Financial engineering to tackle poverty?

The development community have tried out several strategies and approaches to address persistent and critical development challenges. But most of them have not yielded satisfactory enough results. The natural inclination is therefore to try out something different. Do something innovative.

Nothing wrong in thinking this way. 

The only issue, most often, is that such thinking betrays a lack of perspective about the problem. How difficult is the challenge that we are trying to address? What is the context in which these problems exist and their potential solutions are to be grounded? What is the solution choice set available and its assessment? What has been the history of attempts to address the problem? And so on. 

When this perspective is deficient, these innovations become compelling magic-pill solutions. They are easy to explain and comprehend and resonates with our strongly held priors of how technocratic innovations can address persistent development challenges. Most importantly, they leave us comforted that the problem can be solved within a finite time and with the available public resources. In some ways, we are searching for the proverbial free lunches or the low hanging fruits. 

The two main sources for such innovation are technology and financial engineering. This post focuses on the latter. 

Development cosmopolitans argue that we need to deploy finance in service of development goals. The assumption is that finance has a disciplining and risk mitigation role which can be useful, for example, to trigger payouts on insurance against pandemics, natural and man-made disasters etc.

It is part of the dominant narrative that the financial sector has done innovative things with structured instruments. Never mind the fact that the vast majority of them have been value extractors and have engendered serious incentive distortions within the financial markets. Never mind all the increasingly recurrent bouts of financial markets induced economic crises and pervasive distortions arising from financialisation. But the narrative endures. Its hegemony has not spared development opinion makers. 

Poor people get ruined by episodes of catastrophic health conditions. So let’s give them micro-health insurance. Poor people grapple with uncertain weather and pest attacks that imperil their crops. So let’s help them mitigate the risks with index insurance. Poor people struggle to save enough for old age. So let them subscribe to micro-pensions. 

Such financial instruments are not confined to helping individuals. Development experts feel that countries and markets too could do with innovative finance. Not only are the underlying theoretical frameworks behind these ideas flaky - see this and this - but also there is little evidence about its efficacy in overcoming persistent development challenges and improving the lives of the world's poor. 

Not satisfied with inflicting themselves directly on the poor people, cosmopolitans pursue grander macro-economic ambitions. Countries face recurrent natural disasters and struggle to cope with the resultant damage. So help them with weather insurance. Aid comes in very late, is insufficient, and does not allow countries to plan effectively for post-disaster relief and rehabilitation. So some cosmopolitans have even suggested getting countries to subscribe to “pooled funding attached to contracts that pay out when disasters hit”, and if pooled finance is not available “transfer risk to the insurance sector by using concessional insurance to create certainty”. They have proposed "combining novel insurance contracts that provide fast payouts based on ‘parametric’ triggers with clear incentives to manage risks and invest in reducing losses". They claim that "an insurance paradigm for disaster aid will save many more lives for much less money". 

Millions of poor people struggle from certain infectious diseases which do not have effective enough vaccines at an affordable price. So guarantee them a commercially viable market so that pharmaceutical companies can be encouraged to invest in the development of such vaccines. Poor people and their national governments cannot afford expensive drugs for diseases like AIDS, Hepatitis, and Cervical Cancer. So provide them volume guarantees so that pharmaceutical companies can leverage economies of scale to lower prices enough to make it affordable. 

Governments do a bad job of delivering desired development outcomes. So let’s use the disciplining force of finance to help realise desired outcomes, or do outcomes-based financing. Learning outcomes are deficient in public schools or recidivism among released prisoners is very high. So let’s structure a complicated instrument called Development Impact Bond (DIB), with a transaction intermediary, implementation agency, independent outcomes evaluation agency, legal advisor, investors, and outcomes payers. 

Never mind there is scant or no evidence whatsoever of anything like these having worked at anything remotely close to scale. Never mind that the weak state capacity and limited markets in these contexts are in no position to take on such financial engineering. Never mind that these instruments open up opportunities for corruption and cronyism that often end up sinking countries into macroeconomic mess. Never mind that neither the corporate track record of financial institutions and big-pharma or big-tech nor their corporate governance standards and development commitment signals nor anything about their industry/corporate incentives suggests that these wonderful things are possible. But the logical attraction of these innovations, like those of the alphabet soup of financial market instruments, is irresistible. 

How do these innovations fare when subjected to rigorous scrutiny? 

In 2017 the Bank sold Pandemic Bonds to private investors who would have to payout upto $150 m if any of six deadly pandemics hit. It was to get triggered and cause payouts if certain pre-defined pandemics break-out. The investors who would have kept getting payouts as long as the pandemics don't happen. 

This is what happened with the Pandemic Bonds,

Last year Ebola struck the Democratic Republic of Congo. It has already killed nearly 2,000 people. But the scheme has not paid out. The 386-page bond prospectus contains a clause making payout conditional on the disease spreading to a second country, with at least 20 people dying there. Ebola has indeed spread, to neighbouring Uganda. But it has killed just three people there, with no new cases since June. Investors, including pension funds and asset managers, had bought $320m of the bonds in a deal that was heavily oversubscribed. The notes covering Ebola give them an annual coupon of 11.5 percentage points above LIBOR, a benchmark interest rate. The World Bank, with contributions from Japan and Germany, has already spent $87m on coupon payments, swap premiums and fees. Unless the outbreak worsens, investors will get their money back when the bonds mature next year... In all insurance contracts the cost of cover exceeds the expected payout (otherwise insurers would go bust). For pandemic bonds and related swaps this risk premium is about $17m a year. That money would be better spent on public-health systems and surveillance to try to catch outbreaks earlier.

