial statements, and other reports are derived from business data, but the rules of derivation are complex and change frequently. Regulators impose on each business to perform the translation between the two. Each regulator uses a different language, which means that the same business data must be translated in several different ways. Each year rules change and new ones are issued. Each translation must be changed.

All these translations are hardcoded in business software and, pervasively, in manual spreadsheets. Their creation and maintenance is the main source of reporting costs and inefficiencies for businesses and nonprofits, which are significant. Global estimates indicate that the average amount of resources that organizations of all kinds waste in the assembly of reports is 30% of their total administrative costs. For example, in Australia, where efforts to move to structured data to reduce compliance burden are under way through the Standard Business Reporting Program[1], a Deloitte study published in 2014 estimates the cost of compliance reporting for Australian businesses at AU$ 95 billion per year.[1]

The role of structured data

TALTIO and other similar formats, such as XBRL Global Ledger (XBRL GL)[2] on which TALTIO is based, are designed to address this problem. They are structured, standardized formats that represent business data and the translation logic applied to it to derive the different views applied to business data: compliance and other external reporting, management reporting, auditing, data monitoring. These views are also represented with standard formats broadly used globally, such as the Extensible Business Reporting Language (XBRL).[3]

This framework makes it possible for regulators and other parties that consume business and financial data to publish the views that they require to understand the data as XBRL taxonomies, together with the logic necessary to populate those views from raw business data. Consequently, the burden of translating business language into other languages does not rest with each individual business, rather the translation is performed once by the party that consumes the information. Also, the translation logic does not need to be hardcoded in business software or embedded in manual spreadsheets any more – they just need to have the capability to understand and process the TALTIO format. The root causes for costs and inefficiencies related to internal and external reporting disappear.


The introduction of structured data brings significant benefits to three main categories of stakeholders: businesses and nonprofits, business software developers, and regulators and other consumers of business and financial data.

Businesses and nonprofits

  • Elimination of the costs and burden related to the creation and maintenance of the logic necessary to translate raw business data into compliance forms and other views created for the benefit of business data consumers.
  • Transition from a retail to a wholesale model for collection of regulatory information and other aggregated data derived from raw business data. The retail model is the traditional one, where regulators and other data consumers collect the information they need from each organization through forms and portals. In a wholesale model, data collection happens through features that software developers build into natural business systems, and is a by-product of normal business operations. This translates into seamless and connected services.
  • Easy identification of duplicates in the information that organizations provide to data consumers. In the compliance space this leads to a significant reduction in the information collected by different regulators, and in greater data quality and usability.
  • Ability to use business management software and systems that support interoperability for all information exchanges in the digital economy.
  • Ability to improve the interoperability of data across different business systems and reduce inefficient, manual data-related internal processes typically based on spreadsheets. Software vendors develop products to meet common requirements and cannot meet all the data management and reporting needs across the extremely varied practices of the business community. Indeed, the reality is that any business of any size battle with a proliferation of spreadsheets within their organizations. It is a fact that the “last mile” of reporting, internal and external, happens in spreadsheets, and this is a symptom of a gap between business requirements and how they are supported in business software.

Business software developers

  • Lower investment on creation and maintenance of business software.
  • Increased business opportunities, diversification, new business models based on structured data.
  • Ability to leverage structured data for all information exchanges in the digital economy.

Regulators and other business and financial data consumers

  • Access to accurate, real-time, high quality data, enabling timely and responsive decision making.
  • Complete interoperability between regulators, the software industry, and the business community, by encouraging the use of a single language that is also closely aligned with the language used by businesses in their day-to-day operations.


Evidence from jurisdictions where structured data is already used speaks for itself. In 2014-2015, the already mentioned Australian Standard Business Reporting Program recorded some $400 millions in compliance savings[4] across two spheres: business-to-business and business-to-Government. An Australian Government/Deloitte report estimated savings of $1.1 billion for 2015-16[5]; these savings are projected to increase substantially in future years as the Program further expands.

These savings are very sizeable both in themselves and in relation to the size of the Australian economy. They are a good indicator of the positive impact that the introduction of TALTIO and similar structured business and financial data formats can deliver.

Gianluca Garbellotto, CEO





[6] Australian Government, Report of the Australian Business Registrar, 2014-15(“ABR Report), page 3.

[5] Australian Taxation Office and Deloitte, ABR Program Savings Review (“Deloitte Report”), March 24, 2016, page 26.