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Commercial Real Estate

Asset Managers have long been active within the Real Estate and Infrastructure sectors. With large Assets Under Management and long-term investments, the sector offers the relatively safe value retention of bricks and mortar assets, combined with steady returns generated from rent, leases or the management income of said properties. In addition, and in search of new avenues,

Asset Managers now venture deeper into traditional banking activities, participating in Real Estate and Infrastructure loan syndicates. The participation in syndicated loans, however, increases risk exposure due to the inclusion of borrowers, and in turn 2nd-degree exposures to the borrower’s tenants. The nature of how the relationships are set up limits the Asset Manager’s access to the critical data they need for risk monitoring purposes. Any form of investment or financial exposure requires oversight. The question though remains: how does one keep track of this risk, legally and operationally, when the required information is not easily available?

Challenges

– Limited access to operational and financial data required for risk monitoring
– Illiquid real estate assets have (indirect) exposures to many parties
– Retail operators generate large amounts of irrelevant news
– Fragmented markets with local sources reporting on local players
– Generic entity names produce false positives affecting the accuracy of the data

Solution
Owlin’s clients quickly identified Natural Language Processing and AI as the best tools to provide qualitative insights into their exposures, analysing local news on a global scale to pinpoint material events that affect their assets and counterparties. Due to the geographic diversification, with exposures to international brands and privately held local operators, no single source or data provider offers complete coverage.

To ensure that sanctions on a Chinese brand or lay-offs in a retail chain in France were on their radar, they required a tool that could analyse millions of sources of unstructured data in real-time. More important evenly, was the need to call upon the local newspaper reporting on an event first or natively analyse the national papers reporting in Mandarin, and thus ensuring the necessary coverage to maintain up-to-date risk profiles.

Through the use of the latest NLP technologies, our clients are able to analyse the vast amounts of unstructured data that is generated from monitor 100’s of assets. Owlin’s technology enabled them to pick up on the jargon, nuances, synonyms or acronyms within the content in ways that were previously unimaginable, allowing them to identify material events, proactively stay atop of developments and take timely action when the slightest whiff of problems, changes or updates are reported.

Result
In these unprecedented times, any investment manager will have aged many years in just a few months. Our clients, with great exposures to the retail and consumer sectors, encountered the challenge of managing and updating the risk profiles and forecasts for their portfolios in times when changes would take place on a daily basis. Not only did Owlin enable them to identify which of their 500 exposures required immediate attention or gain insights into the latest status of a leaseholder or borrower, it also enabled them to proactively put plans in place and temporarily restructure payments to mitigate the potential of all-out defaults.

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