BANKS – FAIR VALUE – HOLISTIC INDEX – MACHINE LEARNING – AI – LOANS – DIGITAL TRANSFORMATION – REAL-TIME VALUATION
Real Estate in Real Time
Far from addressing the banks’ many weaknesses, we have written, the real estate exposure has been possibly the most brutal force in the history of lending, determining most of the systemic risks and of the failures of financial institutions of the last few decades. Banks have played the real estate collateral card thinking they were smartly buying a “call” on the asset, we have commented, whilst, they were most likely selling a “put” to their debtor. And they have become, in doing so, almost like a hedge fund with a very long position (mostly “naked”) on the real estate cycle. It’s kind of easy to make some money when the value of houses keeps growing (albeit it is still possible and fairly easy to go bust as bad debtors are always looking for stupid bankers), but banks are mostly infallibly broken when the cycle turns. All this makes it very critical to get a better approach to “fair value” analysis and towards a mark to market valuation of real estate assets.
With the abundance of data and information potentially mastered by digitization approaches, real time based holistic indexes on real estate could be now developed, mixing structured data with further unstructured information taken from all kind of sources, including satellites and video cameras (measuring the exposure to the sun of any single apartment, or the trend in traffic and illumination during night time of a certain area), not to mention social feeds from the web (monitoring the “likes” and the suggestions and comments on specifies streets, shopping areas and restaurants or on the “coolness” of the neighbours.
The grabbing of instant information from online real estate agency web sites would also allow to monitor the demand for information and of potential investors’ visits, and the gap between asking price and the implied number and price level of bidding offers (also potentially done over the web). With the help of machine learning/AI techniques, it could all lead to the development of a holistic monitoring of the market value of flats and villas and commercial or industrial buildings, as shown in the following Figure, complementing the more rigorous DCF approaches which are good if you believe people are economically rational and consider a flat in Notting Hill and another one in Canary Wharf as fully fungible and as perfect substitutes (they are not).
Should such an index, marked to market, become largely available and certified from reputed counterparts, it would revolutionize the world of real estate and of banking as well (Real estate across-the cycle behaviours and trends can be analysed using unstructured information and machine learning). Pricing on loans would reflect these new values and their implied volatility. Lending portfolios (and real estate development portfolios) managed by banks, insurance companies, asset management companies and by other financial institutions could then consider the diversification coming from the different risk factors and performance drivers of any sub-class of real estate assets, based on the matrix of variances/covariances that could be developed.
Hedging by derivatives or reinsurance and financial guarantee could become widely available and cheap, and even collateral management could be informed by margin calls operated by some central “bricks and mortar” specialist clearing house. Even the tax collection agencies could do a better job in spotting the black economy so typical of the sector and the money laundering activities sometimes involving real estate trophy assets.
The digital transformation of the real estate sector would then be completed by the “smart home” applications, and by the many utilities that could help us in making our life at home easier and more convenient, or actually further foster the “shared economy”—e.g. an economy where “owning” a house does not make sense anymore, as mobility is the key principle, and the “rent generation” is the new king of the sector. This would in turn develop the sector into multiple hyper liquid renting markets, operated by “long only” professional investors and with buildings serviced by professional multinationals driven by scale and scope economies. Fungibility of homes, if not of a single, “yours truly one”, would therefore also increase.
In this extreme scenario of digitalization, a new set of indexes and a new market infrastructure helping to provide a real-time valuation of the real estate assets would then become even more important, introducing further opportunities that are not yet dreamed of: impacting heavily even on the most “brick and mortar” sector of all, and potentially helping banks in sorting out the negative “heaviness” they have added, via their exposure to the real estate sector, to the already unbearable lightness of their core business model.
Sources: Digital Transformation in Financial Services, Claudio Scardovi, AlixPartners London UK, 2017
Graphics & Photos: Made in PropTech Switzerland