The importance of collecting historical recovery data for NPL transactions

Research

 

The year 2020 will see important changes in the use and disclosure of detailed recovery cash flow data for non-performing loans (NPL). On 20 December 2019, the European Securities and Markets Authority (ESMA) published revised technical disclosure standards for the reporting of securitisation transactions in Europe. For the securitisation of NPL, ESMA requires loan by loan reports on the underlying exposures according to the relevant template (for example, the template for residential mortgages or corporate loans) plus add-on data fields for non-performing exposures including details of historical repayments and unpaid balances. Banks or entities who have issued or sponsored NPL ABS in 2019 or are planning to do so going forward must comply with securitisation regulation and the technical reporting standards of ESMA which are expected to come into force by March 2020. Meeting the reporting requirements and detailed loan-level disclosures with historical collection information will be challenging.

You can access the full technical paper by clicking here: NPL Markets – Collecting Historical Recovery Data for Transactions of Non-Performing Loans

In this article, we provide some guidance on how this NPL ABS reporting challenge can be met and what other collections of historical recovery data are currently available in Europe. The add-on data fields from ESMA for NPL are a subset of the data template published by the European Banking Authority (EBA) to facilitate transaction of NPL. The EBA NPL template was published to create a common data standard for the screening, due diligence and valuation of NPL transactions with the aim to make the secondary market for European NPL more efficient.

We explain the ongoing work on the provision and collection of standardized data for NPL and compare five loan-level data templates in Europe:

  1. The ABS data templates from the ECB loan-level initiative,
  2. The recently updated ABS reporting standards from ESMA as part of the securitisation regulation,
  3. The EBA NPL template for the sale of non-performing loans,
  4. The loan loss database developed by the bank association Global Credit Date (GCD), and
  5. The AnaCredit data template of the European Central Bank.

We compare a specific part of the EBA NPL data template, the table concerning historical collections, with other available data sets collecting individual cash flows from the workout of defaulted loans. We highlight the importance of such cash flow data for NPL ABS investor reporting in addition to bank model development and NPL valuation. Finally, we propose a statistical method to capture the information from collection data for loss modelling and NPL valuation. The recovery curves derived from collection data are used in the valuation analytics of the NPL Markets platform, which values loans based on standardized input data sets following the EBA NPL template.

The author and the NPL Markets team have worked extensively with loan-level recovery cash flow data sets. We have used ABS loan-level data and GCD data for model building of bank credit risk parameters like the cure rate, loss given default or time to recovery. Other recovery models our team developed relate to the calculation of IFRS 9 loan loss provisions and models used for supervisory stress testing.

Our team went through a detailed field-by-field mapping exercise between ESMA ABS and the EBA NPL fields. NPL Markets offers an online mapping tool to automate mappings between non-standard data and any of the published data templates. The EBA NPL template is used with minor modifications in the database behind the marketplace platform of NPL Markets.

You can access the full technical paper by clicking here:

NPL Markets – Collecting Historical Recovery Data for Transactions of Non-Performing Loans