ANACREDIT: NEXT GENERATION CREDIT RISK BIG DATA

A NEW CREDIT RISK BIG REPORTING BIG DATA PARADIGM

Financial institutions are facing an increased level of regulatory examination in the repercussion of the Great Recession. Regulatory pains entail different and extended reports, templates, models and quantifications from financial institutions with a significant increases of the compliance costs.

Still, On 18 May 2016 the Governing Council of the European Central Bank adopted the regulation of the collection of granular credit and credit risk data (ECB/2016/13). The Credit Data is to be collected in a common register named as the Analytical Credit and Credit Risk Dataset (ANACREDIT). ANACREDIT is a main European System of Central Banks (ESCB) project and one of the principal projects expected by the statistics team of ECB. Such a joint granular storage is a stage in refining detailed, more accurate and timely statistical information on individual loans and credit risks in the euro area, harmonized across all the Member States. if decided to join the member States whose currency is not the euro to turn out to be a reporting Member State on a voluntary basis by incorporating the ANACREDIT regulation into their national law. As a result, a new paradigm – “regulatory credit risk reporting” – is emerging where an institution should provide its substance fundamental granular data to supervisors for their regulatory controlling, risk assessment, and benchmarking exercises.

In the data science terminology, Big Data enables organizations to store, manage, and handle vast amounts of disparate structured or unstructured data at the right speed and at the right time, ANACREDIT is an umbrella (like big data) to describe the capture and processing of larger sets of credit and credit-risk data through the usage of newly advanced analytics data processing.Even if this data isn’t of the same scale as, for example, a highest of clicks on a popular website, its volume is much larger than the regulatory reports delivered today.

ANACREDIT as a new Credit Risk Reporting Big data combined to advanced analytics helps supervisors and financial institutions process the large volumes of data produced by financial institutions for benchmarking and compliance purpose on granular credit & credit risk data levels.

 WHY ANACREDIT?

Formerly this year, the German banking industry expected that the ANACREDIT project would cost smaller banks millions of euros to comply with, and larger banks up to EUR 50 million* knowing that the data required by ANACREDIT will result in changes in reporting systems, credit systems, finance systems and processes and, in other cases, consequent data collection exercises to provide the wished huge data.. An example of this huge data is linked to €100 threshold for non-performing loans which it would effectively lead to an indirect lowering of the reporting threshold from €25,000 (The threshold of €100 for non-performing instruments has been aligned with the general threshold of €25,000), to be in a position to state non-performing loans, financial institutions would invariably need to maintain a complete dataset for every single loan granted to a reportable counterparty.

A number of extra reporting requirements introduced by national authorities have also an impact on required databases. As ANACREDIT overlaps with other regulatory reporting requirements (e.g. IFRS 9, BCBS 239, FinRep, CoRep), a holistic approach towards the credit data architecture will definitely save time and cost in the future. The monthly and quarterly reporting under the ANACREDIT regulation shall start in September 2018. Small banks, however, will be able to report on a quarterly basis for a transitory period of two years. National Central Banks (NCBs) are allowed to collect the information to be transmitted to the ECB, as a part of a broader national reporting framework and using their own data storage systems.

ANACREDIT templates: data terms and frequency.

For ensuring the appropriate identification of counterparties, NCBs shall transmit to the ECB a first set of the counterparty reference data six months prior to the first transmission (March 2018) and NCBs may require partial or complete reporting of counterparties reference data and credit data from 31 December 2017 onwards. However, the NCBs may demand a test delivery of master data (and possibly counterparty and credit data as well) two months earlier.

 The motivation behind ANACREDIT is mainly a better support for the tasks of the ECB, namely monetary policy analysis, risk management and financial stability surveillance. The ECB is aware of the cost of reporting agents and tried to balance the reporting burden with the benefits of a new dataset. However, credit institutions can benefit from ANACREDIT, too. The infrastructure for the new reporting duties can be used to fulfill other regulatory frameworks at the same time. Such synergies exist between ANACREDIT and the new accounting standard for financial instruments, IFRS 9. And vice versa, ANACREDIT requires accounting data with explicit reference to IFRS 9, but still the need to resolve the reporting frequency, as ANACREDIT required granular data closer to operational systems.

