Presented by Monocle

Why banks still fail in 2023 and why they don’t have to

 ·26 Jun 2023

Following the collapse of several high-profile banks earlier this year, regulators are scrambling to uncover exactly what led to these bank failures and what can be done to prevent similar occurrences from happening going forward.

The autopsy on Silicon Valley Bank (SVB), the first major victim of the latest banking crisis, has revealed that its executives had scaled back its interest rate hedging strategy and knew it could face a liquidity crisis as early as November 2022.

In March 2023, it collapsed under the weight of one of the most severe bank runs in history, as depositors withdrew $142 billion in two days, representing 81% of the bank’s total deposits at 2022 year end.

Over the past few decades, the banking industry has shifted its priority towards managing profitability rather than risk.

This is evident in the collapse of SVB, as well as Credit Suisse – a bank that was embroiled in controversy for many years.

Additionally, we have seen traditional banking become entangled in a battle against FinTechs and challenger banks that has led to a renewed focus on innovation through technological advancement.

Cloud computing, artificial intelligence, open APIs and blockchain have been declared as the future of banking, however, in the race to embrace these new technologies, many banks have seemingly forgotten the importance of the building blocks for decision-making and strategy execution – their defensive data strategies.

The aims of defensive data strategies are to minimise negative outcomes and risks – such as SVB’s interest rate and liquidity risk – as well as to comply with regulatory and fiduciary requirements.

While these strategies may seem mundane and unexciting compared to the novelty of cutting-edge technologies, they are nevertheless the critical building blocks upon which trust in the system ultimately rests.

Defensive data strategy serves as the stable base, as in the case of a building’s foundation, on which an offensive data strategy can be built, which paves the way for future innovation.

Yet, without trust, the value that these exciting new innovations may bring are ultimately nullified.

Banking is a complex industry that involves a wide range of financial activities, including lending, borrowing, investing, and managing financial assets.

At the core of all these activities, however, is the concept of trust. Banks function as the intermediaries between savers and borrowers.

Savers trust banks to safeguard their money, provide secure and convenient access to their funds, and offer competitive returns on their deposits.

Borrowers, in turn, trust banks to provide them with access to credit, manage their financial risks, and help them achieve their financial goals.

In addition to upholding fundamental principles, banks have a responsibility to ensure that regulators, shareholders, and their own employees can trust the information that they provide about their activities.

This is echoed by investment legend Charlie Munger, Berkshire Hathaway vice-chairman and right-hand man to Warren Buffett, who recently declared that “bankers should be more like an engineer, avoiding trouble rather than trying to get rich”.

Furthermore, banks must ensure that they comply with a plethora of regulations, including Basel III/IV, MiFID II, AMLD, and many others.

These regulations require banks to collect, store, and report a vast amount of data to regulatory bodies. Implementing and maintaining robust and trusted statutory and regulatory reporting platforms can be challenging for banks, largely due to the complexity of regulatory requirements, data quality and integrity, and legacy infrastructure.

This burden will no doubt increase as regulators begin to implement new standards and requirements to mitigate similar bank runs and liquidity risks in the near future. Despite these obstacles, non-compliance is simply not an option.

Failure to comply with regulations can lead to severe consequences, including substantial fines, reputational damage, and in the most severe cases, the revocation of banking licenses.

Therefore, both senior executives, as well as regulators, must always have access to accurate and reliable data to make well-informed decisions and manage risks in an effective and timely manner.

The recent examples in the US and Switzerland – where poor decision-making has resulted in catastrophic consequences – have only served to further highlight the critical importance of accurate and reliable data in the effective management of these financial institutions.

While defensive data strategies are crucial, it does not mean that banks are unable to innovate.

Defensive and offensive data strategies are not mutually exclusive, in fact, they are mutually beneficial.

This is particularly true in case of new data-dependent technologies, such as artificial intelligence, where robust, comprehensive, and accurate data from a defensive data strategy is one of the biggest success factors in any advanced analytics initiative.

Monocle Solutions assists clients with the implementation of data products that prioritise defensive measures, such as completeness, accuracy, and timeliness, while also enabling users to confidently identify new opportunities, enhance products, and provide superior customer service.

Ultimately, this not only gives banks the assuredness that their regulatory requirements are met, but it can also provide them with a competitive edge in an increasingly challenging and uncertain banking landscape.

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