IFRS 9 / CECL Impairment Benchmarking

Credit Consensus Data for Impairments Benchmarking
Under IFRS9 / CECL

Why Credit Benchmark?

Point-in-Time term structures provide comparability for the impairment process

In addition to “through the cycle” probabilities of default, Credit Benchmark also collects and aggregates Point-in-Time (PIT) PD curves from a growing number of global banks, allowing our clients to access a comprehensive set of consensus term structures at entity-, sector-, industry-, geographical level.

Leveraging the insights provided through the benchmarking outputs, clients are able to identify, justify and articulate the key drivers of variance in expected credit loss and provisions to both internal and external stakeholders.

Solutions

How we can help your business

BOOK A DEMO

Better understand key drivers of divergences of ECL to equip Investor Relations team to articulate Impairment comparisons.

Benchmark PIT PDs / Curves against peers to allow for identification of drivers of earnings volatility.

Track changes in Credit Consensus Ratings to bolster staging assessment process, compare internal staging assumptions against the consensus, and enhance view on unrated / LDP portfolios.

Optimize internal processes by identifying risk areas with largest relative / absolute PD movements, monitoring rating changes well before year-end, and improving connectivity and reconciliation between credit ratings, regulatory capital, and impairment.

Utilise benchmarking outputs to assess the impact of economic scenarios and weightings in impairment outcomes.

Case Study

The Client
The model validation team at a major UK-based Bank

The Challenge
The model validation team wanted to implement a robust model monitoring and validation framework for IFRS 9 utilising a representative independent dataset. They were also looking to help justify amendments to models and validation framework to auditors and regulators.

The Solution
Credit Benchmark’s Consensus Term Structures facilitated like-for-like benchmarking on an economically representative proportion of the bank’s portfolio. Independent and representative data allowed for tangible justification to internal and external stakeholders and formed a central part of their validation and monitoring framework.

In Numbers

75,000

Entities with Credit Consensus Ratings

800,000

Credit Risk Estimates Collected Each Month

50 Million

Credit Risk Estimates Collected Since Launch in 2015

1,200

Industry & Sector Indices

160

Countries Covered

Major Global Banks Contributing, Almost Half Are GSIBs

20,000

Credit Analysts Contributing Risk Views

90%

Of Universe Unrated by Traditional Rating Agencies

90%

Of Corporate Universe Are Private Companies

The Benefits of Consensus Credit Data

Rating the unrated

Unparalleled coverage of public and private issuers; filling the gaps left by traditional ratings agencies.

Independent

Free from “issuer-pays” conflict and any bank bias.

Real-world exposure

Driven by the credit views of >40 of the world’s largest regulated banks, almost half of which are GSIBs.

Identify that entity

Risk data is processed through a sophisticated purpose-built mapping engine.

Dynamic

The consensus is refreshed twice monthly to provide dynamic indicators of potential credit risk changes.

Alerting and monitoring

Assess risk over the lifetime of a transaction.

Secure reporting

Ease of internal integration within reporting.

Expanding footprint

A unique growing global dataset.

Related Material

Risk Solutions

Understand your risk

Request a coverage check of your portfolio & access unique insights and analysis from our exclusive, contributed credit risk dataset.

Credit Benchmark brings together internal credit risk views from over 40 leading global financial institutions. The contributions are anonymized, aggregated, and published in the form of consensus ratings and aggregate analytics to provide an independent, real-world perspective of credit risk. Risk and investment professionals at banks, insurance companies, asset managers and other financial firms use the data for insights into the unrated, monitoring and alerting within their portfolios, benchmarking, assessing and analyzing trends, and fulfilling regulatory requirements and capital.