 What are the business impacts from ANACREDIT?

For Financial Institutions the data required by ANACREDIT will result in changes in reporting systems, credit databases and processes and, in some cases, subsequent data collection exercises to provide the requested data. Several additional reporting requirements introduced by national authorities have also an impact on required databases. There are two main impacts on:

A. Business:

• Consolidated Customer Vision: The credit process will need to be reliable and provide coherent data all over the lifecycle of customer exposures to simplify the required data attributes deprived of costly and laborious manual data reconciliation.
•  The need to link borrower information across multiple systems therefor, the traceability has to be automated.

B.Credit risk information previously used only for internal purposes will support also the ANACREDIT reporting such :

• Data Governance :From a risk data management perspective, the comprehensive metadata should only be built once and in a approach that allows financial institutions to capture all relevant metadata across business lines, in a consistent and well-defined data structure that is easy to extract, analyses and report, with the aim that to improve sharing, retrieving and understanding of data information assets.
• Data Quality represents the state of completeness, appropriateness and accuracy of data for generating ANACREDIT templates. Accuracy means that a high level of confidence can be placed on the data. Data is considered to be accurate if it is free from material mistakes, errors and omissions; the recording of information is adequate, performed in a timely manner and is kept consistent over time. Data is considered to be complete if it has sufficient granularity to allow the identification of trends and the full understanding of the behavior of the underlying risks or financials. All material information, shall be taken into account and reflected in the data set and finally Data is considered to be appropriate, if it is suitable for the ANACREDIT templates and relevant to the credit risk portfolio being analyzed (i.e. directly relates to the underlying risk drivers).
• Multi-business lines Data Governance should be defined including roles and mandates that govern decision making and ownership of ANACREDIT process. The objective of the data governance is to ensure that data is owned and stewarded accurately and consistently to meet ANACREDIT templates delivery.

 ANACREDIT Benefits?

From an economic standpoint, Monetary Policy requires a vast amount of data Market policy within decisions that affect economic activity and inflation through several channels, the ‘transmission mechanism’ of monetary policy; that’s why ANACREDIT data is critical to assess the extent to which b/s conditions of banks or debtor are influencing credit expansion.

For Financial Institutions, NCBs and Central Banks, ANACREDIT is Covering the whole collection of financial institutions as counterparties (since the threshold of € 25,000) this will help to:

• Leveraging on granular data characteristically produced by banks for their internal risk management processes
• Allowing identification and valuation of developments in credit demand and credit stream across all SMEs in the euro area in an appropriate manner.
• Improving monitoring of credit expansions at the borrower-lender level
• Supporting measure better the credit risk that financial associate with firms conferring to some specific balance sheet features.
• Providing better information about provision of credit  (on the readiness/availability of Financial institutions to provide credit) and can be matched with granulated ANACREDIT data.
• Assisting the valuation of the efficiency of various methods to improve for example SMEs admission to credit.

Still that, ANACREDIT is a highly complex project. It will, furthermore, take time in “my own” view for consistent reporting practices to establish themselves by given the need to clarify a number of open questions of interpretation.

The possibility consequently cannot be excluded that financial institutions may unintentionally break reporting obligations and turn out to be liable to sanctions despite their exhaustive preparation and best hard work. With this in mind, and particularly in view of the difficulty of the new reporting requirements, the ECB should refrain from imposing sanctions for a reasonable transitional period of five years from the first reporting date.

 Last and not least, the reporting data on a monthly basis would be virtually impossible, with a monthly frequency, for financial institutions to ensure the delivery of high-quality data, probably speed would come at the cost of quality and the financial. Still, it should be kept in mind that there is probably slight or no volatility in the data basis and the attributes to be reported in template 1 where as the colossal additional workload for both financial institutions and supervisors would be out of all proportion to the additional gain in insight. For these reasons, the best is to consider quarterly reporting enough from a statistical and prudential perspective.