From template cells to data points
In a template, a number is defined by where it sits: row 120, column 30. In a data point model, it is defined by what it is. Loans to non-financial corporations, in euro, more than 90 days past due, at the reporting date, becomes one data point described by a metric and a set of dimensions.
The same data point can then appear in several templates, but it is defined once, owned once and validated once. Templates become views of the model rather than the model itself.
How DPM relates to XBRL
The EBA describes its DPM as a structured representation of the data, the business concepts behind it and their relationships and validation rules. The XBRL taxonomy then expresses that model in a technical format for transmitting and validating data (EBA). Put simply, the DPM says what is reported and the taxonomy says how it travels.
DPM 2.0
The EBA has moved its data dictionary to DPM 2.0, a refit of the methodology, finalised in reporting framework 4.2. EIOPA uses the same approach for Solvency II, pension funds, the pan-European personal pension product and financial conglomerates. The aim is a consistent dictionary across European prudential and resolution reporting.
Why it matters outside Europe
Any supervisor designing new returns faces the same problem: the same figure defined slightly differently in three reports, collected three times and reconciled by hand. Data point thinking fixes that at the design stage, and it is also the natural route to granular collection, because each data point can later be derived from underlying records instead of being reported.
Where AI fits, and where people decide
AI can help map a firm’s internal data to data points, explain a definition in plain language and show which templates and rules a proposed change would affect. Supervisors approve definitions and changes. The model is the authority, so people who understand the policy must own it.
- 1List the figures that appear in more than one return today.
- 2Give each one a single definition and a named owner.
- 3Describe each by its dimensions, not by its position in a template.
- 4Write validation rules against data points, not cells.
- 5Generate templates and taxonomies from the model, never the other way round.
Where Line4 fits
Line4 is a SupTech platform for financial regulators. It collects returns in XBRL, Excel and CSV, validates them against your taxonomies and rules at the point of submission, and puts AI to work reading them, with supervisors making every decision. If you work with a standard we have not yet run in production, we will say so plainly and show you how we would approach it.
Questions
What is a data point model?
A data point model defines reporting requirements as individual data points, each described by a metric and a set of dimensions, instead of as positions on fixed templates.
What is DPM 2.0?
DPM 2.0 is a refit of the data point modelling methodology. The EBA finalised the transition of its data dictionary to DPM 2.0 in reporting framework 4.2.
What is the difference between DPM and XBRL?
The DPM describes what is reported in business terms. The XBRL taxonomy is the technical format generated from the DPM to transmit and validate the data.
Who uses data point models?
European supervisory reporting is built on them, through the EBA for banking and EIOPA for insurance and pensions. Any authority can apply the same approach to its own returns.