A recently published article on Global Trade Review (and appearing on other sites) reveals intentions by a major software vendor in the syndicated loan space to bring crowd-funding to the commercial lending market, and subsequently to syndicated loans.
I know I’m not alone in immediately imagining how this could impact the very model of syndicating a credit: the legwork and active management involved in negotiations between parties replaced by matching algorithms that don’t require political massaging, nor need to account for human emotion. An efficient syndication process, made objective and quantifiable…
As mentioned in the article, focus must be paid to data standardization across the industry. If left unresolved, the long term viability of crowd-funding to grow and evolve in the syndicated loan market could be stunted. Luckily, developing the framework around these efforts are, and have been for some time, underway. This is represented by notable initiatives such as Loan FpML.
But, another critical question must also be asked. As exciting (or terrifying) as imagining the impact of such innovations may be, know-your-customer/anti-money laundering requirements cannot be abstracted away from the conversation at this stage. How will counterparties in the market ensure they ‘know’ who they’re dealing with in advance of robots’ forcing them to lock arms in legally-binding contracts? I think the short answer is that counterparties won’t consider taking advantage of this opportunity until this question is answered. With the growth in interest by companies and regulators in distributed ledger technology solving KYC/AML issues, perhaps utilization of crowd-funding for an industry as complex as syndicated loans is not as ‘futuristic’ a proposition as one might have thought as little as 18 months ago.
One thing is for certain, if they haven’t yet, commercial lending and syndicated loan market participants should assume eventual disruption across their business model (and not just in the back office) and start now to plan accordingly.