“History doesn’t repeat itself,” wrote Mark Twain, “but it rhymes.” With the collapse of Silicon Valley Bank last week, the persisting market turmoil and volatility, and the regulatory scramble to contain the market fallout – the echoes of a few of 2008’s stanzas were audible over the nervous chatter of the tech company founders who found themselves in the surreal position of queuing outside SVB’s branches to withdraw their company’s deposits.
We’re seeing, again, the rapid implementation of emergency measures and the inevitable prospect of fresh regulation for the banking sector. The market is weighing up at least the possibility of a fresh round of measures aimed at improving transparency around liquidity, a review of the collateralization of obligations and potentially, even, a need to respond to higher levels of risk around counterparty default.
There’s a general sense in the air of needing to be ready. The question is, “ready for what?” For those responsible for overseeing and mitigating potential emerging risk, the core problem is being able to lay their hands on the right levers at the right time.
It’s a trite statement of the obvious, but if you want to know how risk is allocated between you and your counterparties, you need a clear view of what’s in the myriad of contractual documentation that captures both the commercial and legal risk you share. The challenge is that the process of risk allocation takes place at a client or even transactional level, but the assessment of risk and its mitigation happens at a broader, portfolio level.
For many institutions, there’s a reasonable degree of visibility and understanding of the risk nexus of a particular product line, or specific client engagement. What’s much less visible is the portfolio risk across product silos, or, indeed, across a suite of engagements for a particular client. But it’s at this slightly higher level of abstraction that the core insights needed to plot a strategic course are to be found.
So, how might institutions capture that level of insight, and do so in a way that avoids an emergency – and costly – review of documentation in a pinch? How can you, as someone needing to get – and stay- on top of risk, be confident that you will have the right information at hand irrespective of how the present turmoil shakes out?
Factor has extensive experience in complex contract review and negotiation in the financial services sector. One of the key lessons that we’ve learned is the importance of developing a contractual “data model” to power the review process.
In practice, a “data model” is simply an abstract of the core questions you’d want to know the answers to in a top-down review of your contract portfolio. For example, what are the cross-default and cross-acceleration triggers and rights and what are the default cure periods? What, if any, rating downgrade clauses might trigger, and when?
The model can contain specific queries, like the ones above, or queries answered by a review across a number of clauses – for example, profiling the eligible collateral within a product or client portfolio.
Every organization needs a bespoke data model. Creating one from scratch can feel daunting, both in terms of the amount of internal time and bandwidth required across the business to achieve a successful outcome. And, of course, time and capacity are in shorter supply in times of market stress. But, by partnering with a third-party provider that has both experience in building data models for contract review and expertise in the underlying legal documentation, you can achieve success in a short time frame and without placing strain on internal resources.
The best data model in the world does not yield insight until deployed against a body of contracts. And, just like the creation of a contractual data model, a contract review at scale can feel like a significant undertaking.
Indeed, one of the biggest barriers is the amount of internal bandwidth needed to review a large body of contracts and align that review to the defined data model. Technology solutions can potentially help in this process, but few, if any, are lightweight to adopt, and there remains the need in all cases for evaluative assessment of the relevant terms to ensure credible insight results.
The ideal solution is a lawyer-led, technology-enabled managed service. This type of contract review harnesses the power of cutting-edge machine learning technology with human expertise to provide the highest quality review at scale. The combination of human expertise and technology yields efficiency gains, by using machine learning systems to extract contractual data to a preconfigured data model and then human review to analyze the extracted terms to ensure you get meaningful insights.
The core benefit of a contractual risk review is that it transforms your relationship with your contracts.
At some point, whether triggered by an external event like the collapse of SVB or internal drivers, the need to undertake some form of wide-ranging contract review is a strong likelihood. Today, many institutions review contracts at an individual transaction level, to assess each against specific risk factors. This kind of approach is the most resource intensive and time-consuming and yields few reusable insights. By contrast, undertaking a broader “top down” risk review enables you to analyze and interrogate the entire of body of contracts, and to identify potential risks and options for mitigation at a portfolio level.
A broader risk review has key benefits in a scenario demanding rapid response, like counterparty distress or one with fixed deadlines for compliance, like regulatory reform. You can quickly find compliance or risk in key contractual terms and the contractual levers available to mitigate. And you can then conduct that mitigation efficiently and effectively, within the necessary time scales.
But a risk review is more than a “point in time” exercise. Once you align contracts against the data model, it becomes easier to ensure future consistency of approach in new engagements, and to ensure that the core contractual terms match the evolving overall risk profile of the business.
The collapse of SVB and the subsequent increased levels of stress across the financial markets highlights the possibility of disruptive surprises happening at any time.
Getting on top of the core risk information that lies within their documentation is the kind of task that many in-house legal teams in financial service firms appreciate would be good to undertake, but it often feels too complex and resource-intensive to action in practice.
If undertaken in partnership with an experienced strategic partner, this kind of review is achievable without imposing a significant burden on an organization’s capacity. And creating the ability to extract and review the key risks as contained in critical contract terms, quickly and efficiently, will save at a minimum significant time and cost when responding to emergent and unpredictable risks.