On March 10, 2023, Silicon Valley Bank (SVB) failed after a bank run, marking the second-largest bank failure in US history and the largest since the 2008 financial crisis. It was also one of three US banks to collapse in March. At the end of 2022, SVB had USD 209 Billion in assets and USD 175 Billion in deposits, according to the FDIC. While it was not insolvent, several risks left the bank exposed.

One of the primary reasons that led to SVB’s collapse was a high concentration of investments in the technology and startup sectors, which faced financial difficulties recently. Many of these companies began withdrawing funds from their SVB accounts. Moreover, SVB had invested heavily in mortgage-backed securities and longer term high-yield bonds that are sensitive to interest rates. As the Fed raised interest rates, these assets lost value.

Matters came to a head when SVB, risking its reputation, publicly shared its plans to raise capital and cover its shortfall to avoid the threat of having its credit rating downgraded. The announcement spooked its clients, accelerating a massive withdrawal of deposits and creating the panic that upended its capital-raising efforts. Consequently, SVB’s stock price declined and a collapse followed.

The Need for Proactive Analysis – Regardless of Current Regulation

In 2018, a rollback of regulations, established a decade earlier, eased the compliance burden on many regional banks, particularly those with USD 50-200 Billion in assets. SVB fell into this category. They were exempt from various reporting requirements, such as Liquidity Coverage Ratios (LCR) and Net Stable Funding Ratios (NSFR). The bank was compliant with regulations and transparent about its balance sheet positions.

Despite this clean bill of health, the bank collapsed. This highlights a key fact that stringent compliance and transparency are not enough to future-proof an enterprise. Banks must develop comprehensive risk management models to assess and prepare against a variety of disruptive scenarios.

Call to Action

Banks and risk executives must assess the following priority areas with a systematic data and analytics-driven approach:

  • Regulatory Readiness: Staying above board in an evolving and interconnected business landscape is challenging. The accelerated pace of digitization, ESG requirements, data silos and cybersecurity threats make the terrain even more difficult to navigate. Harnessing data can provide banks with the necessary information and visibility to develop a comprehensive and up-to-date governance, risk and compliance strategy.
  • Contingency Planning: This is a must to ensure there are other sources of funding as well as a foolproof plan of action to pursue the alternatives.
  • Concentration Risk: SVB was heavily concentrated in the technology sector. Instituting a more proactive and diligent understanding of concentration risk that takes into account factors such as geography, industry, etc. can be valuable in the short and long term.
  • Integrated Stress Testing: Executives must have actionable insights on scenarios where the bank is potentially pushed to its limits from a capital or liquidity perspective.
  • Liquidity Risk Planning: Dynamic plans are a must to better assess liquidity risk, and daily (or intra-day) plans are useful in establishing where the bank stands in terms of liquidity.

The foundation for risk modeling is a well-defined data architecture that can be leveraged by strong algorithms. Banks must therefore invest in technological capabilities around data, Artificial Intelligence (AI), analytics and automation to handle the massive volumes of data they generate.

Accelerating Data and Digital Transformation

Adopting a data-led risk transformation approach will empower bank executives to proactively evaluate their risk exposure and protect customers, shareholders and employees. However, this can be a daunting task for many banks, given the sheer scale and complexity of the undertaking – with the volumes, sources and formats of incoming data, not to mention the bewildering variety of options and solutions available in the marketplace.

Working with a third-party solutions provider that understands the ins and outs of the banking industry, and has expertise in technology, analytics and business process can power cost-efficient digital transformation that banks can leverage for their regulatory and risk management needs.

An ideal strategic partner puts skin in the game and brings the skills to analyze, design, build and run digital solutions. Benchmark capabilities would include a dedicated global talent pool, a center-of-excellence model, experience with hyperautomation and proficiency in data, AI and analytics.

To know how WNS can digitally enable effective risk management – combining operational processes and procedures, data engineering and skilled talent – contact BPM and Outsourcing Company | WNS.

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