Cross-border debt is as old as currency itself. Sovereigns would borrow from their neighbors to finance territorial expansion, and merchants would borrow in a foreign country to finance their trading ventures. This fundamental business model has not changed over the millennia, where lenders and borrowers with differing cultures, languages, business practices, and legal systems engage each other in an often long-term relationship.
The biggest problem with cross-border lending has been, and remains, managing the risk of default by the borrower. When a lender decides to lend money to a borrower in another country, there are legal, business, cultural, political, and social particularities, any combination of which may lead to default. What can further exacerbate the problem is that in many situations, the lender may be unaware of the possibility of default until it is too late.
The often preferred solution in cross-border lending, where there is a likelihood of non-performance by the borrower, is for the lenders to negotiate an out-of-court restructuring of the debt -- called a "workout." This debt workout can be accomplished only if the interests of the lenders are aligned with each other and with the borrower. This process is invariably time consuming, involving many lawyers, bankers, and turn-around experts to help the borrower, not only to restructure the debt, but to maintain its business operations as a going concern in order to be able to pay back the new and improved loan.
This author has often wondered if some of these problems can be prevented or mitigated with the use of technology. Today, there are many tools that employ behavioral analytics to calculate how individuals behave in their use of technology, credit, or investment by way of example. This field is sufficiently sophisticated; many software companies can actually predict the future behavior of their audience, and lead them toward a desired outcome. The question is whether similar software can help banks (as lenders) better predict, price, and promote their loans so as to reduce the chances of default. Given advances in today’s software industry and the ability to analyze large amounts of information -- fashionably coined as "big data" -- banks simply need to develop a coherent process to gather such data on a regular basis.
In order to be able to utilize and integrate technology to better enable cross-border debt transactions, and reduce the incidents of restructuring and default, bankers and their technologists need to develop a common informational and analytical blueprint for these transactions. When a lender decides to enter a foreign market, the threshold issue becomes the differences between the legal structure of the home jurisdiction of the lender and that of the jurisdiction where the loan is made -- a legal risk analysis. Since many of these loans are secured by the assets of the borrower, the process by which that loan can be secured, and if need be foreclosed, becomes of paramount importance to a lender. Thus the legal landscape of the borrower’s country of residence needs to be analyzed in detail. In the past, even though there has been much information available about many countries, it has been cloaked in mystery due to cultural differences, language barriers, and other factors. Therefore, whether the country has an independent judiciary or a history of dispute resolution rooted in contract, employment, or tort law will be important to a lender.
The next issue is the creditworthiness of the business and its owners -- a credit risk analysis. In many cases, the borrowing entity is a private company, perhaps owned by an individual, family, or small group of shareholders who also manage and operate the day-to-day business. The mere fact that an international lender is considering purchasing debt from this company means that the business is large enough in both revenue and profit to merit such a transaction. However, if this is the first time the business or its owners have sought to borrow outside their home country, then their credit risk may not be known or easily gauged. Almost all such businesses will have a past credit performance that can be used as a model to predict future performance. The only caveat will be to incorporate the relationship between the local lender and the borrower and potentially discount the borrower’s performance if such a relationship is based on personal ties.
Another issue is socio-economic and political risk analysis. Many emerging markets have long histories of socio-political or socio-economic risk that tend to deter lenders from entering the country. The history, stability, and resilience of the current political system and economy are important dynamics to consider. These risks are primarily data driven, even though it may seem as if there is no way to analyze such risks. These factors, and perhaps others, can form the basis of a risk analysis tool, which will help banks and lenders analyze and price a loan in a far more robust, rapid, and objective manner. Technology that incorporates risk analytics, with country- and borrower-specific data, will eventually be able to minimize the risk of default to a nominally acceptable level. While risk reduction and mitigation will not happen overnight, this continuous data gathering and analysis will help the downward trend.
Many will decry the impossibility of such an undertaking. However, much the same way that the advent of electronic communication globalized banking, the advent of big data will eventually globalize risk analysis of cross-border lending. The benefits of such an outcome will far outweigh the costs of the journey. The ability to predict risk with a reasonable degree of certainty increases the potential for more lenders and borrowers participating in a far larger and more stable market. This market expansion, coupled with a reduced risk of restructuring, will result in more rapid economic growth in emerging markets, and higher overall profits for lenders that choose to cross a border to find new customers.
Behzad Gohari is a Managing Director at The Althing Group, an advisory firm helping clients navigate the capital markets. Over two decades, and through a dozen startups, he has acted as founder, investor, and strategic advisor, as well as utilizing his ... View Full Bio