Undertakings for collective investment in transferable securities (UCITS) are collective investment schemes established and authorized under a harmonized EU legal framework. These schemes allow fund managers to operate freely throughout the European Union through a single authorization from one member state.

The Commission de Surveillance du Secteur Financier (CSSF) requires UCITS to ensure their eligibility. This requires fund managers to check each fund’s prospectus to identify phrases that confirms its accordance with UCITS eligibility requirements. As fund managers have many prospectuses to review, and each averaging around 150 pages, this task is time-consuming and can be error-prone. Generally, fund managers are performing this task manually, generating high operational costs and deviating resources from more added-value activities. 

To tackle this challenge, Deloitte explored the field of artificial intelligence (AI), with a particular focus on natural language processing (NLP), an AI subfield combining linguistics and computer science that allows machines to understand, process and perform human-language tasks.

Manual approach

Fund managers review UCITS eligibility by checking if these two necessary but not sufficient conditions are covered in its prospectus:

1. Compliance with the Luxembourg law of 17 December 2010 implementing the EU Directive 2009/65/EC; and
2. That the fund shall not invest more than 10% of its assets in transferable securities or money market instruments.

Without a dedicated tool, this is mainly a manual task. It consists of reading through the prospectus page by page, documenting the location of sentences that justify one of the UCITS eligibility criteria in a review sheet, and finally checking if both eligibility criteria have been met.

Identifying these relevant sentences from a 150-page prospectus is tantamount to looking for a needle in a haystack. And, if the prospectus is only available in hard copy, keywords cannot be automatically searched. Furthermore, prospectuses from different sources have different layouts, increasing the difficulty of a human review and potentially leading to classification errors.

AI automation

Figure 1 shows how an AI automated solution can reduce fund managers’ current burden. It inputs the PDF prospectus, preprocesses and parses the text, and then separates and organizes the content into a standard format ready to be analyzed by the algorithm. Through NLP and rule enhancement techniques that recognize patterns, the algorithm can identify relevant UCITS compliance sentences. Based on the sentence extraction, the model can identify the prospectuses that comply with the stated criteria. The model’s classification proposal is evidenced through the algorithm returning relevant sentences, page numbers and paragraphs to provide the fund manager with the full context.

FIGURE 1: AI-based solution

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An example of the model output:

• Criteria 1: compliance with the Luxembourg law of 17 December 2010
  Sentence extracted: The investment fund is an investment company incorporated in the Grand Duchy of Luxembourg and qualifies as an Undertaking for Collective Investment in Transferable Securities (UCITS) complying with the provisions of Part I of the 2010 Law.
  Model output: Compliant
• Criteria 2: less than 10% investment in transferable securities or money market instrument
  Sentence extracted: The sub-fund may invest a maximum of 10% of its assets in MMFs.
  Model output: Compliant

The involvement of field specialists in the model’s training and output validation is the foundation of the product and optimized its accuracy. More specifically, the algorithm is trained on a dataset of prospectus labeled by fund managers. Fund managers remain the final decision-makers on a prospectus’ eligibility by assessing the batch of relevant sentences returned by the algorithm. Furthermore, feedback logged during the validation process is used to enhance its accuracy.

By virtue of the AI algorithm, the UCITS eligibility check can be performed in five minutes as the analyst just has to review and validate the outputs, which is statistically six times faster than the traditional manual approach.

Added value

Automating UCITS compliance tasks with AI techniques like NLP overcomes the limitations of traditional approaches and offers a multitude of benefits.

Not only does it significantly trim operational costs but it also optimizes resource allocation. As the manual processing of financial documents takes up professionals’ time, outsourcing this process to AI frees up talent to focus on the core business.

It can also help reduce operational risks and bias compared with manual processing. In particular, a dedicated platform allows for comprehensive documentation and better traceability regarding potential errors.

Last but not least, the solution provides sustainable data capacity. In stark contrast to conventional methodologies, AI works better with scale—the more data it is fed, the smarter and more agile it gets. This enables organizations to keep up with explosive data growth.