by Jennifer McComas, Lorenzo Lucchi, Nitya Mohan, and Monika Aggarwal
In one of the biggest bank failures since the 2008 financial crisis, Silicon Valley Bank [SVB] was recently shut down by regulators, and its deposits seized by the FDIC. Recognized as the bank of choice for many start-ups and VC ventures, this has dealt a jarring blow to many small businesses who weren't sure how they would make payroll in the days to follow.
For those that remember the very fast, very scary, near collapse of the U.S. financial system in 2008, you might be wondering what many of us are wondering: What happens next?
Let’s distract ourselves with an examination of how we got here as we wait for those proverbial shoes to drop. To understand the situation we need to take a closer look at how commercial banks like SVB make money, and the series of triggers and events that led to the run:
- First, the largest source of revenue for commercial banks is interest income. This is earned from loans extended from capital holdings, and from deposits that comprise the capital from which said loans are extended. Typically the revenue generated from interest on loans is greater than that from the deposited assets.
- Due to the pressure of continued rising interest rates, a conservative turn on VC and startup activity that slowed deposit income and demand for loans, and increasing concern about the ability to meet the demands of longer term commitments, SVB announced that they were seeking to raise capital. Customers with deposits beyond the FDIC insured limit were spooked, a bank run a la the Bailey Building and Loan [from the film "It’s a Wonderful Life" ensued, and within 48 hours SVB found itself shutting its doors.
Could this have been avoided? Sure. There is much wailing and gnashing of teeth about the knee jerk reaction of the VCs and their short sighted posture on their respective positions; however, we could also look at the sluggish approach, if not ultimate failure, of risk management at SVB. This is where banks and regulators alike will be turning their attention in the near future.
To be ready for increased scrutiny, financial institutions will want to fine tune and automate their risk management processes to avoid delays and errors, particularly with regard to risk scoring and prioritization. IBM Process Mining enables the detection of bottlenecks and compliance issues within the existing operational business process, providing visibility to the complete end-to-end business process. It pinpoints how compliance issues affect the process outcomes and performance and eventually trigger actions or initiatives to avoid maverick behaviors.
The process is very straightforward; The IBM Process Mining software utilizes sophisticated Machine Learning techniques on event records to produce a practical model of business operations that offers valuable insights into concealed decisions, resource utilization, rework, and executive dashboards with reports that are exceptionally helpful and captivating. Its Simulation capabilities lets organizations analyze the financial impacts of process improvements and helps make informed business decisions.
Along with this increased regulatory pressure will come a focus on optimization of the audit process. Audits conducted manually can be challenging, time-consuming, ineffective, and may not be entirely impartial, which could potentially compromise the quality and standardization of conformance checks. IBM Process Mining's AI driven process discovery capabilities can unveil any non-compliant and inefficient process behaviors, thereby facilitating precise, unbiased, and speedy auditing. IBM Process Mining applies AI to implement a continuous monitoring and alerting system that can aid in the early detection of anomalies, leading to a decrease in non-compliant behaviors.
We are not making this up. IBM Process Mining was leveraged for a major bank in Europe who needed to perform a regularly scheduled audit for the compliance process of rebate eligibility on Green (Environment) incentives; For regulatory reasons, they had to prove they were complaint in their process to assess customer eligibility. This helped them ensure 90% process compliance and 75% FTE saving, as the manual audit was replaced with the AI derived operational business process model using IBM Process Mining.
IBM is offering a complimentary half-day Automation Innovation Workshop (AIW) to help you identify how AI-powered automation can solve some of your toughest operational challenges. Request an AIW where you can meet with IBM experts and discover new ways to improve your business operations using AI driven automation technology.
We are still in the early days of the impact of the SVB closure on global financial markets. While the practices and methodologies we describe here are not new, we believe we may have a renewed interest and incentive to strive for further automation and efficiency in risk and audit practices. Let’s refocus, and get back to work.#processmodeling#processoptimization#processframework#audit