Take crop insurance. Consider the challenges faced by a weather index insurance agency. It has to cover for an episode which has a high frequency but is completely uncertain, ensure the data is credible and minimises basis risks (affected farmer not eligible for claim because the index trigger was not hit), and pay out an amount which is commensurate to the damage suffered. It also has to keep the premiums affordable for the poor farmers, ensure that pay outs are done within a reasonable time, and genuine victims are not excluded. And it has to do all this with poor quality of index data and very patchy actuarial data, not to mention very unreliable crop damage models built on the index data. 

A viable insurance model assumes reasonable premiums, diversified risk pool, and low frequency of insured episode incidence. But in case of crop insurance for the poor, the actuarial model has to support ultra-low premiums even with the constraints of high (and increasing) frequency of index triggers being hit, highly correlated insured pool (weather is the same over reasonably large areas or regions), and significant enough reimbursements required to make this meaningful enough for the farmers.

An insurance product benefits from risk pooling on time (long-term premium payments), space (different uncorrelated geographies or types of people), and portfolio (different sets of policies) to keep claims ratio below 1. The multitude of small micro-insurers trawling the low income countries enjoy none of the basic requirements. In the context of micro-insurance based financial products, pls read this, this, and this. 

If we try doing the math, we will soon realise in no time that self-financed micro-insurance for the poor is an impossible proposition. In fact, it is no surprise that even the most efficient and largest crop-insurance schemes in the developing world, including China, enjoy over 80% premium subsidy support. India’s new massive nation-wide crop insurance program, Pradhan Mantri Fasal Bima Yojana (PMFBY), has premium subsidy of a whopping 98%! As the slide 6 here shows, subsidies, even in the US with crop-insurance are substantial. Even by squeezing out all the efficiency gains from financial engineering and technology, the commercial viability frontier will still remain very distant. In any case, whatever the insurer will pay out has to come from what is remaining after covering their costs – a claim ratio above 100% is not sustainable.

In simple terms, index insurance tries to do both financial engineering and weather modelling to address a complex development challenge. This is a double challenge. One, the actuarial models have to support affordable premiums. Two, the index data model that underpins the premium calculation has to be robust enough to minimise basis risks and also ensure that the development objectives are met. The first suffers historical data deficiencies and the second is an emerging area of research fraught with deep uncertainties. 

In contrast, a direct payment to identified victims does not involve any of the risk mitigation and transaction costs associated with managing an insurance. However, it does involve the challenge of assessing damages and their validation, whereas an index insurance only requires more easily verifiable (though less directly linked to the desired outcome) index triggers. But it eliminates the significant basis risk faced by farmers and ensures that the desired development objectives are realised. Besides, it also captures the true cost of crop damage mitigation in a clean, direct, and efficient manner. 

In light of the above, it stands to reason that the most efficient crop risk mitigation strategy would be direct income payments and not heavily subsidised insurance.

If we are engaging on a truly evidence-based policy making mode, the focus of innovation should be on helping governments make accurate assessments of crop damages in quick time. The one area where significant efficiency gains can be realised is from optimising the process of data collection and its validation. And this could be outsourced to a competent agency. But is anyone even talking about this?

Much the same analysis and conclusion applies to the other aforementioned examples of financial engineering-based innovations. All of them gloss over fundamental constraints.

Micro-insurance and pensions assume that poor people can save enough to pay for insurance, a deeply questionable assumption even in developed economies. It is a massive leap of faith to assume that debilitating state capacity weaknesses can be overcome by the disciplining force of finance (through outcomes-based financing) to realise complex development outcomes like learning outcomes. Financial models, however compelling, can do little to overcome powerful political economy forces that motivate aid spending. In pharmaceuticals industry, more so than most other industries, the market failure is less about incentive compatibility problems that can be fixed with financial incentives as about fixing the prevailing intellectual property rights regime and the flawed shareholder value maximising approach to capitalism. It is about increasing and targeting public investments into research and development about diseases that affect those less than well-off. 

In all these cases, as we peel enough layers into the problem it becomes evident that these so-called innovations are mere band-aids on gangrene. At best they are temporary palliatives. At worst, they represent an inadequate understanding about complex development challenges. In any case, they deflect the attention of governments, entrepreneurs, donors, and opinion makers away from the important task of engaging more deeply with the problem and figuring out more meaningful and serious solutions to those problems. 

None of this is to deny the value of these innovations, even with all their shortcomings. For sure, they have relevance in certain contexts, at certain times, and for certain problems. But as general solutions to addressing the fundamental underlying problems, their relevance is marginal. But by projecting them as a panacea, as mentioned earlier, proponents risk detracting from more meaningful engagement with the problems. Kinky development, as Lant Pritchett calls it. 

One of the basic principles of Econ 101 is that there are no free lunches. This is one of the few which have survived the test of time. It is indeed true. Always!