Getting ready to implement Basel IV: Now is the time for innovation

The Basel IV framework, which will come into force in 2023, poses major challenges for the European banking landscape. In particular, the new package of reforms increases capital requirements. As a result of the new requirements associated with Basel IV, there is a capital shortage of over 135 billion euros at European banks. Accordingly, the banks are concerned with one question: How can the increased capital requirements be met?

A decisive reform in connection with Basel IV is application of a more conservative calculation of risk-weighted assets (RWA) than was used under the Basel III regime. The Basel Committee on Banking Supervision (BCBS), which is responsible for the creation of Basel IV framework, proposed that the calculation of a bank’s RWAs using an internal ratings-based approach should not be less than 27.5 percent below the requirements as calculated using the standardized approach. This restriction is called an “output floor”. Additionally, the input parameters in the banks´ internal risk models cannot be smaller than certain minimum levels required by Basel IV. These minimum levels are called “input floors”. Both output and input floors aim to increase comparability and transparency of RWA calculations across the banking industry. At the same time, they make it more difficult for banks to save capital. Big financial institutions are affected by Basel IV to a larger extent than smaller banks, as they mostly use internal models.

How can banks meet new requirements?

Since a rapid capital increase is hardly possible due to current low profitability and high levels of competition, banks have only one option to meet new capital requirements: reduction of the risk-weighted assets.

In the context of Basel IV in particular, lowering RWAs may seem impossible, but Capgemini Invent has worked out two solutions. Both solutions involve the use of innovative technologies, which is a part of our DNA.

• The first option is to develop new internal risk models supported by artificial intelligence (AI) technologies. In such a case, RWAs are optimized by AI ​​so that they are at most 27.5% below the capital requirements calculated using the standard rating approach. This is achieved by continuously recalibrating the risk models while simultaneously maximizing their separation power.
• The second option is to issue blockchain tokens that divide and securitize high-risk assets. The use of tokens enables a more flexible and quicker sale of risky positions on blockchain technology than it is possible with a direct sale of assets. As a result, the proportion of high-risk assets in the balance sheet may decrease, leading to a reduction in RWAs.

As mentioned above, the new Basel IV framework poses a challenge for banks by forcing them to update the ways they calculate their capital requirements. Nevertheless, this challenge can be addressed by optimizing the processes used for the calculation of capital requirements, or even redesigning them. Innovative solutions such as the tokenization of high-risk assets or AI-driven credit risk modeling form a sustainable basis for dealing with the new regulatory requirements. The key to a successful solution is efficient planning and implementation. It therefore makes sense to deal with the effects of Basel IV early.

At Capgemini Invent we have many years of expertise in project planning and management and can assist in the development and implementation of risk models.

This article is co-authored by Oleksii Dakal.

To learn more about Basel IV, do reach out to Grigori Tymchenko. Looking forward to the conversation.

Grigori Tymchenko

Expert in Financial Risk Modeling, IFRS9, Validation and Management

I have 12 years experience in Financial Risk modelling and validation, compliance, data management as well as development of early warning systems based on open data.
I delivered numerous projects on Basel IRB, IFRS9, market, operational, business and model risk topics at financial institutions in and outside of the EU.
Recent work includes:
Basel IV readiness assessment and designing the transition roadmap for G-SIB in Europe to achieve regulatory compliance.
Development of early warning systems and KYC checks for credit risk and market compliance monitoring based on structured and unstructured public information: social media data, news, blogs etc. for internationally operating large banks in Germany to improve separation power of existing rating/scoring systems.
Risk & regulatory management content, credit risk model development and validation incl. backtesting and ongoing monitoring (PD/LGD/EaD/CCF retail/non-retail under ECB/EBA-GL, esp. DoD, MoC, TRIM), automation of reporting in R, SAS as well as closure of regulatory findings, action point control, model tiering and model risk management for large banks in Europe.
IFRS9 gap analysis incl. road map design, implementation planning and budgeting, followed by complete implementation projects esp. PD/LGD/EaD modelling for IFRS9 purpose in R, SQL as well as model validation in R, SAS, SQL, external and internal data management, software selection at large European banks.
Before joining Data, Risk and Regulatory of Capgemini Invent, I have been working for several years at KPMG and Deutsche Bank in risk analytics and regulatory area.
I am fluent in German, English, Russian and Ukrainian. I like travelling a lot, as well as going for biking and surfing.