金程FRM：气候变化如何影响银行？

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来源于：GARP

自从气候变化压力测试话题引发关注以来，我就有点被卡特里娜飓风迷住了。2005年的那次灾害不仅造成了广泛的人类苦难和巨大的保险损失，而且还极大地改变了新奥尔良、路易斯安那州和墨西哥湾沿岸社区的经济增长前景。

据估计，灾难一发生，新奥尔良的人口就减少了一半以上；此外，时至今日，当地人口仍比卡特里娜飓风发生前少20%左右。

我们已经知道气候变化可能使极端天气事件的强度增大、频率增加，了解气候事件对金融利益的影响应该是建立数据驱动的气候风险压力测试平台的第一步。

虽然卡特里娜飓风对保险企业利益的影响是显而易见的——它导致的财产损失估计超过1000亿美元——但对于银行和信用合作社在内的的影响则有些难以辨别。幸运的是，学术界已经发表了几篇文章，深入探讨了卡特里娜飓风对家庭财政的影响。

比如，Tatyana Deryugina、Laura Kawang和Steven Levitt发表的一篇论文利用纳税申报信息探讨了飓风对家庭收入和就业的影响。研究人员将那些受飓风影响的人(包括许多离开城市的人)与另一组对照组的人进行了比较。对照组人群在2005年之前居住在偏北的、但规模大致相当的城市。

这项研究中最有趣的发现是卡特里娜飓风只对收入和就业产生了微弱的、暂时负面影响。更重要的是，研究人员发现，几年后，那些受卡特里娜飓风影响的人比未受其影响的对照组的收入要高得多。

这项研究还确定了导致这一结果的几个驱动因素，其中最有趣的是关于劳动力流动性的。通常情况下，由于搬迁的固定成本很高，人们会长期留在一个特定的地方。然而，当被迫搬家时——通常这些人手握一张保险支票——人们就可以选择他们新的生活地点。这些选择常常基于如何最大化潜在的赚钱可能性而作出。来自Deryugina等人的数据证实，总的来说，人们在灾难后的重新安置中获得了成功——这是异常黑暗的乌云背后的一线光明。

对家庭信贷的影响

An even more pertinent paper for our purposes was produced by Justin Gallagher and Daniel Hartley. They used data from Equifax credit files and information on the local severity of Katrina-related flooding to calculate the effect of the storm on household credit performance. Again, the data they used allowed them to follow individuals who moved as a direct result of the hurricane.

The biggest impact was to reduce total debt loads for the most flooded households. Rather than rebuild, people affected by Katrine-related flooding opted to use insurance payouts and government assistance to retire mortgage debt and move elsewhere.

While 90-plus day mortgage delinquencies rose for flooded residents in the months after Katrina, the effect was surprisingly muted. The researchers found a brief spike in the default rate in early 2006, but this quickly reverted to something resembling the normal level. They also found some evidence that longer-term default rates fell for the most flood-affected group, consistent with the income dynamics identified by Deryugina et al.

Two other findings are relevant for banks building climate risk stress test models. The first is that credit card balances rose somewhat in the months immediately following the disaster, but quickly reverted to their pre-storm levels. This is surprising because it would have been understandable for victims to use unsecured credit to smooth consumption in the wake of such a huge income shock.

The second finding is that mortgage originations fell sharply in the local area and, consistent with a large population decline, remained weak throughout the observed post-storm period.

If a bank were conducting a stress test on the basis of these findings, the biggest impact would be in the calculation of pre-provision net revenue (PPNR). If we consider a hypothetical bank whose territory was, and is, limited to the most flooded areas of New Orleans, we would find only a small spike in subsequent credit losses for the institution.

A reasonably well-capitalized bank should be able to cope with a shock of this magnitude. Its business, however, would have failed, due to a combination of the severe reduction in the scale of its mortgage book and the precipitous decline in new originations.

Real banks are much better diversified than this. Gallagher et al. considered the behavior of “local” banks, defined as those with more than 24% of mortgages held in the New Orleans CSA. These institutions saw originations eventually recover to pre-storm levels, while non-local lenders basically deserted the city. These non-local lenders are usually much bigger national or super-regional banks, able to weather such a shock and capable of following displaced clientele to their new location.

While local banks faced a revenue crunch – including several years of poor mortgage originations and elevated mortgage pre-payments – they ended the post-Katrina period roughly at par in terms of new loan generation. The desertion of non-local banks meant that, despite a shrinking market, local players had – and continue to have – more pricing power than they did previously. Top-line profits may be lower for these banks at the post-Katrina steady state, but overall profitability may be somewhat enhanced.

一些其他思考

Moody's Analytics research suggests that some countries, including the U.S., Canada and many nations in Europe, will gain a small macroeconomic boost as a result of climate change. In these locales, the main impact will be migration of capital and labor from places made less hospitable by the warming planet (like New Orleans) to places made more hospitable (like, perhaps, Boston or Denver).

Most financial climate risks are diversifiable, provided there are some people, places or industries that actually benefit from the new reality. It's a process that brings disruption for banks – particularly those rooted to a specific location – but also opportunities.

This is the inherent paradox of climate risk stress testing. For some banks - those capable of anticipating the winners and losers - it will be a boon rather than a burden.

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