How to meet the loan monitoring requirements of the EBA guidelines
In May 2020, the European Banking Association (EBA) published new loan origination and monitoring guidelines. These guidelines specify the internal governance arrangements that banks operating within the region must put into place regarding the approval and monitoring of credit facilities throughout their lifecycle.
We explain below what these new guidelines mean, the reaction we’re hearing from our banking clients and contacts, and how we can help firms with a compliant, cost-efficient solution that improves data access and analytics for other use cases.
Understanding the new EBA guidelines
The EBA guidelines published last May aim to ensure that firms have robust practices, procedures and processes for credit risk decision-making, management and monitoring in operation to minimize non-performing loans. As well as meet their obligations relating to consumer protection and anti-money laundering. The guidelines break down into five chapters covering governance, loan origination, pricing, collateral valuation and loan monitoring. The guidelines form a demanding set of regulations that have wide-ranging implications for banks relating to data management, IT infrastructure, methodologies, policies and processes.
The guidelines demand near real-time data gathering from a bank’s flow book and ongoing reporting for the life of the loan at a level of granularity and accuracy previously unrequired. With minimal reliance on manual processes. While loan origination procedures sit at the core of the guidelines, the loan monitoring requirements will form the bulk of the effort required for many banks. They are particularly onerous because they need to be applied retrospectively and necessitate the gathering and analyzing of back book data.
The EBA acknowledges that banks need to balance immediate operational priorities (that have become more challenging due to COVID) with the effort required to implement the guidelines and strengthen lending in the future. As such, the EBA has set out a three-phase implementation of the guidelines, as follows:
- For new loans, the effective date is June 30, 2021
- For existing loans that have been renegotiated, the effective date is June 30, 2022
- For all existing loans and to address possible data gaps, adjust monitoring frameworks and infrastructure, the effective date is June 30, 2024.
The reaction from European banks
At Eigen, we are fortunate to work with several European banks and be in regular discussions with others in the region who want to understand how we can help them. Listening to our clients and contacts, we understand that a major area of concern for many firms is implementing a monitoring framework and infrastructure that automatically compiles granular credit risk data at high accuracy. The EBA guidelines stipulate that there should be minimal reliance on manual processes in gathering this data on an ongoing basis.
The contacts we’ve spoken to clearly recognize the need to automate the compilation of credit risk data and the benefits in doing so, however, many of them don’t currently have the systems, people, or workflows in place to support this goal. The organizational changes required to meet these elements of the guidelines come at a time when teams are already stretched implementing and reprioritizing change programs due to COVID. The extended deadline of June 30, 2024 for changes to monitoring frameworks and infrastructure is a welcome relief but still puts pressure on teams to a deliver against a new set of data requirements.
This isn’t just a problem for banks operating in Europe. Increasingly, regulators worldwide are bringing in reforms that require firms to provide more detailed information within a 24-48-hour window. Dodd-frank QFC recordkeeping and the FASB CECL standards in the US, for example, require firms to report on multiple data points within 48 hours. Near real-time reporting of this nature, where accuracy, specificity and completeness of data are mandated requires automation whether ‘automation’ is specified in the rules or not. Even the most robust and streamlined of manual processes can’t handle these requests within the given timeframes.
How Document AI can help
The Eigen Document AI platform has been purpose-built to help banks and financial services firms scale their regulatory compliance, reporting and credit risk management capabilities. The platform not only accurately extracts information from a wide range of documents (such as credit agreements, compliance certificates, pledge and security agreements and agent bank notices) it also analyzes, interprets and aggregates the data to provide the necessary answers. The platform offers clients a flexible and scalable solution with the ability to train machine learning (ML) models to perform ongoing data compilation tasks, for loan monitoring purposes, and handle one-off projects like LIBOR transition.
The platform is no-code and has been designed for non-technical users, enabling functional teams to develop, evaluate and maintain models without the need for IT support or ML experience. The platform guides the user through the model development process and gives them full visibility over the results, flagging any low-confidence responses so they can be remediated. By putting the power of machine learning in the hands of the document and data experts, the accuracy levels achievable come close to 100%. The diagram below shows a screenshot of the model evaluation tool where users can review their models' performance. The platform can be easily integrated via APIs with document repositories, portfolio management systems and data lakes to minimize manual processing and streamline other workflows.
Every bank is on its own digital transformation journey and has its own appetite and priorities when it comes to the adoption of AI and other technologies. Many are well-advanced and will have successfully built, bought or customized a solution that will enable them to effectively monitor their credit risks in-line with the EBA, or similar, guidelines. But many have not. For those firms, Document AI technology provides a relatively quick and easy way to get started with the flexibility to integrate seamlessly with other tools and scale to support other processes, workstreams and data needs.
Request a demo and see for yourself how Document AI can help you to better manage and monitor your loans or comply with changing regulations and reporting requirements.