AI. Helping you see beyond the Big Red Book
Aldous Huxley probably didn't have financial regulation in mind when he wrote his novel about a dystopian world order, but the slew of newly formed global rules, that today govern international finance, does have a touch of that Brave New World feeling.
Yes, a lot has been happening in the world of Finance lately.
The Bank for International Settlements (BIS) Basel III regulatory framework was finalised last December, with a staged implementation phase over the next 5 years; 10 if you include the Tier 1 capital ratio buffers.
Five years might sound a lot, but when you know that the best banks will want to adopt these new standards well ahead of their competition and the BIS's own deadlines, you know the race is well and truly on. Additionally this January, both the International Financial Reporting Standard 9 (IFRS9) and MiFID 2 went live too.
A cynic might argue that ultimately all of these new regulations have been brought in to ensure that the next financial crisis is not like the last one. There is more than a grain of truth in that. However, let's not forget that the 2007/2008 Global Financial Crisis's Pudding Lane, was the US sub-prime mortgage market.
Ten years on and now all of this may seem like distant thunder to participants in real estate, but actually a great part of what all these new financial fire break regulations do, is put an intense focus on Pudding Lane and particularly on property based finance and securitization.
Amongst the myriad effects designed to improve financial stability through Basel III, these new standards demand regular and better stress testing of the left hand side of the lenders’ balance sheet and specifically Loan To Value (LTV) bands and their associated Risk Weightings.
So for Assets, think real estate, commercial and residential property valuations and any lending based on these, mortgages, MBS and RMBS. These are in addition to the more obvious aspects of credit risk analysis of borrowers and credit default probabilities, along with forecasting and stress testing of future risks and then provisioning for them. All together, quite tricky stuff.
World Keeps Spinning
Meanwhile the real world has not quite stopped while these new regulatory frameworks were being figured out, let alone implemented. During this time it was not surprising that traditional mortgage lending remained and continues to remain subdued, whilst these participants have their financial probity medicine administered. Equally unsurprising that while this happened, a host of 'alternative finance' new entrants have entered into the property lending space. Now what is interesting, is that obviously these new lenders come at a cost and that actually any non-bank or non-regulated lender will likely have a much higher cost of capital, all of which will be passed on to the borrower. This is instructive, as it shows that the actual cost of a mortgage works out as the sum of the credit worthiness of the lender and the borrower plus the risk free rate. However what both traditional lenders and new participants all need, is a clear objective estimate of the collateral (underlying property), the fair value, which actually leads to the mortgage offer and thus the LTV.
Quickly you can see there is a problem, the Pudding lane problem. The GFC fire started with the tinder of poor real estate valuations, the oxygen of leverage through securitization and fanned with the accelerant of fraudulent lending criteria. We cant do anything about the last two, but we can get better valuations thanks to applying AI, Machine Learning and Big data.
Fortune favours the bravish
Over the next few weeks, the team here at Houseprice.AI will go over how several of these factors can be better measured and modelled using ML and Big Data with accurate, objective property valuations. Not exactly heroic of course, but bravish enough to manage this new regulatory maze. Our Property experts will go through how the checklist of the RICS Red Book can be better supported with objective datasets from a variety of drivers, leading to better property valuations. Our Finance and Asset Management experts will show how more accurate portfolio analytics, pricing and granularity directly affects the cost of funds and risk weighted returns for the lender. That then in turn leads directly to an end-users cost for funding property acquisitions, through a variety of distribution channels.
|Eldred Buck is CEO and Co-Founder of Houseprice.AI Ltd and a Non Executive Director at Sequant Capital. He has over 25 years experience in capital markets and banking, specialising in quantitative models and derivatives trading across all major asset classes. Previously he founded Eiger Trading Advisors, a leading fintech company.|
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