Legacy Infrastructure Is Creating Invisible Ceilings on Sell-Side Efficiency and Growth

Big sell-side players are trying to break free from their investment bank legacy systems and fragmented data environments, which limit their ability to scale into new markets, onboard new products, and meet rising client expectations. In fact, two-thirds of US and UK banking leaders estimate that their systems’ oldest operating programming code was written prior to 2000, and 30% estimate their oldest technology infrastructure to be from the 1960s or earlier.ⁱ Enterprise systems are often built by retail banking units for credit cards or auto loans and are not purpose-built for complex institutional tasks like financing equities on swaps or structured products. For every drawback of legacy technology that sell-side leaders can see and quantify, there are other, less visible drawbacks that erode margins and bog down workflows.

Fragmented environments often force firms to run separate, redundant middle-office functions for different strategies, resulting in a revenue-hemorrhaging exercise. Most sell-side leaders have endeavored to revamp operational and data technology, at least to some degree, but also to varying levels of success. Aging platforms continue to handle valid banking operations but have become invisible ceilings that stifle efficiency, block revenue growth, deter talent acquisition, and create systemic risks.

Here are some of the less visible barriers to efficiency and growth, and why now is the time for institutions to revamp key banking systems.

Sell-side operations scalability for new markets

As the industry reacts to ongoing structural change, investment banks have found the biggest symptoms — errors, inefficiency, and complexity — causing their biggest disease: They can’t grow. Brilliant financial minds are writing checks their systems just can’t cash. Workflows are accelerating across the board. Our attempts at marrying high-velocity digital transactions with aging infrastructure are...a marriage on the rocks.

Surging data volume in repo markets

A primary mechanism for funding trillion-dollar balance sheets, repo markets are shifting from bilateral to cleared structures. A single economic trade can generate dozens of clearing trades, dramatically increasing market data volume as well as anomalies. It is critical for banks to have modernized data models that can handle the surge without manual workarounds. Systems built to deal with static trades and end-of-day processing buckle under flows of new cleared repo business with many more events for each trade.

Jurisdictional complexity

Global expansion requires managing data across multiple jurisdictions with differing rules for data masking and regulatory oversight. Big banks that have enjoyed acquisition-led growth find themselves operating a trillion-dollar global balance sheet across 80 different markets, creating the need for a unified operating platform to consolidate what had become a deeply fractured infrastructure. Meanwhile, a treasurer funding that trillion-dollar balance sheet might receive 20 different middle-office and risk reports. Most of these are delivered only once per day, making real-time capital allocation nearly impossible without modernized infrastructure.

Complex asset class strategies stretch legacy systems

• OTC derivatives have complex lifecycle events for which information is trapped in unstructured PDFs that must be parsed and mapped to structured tables. Additionally, margin is inherently difficult to calculate, and errors in these calculations lead to dealers being either over- or under-collateralized, which creates counterparty risk and cash drag. These bilateral trades make it challenging for counterparties to automate because of less standardization of terms.ⁱⁱ
• In FX markets, global banks face significant operational hurdles when pulling global exposure reports across jurisdictions like China and India, where they must adhere to strict local data masking rules. Failure to appropriately do so while managing global FX exposure can lead to substantial regulatory fines.
• Like other asset classes, commodities units often operate on their own front-end trading and risk systems that do not standardize data with the rest of the bank. Rapid shifts in gold and silver markets, which have hit multi-generation highs, create immediate pressure on banks to understand their intraday risk and collateral requirements.
• Banks’ existing systems, often built for liquid public markets, are poorly equipped to handle the unique demands of private market assets. In private credit, for example, there is no industry-wide standard for how data from originators, mortgage servicers, or agent banks should be formatted or delivered. Unlike public markets where data errors might result in regulatory fines, errors in private market data can be catastrophic to the bank's existential being by way of multi-million-dollar loan losses. Further, settlement chokepoints exist because of the manual nature of private asset data processing, which has a direct impact on profitability.
• The digitization of assets including stablecoins and the digitization of cash and treasury for purposes of optimizing intraday funding of balance sheets means that banks must build monitoring systems capable of bridging on-chain and off-chain activity.ⁱⁱⁱ Tokenization of real-world assets is gaining traction, especially in repo, collateral, and structured products.^iv If banks are to unlock blockchain-based efficiencies in the tokenization of deposits, stablecoins for FX, or securitization of mortgages, they will need advanced plumbing.

Interest rates markets

Economic asset reference data like interest rate, inflation, and consumer pricing indices are necessary to monitor interest rate volatility, allowing the bank to track inflation and reposition strategies as desired. Bank systems must have the bitemporal modeling capability to track both effective date and knowledge date time horizons, thus enabling the linkage of changing analysis outputs to their economic drivers.