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Data Verification: How to Trust This Balance Sheet?

So, the latest trend is to become a #datadriven company and make decisions based on data. Like Uber does, for example. Let's assume you want to adopt the data-driven approach in your #credit department. In this case, it is crucial to trust the data on which these decisions are made.

In this post, I'd like to discuss quality typification for financial data sources based on which credit decisions are made for legal entities. These data sources are Balance Sheets, P&L, notes, transactions.

There are 3 types of data quality checks to verify this data:

1. Technical checks: for emptiness, range of values, the value in the row can only take a positive value, comparison of data that came in the current request and a month ago from the client, data versioning.

2. Logical checks: these are checks of control values: an asset is equal to a liability, cross-checks between the balance sheet and P&L.

3. Comparison of data with point values in other sources: with public reporting, reconciliation of data with external sources, such as D&B, with internal data of personal accounts of banks and business applications.

The result of the check is used when deciding how much you can trust this data and make decisions with credit risk based on this data.

This area is very important because raw data in accounting systems may contain incorrect data, an accountant can make mistakes, and transactions may not be fully carried out. Transparency of technical data linage with data quality is the basis for meeting all regulatory requirements of BSBC 329.