Page 344 - 2019 6th AFIS & ASMMA

potential transactions, they talked about that they have a great idea that
the originator loans, and then sells to the capital market by issuing the
RMBS. It is very sensitive issue, because the mortgage sales without risk
retention in the origination model was obviously the key driver for the
global financial crisis.
The second topic I'd like to share about China is the data transparency.
Earlier, Matthias and Simon talked about the importance of data
transparency, although in different contexts. Matthias talked about it
in the affordable housing, while Simon talked about it in the housing
financing. I think the good thing about China is, for the mortgage
originator to issue RMBS, those mortgage originators need to file the
registration report to obtain an issuance quota from the regulators.
In those registration reports, they need to provide up to ten-years
history data. As a rating analyst, I remember when I worked on the first
Taiwanese RMBS transaction, later Hong Kong deals and earlier days the
Korean transactions, obviously we need to get the originators-specific
data one by one. It's hard to have a big picture on the overall industry;
the performance, the trend, not to mention the peer comparison. So, we
had the privilege to get the confidential and non-material information
from each originator. But again, it was quite different then. Now I work
in China, before we are engaged to work on any transaction, I have like
20 mortgage originators and all the top six mortgage originators in China
they follow the RMBS registration report and they provided more than
almost ten-years history data. So, before we talk with them, we rate the
RMBS transaction sponsored by the largest Chinese mortgage originator;
we already have a very deep understanding on them, their performance,
with the peer comparison.
» Moderator | Henny Sender
Jerry, I'm going to stop you there for one minute to talk about data.
Then I'm going to ask you a question from the floor. Both of you have
mentioned the importance of infrastructure and the importance of data.
How confident are you that there is good information available in the
markets that you have experiences of?
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» Panelist | Simon Walley
Very little confidence. I think one of the useful roles the institutions
like Olivier's can play, or whether it's KHFC here or Cagamas in
Malaysia, is to set standards. You want to standardize the mortgage
products, have the same documentation, the same underwriting rules,
which allows you to have collected data on a comparable basis and
build it up. I think the other thing that we often struggle with is the pure
mortgage data. You also need to understand the market you're in, so you
need data on house price and housing production. These are often what
the countries struggle with, but without the data, it is very difficult for
the ministries and the authorities to make good housing policy based Session II
on good judgments. We've seen in many countries, and Thailand can
particularly be a good example. There's some delegates here. In Thailand,
they set up what we call a housing observatory. When we don't have the
data, we're kind of making policy blindly. Let's see how we can collect it,
where it's going to be the municipalities collecting housing production
data. Let's see what's the best way we can do to build a house price index.
In Thailand, I think they put up a big institution, which enabled them to
make the right decisions.
» Panelist | Matthias C. Helble
I'm a bit more optimistic about the data, because now we have lots
of data on the internet. It's quite easy to download the information. For
example, at ADB last year, we downloaded 20,000 housing prices within
Manila. We also could locate the household exactly by the tree, because
it was also available online. So, using these online platforms, we can
actually gather a lot of information. Of course, we have to be careful
how to interpret it. This market might be catered to a certain group, but
I think, for example, this Google Maps, which gives us data on traffic
flows or on restaurants, also can give us a very good idea of the actual
income of neighborhoods, which can help to assess certain risks or
profiles of certain groups. So, there's already a lot of data that can actually
be gathered at a relatively low cost.
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