Re-Entering Private Credit or Digital Assets? The Data Infrastructure Question You Need to Answer First

Investment banks have wind in their sails as a new era of less restrained capital requirements, softened regulatory scrutiny, and banking consolidation has begun. The amended Basel III Endgame proposal could reconfigure the entire banking landscape, especially opportune for tier two, mid-market institutions to make a play for tier one status. By the same token, U.S. regulators are forging digital asset guardrails which will open new business lines in stablecoins and tokenized money market funds, tokenized deposits, and digital collateral. As such, banks are expanding their digital asset and private credit footprints, including ABL in mortgages, receivables, and structured credit.

These new developments have sell-side institutions asking, firstly, if they should re-enter these spaces, and secondly, whether their data infrastructure can support the operational requirements. Here are some critical considerations that inform their answers.

How investment banks scale direct lending partnerships

Banks are zealous about bringing in more credit business via warehouse lending and direct lending partnerships. Some have moved toward an originate-to-share model, enabling them to originate loans and then share the exposure with private capital firms; as evidenced by the May 2026 $17.5 billion deal between Citigroup and Blackrock’s HPS.[i] Such relationships enable banks to provide more capital to clients without holding the entire risk on their balance sheets. The banks and asset managers will each have their respective operating models managing the asset, introducing potential manual exercises for every amendment, payment, or collateral update. For institutions to scale these partnerships, they will need standardized instrument modeling and security mastering so there is consistent reference data and data lineage.

Operational complexity of asset-based lending

Regulators have incentivized banks to return to asset-based finance (ABF) and ABL, including mortgages, receivables, and mezzanine lending, because bank-led structuring offers greater transparency and control compared to the Nonbank Financial Intermediation (NBFI) sector. Further, the new risk weight framework and the removal of mortgage servicing assets deduction thresholds make it more economically attractive for banks to originate, pool, and securitize high-quality residential mortgages. However, ABF brings perhaps the most intensive operational complexities to the middle- and back-offices.

Before a bank can achieve instrument and security master management, its systems must ingest and transform torrents of unstructured data from loan tapes, trade tickets, term sheets, mortgage documents, capital call and various other notices, and drawdowns. Operations cannot afford to summon a salaried team to manually map fields and reconcile naming inconsistencies. This latency causes delayed onboarding of deals in terms of executing financing approvals and collateral eligibility checks, stale risk calculations, poor lineage tracking, or errors in calculating Basel capital levels. Banks lose interest income with latency, since they cannot charge financing interest until these transactions settle. Furthermore, missing critical details in unstructured data could lead to disastrous loan losses.

Smooth private credit operations demand solid security mastering

Advanced data infrastructure, fluent in capital market nuances, can transform unstructured data, no matter its scattershot formatting. It standardizes and centralizes reference data, which enables stout security mastering - the unified repository of security data, aggregating all its attributes to make lifecycle operations work properly. Banks then enjoy the flexibility to use the same reference and investment data across trading, risk, compliance, and operations. This is the key to piercing the growth blocker to scaling operations to incorporate new business lines, new regions, and more volume.