COLUMN – Vinod Jain | If we all see the same version of truth in DLT do we need functions like reconciliation? It’s questions like this that industry analyst Vinod Jain tackles head-on—and the answer is more nuanced than many DLT corners of the market would have you believe
DLT has reshaped how capital markets approach transparency, data sharing, and real-time visibility. So much so that some participants now question the need for functions like reconciliation — the process of confirming that what firms believe they hold matches what they actually hold. After all, if every participant sees the same immutable ledger, what is there left to reconcile?
The truth is far more complex. Transparency does not automatically create trust. A synchronised ledger can still reflect incorrect data, flawed logic, or incomplete information. DLT ensures that everyone sees the same version of the truth — but for that truth to be reliable, it has to be validated against the firm’s own books and records. That responsibility still rests squarely on reconciliation.
Criticality of reconciliations
As tokenised and non-tokenised assets coexist, reconciliation becomes even more critical. Firms will increasingly operate in hybrid environments where some assets live on-chain, others remain in traditional books and records, and many move between the two (see Figure). In such a world, reconciliation is the only mechanism that ensures digital representations match the underlying economic reality. It validates that tokenised positions correspond to the correct quantity of locked assets, that smart contract events align with accounting entries, and that movements across ledgers—whether blockchain-based or legacy—are complete, accurate, and consistent.
This is not a theoretical concern. Tokenisation and the seamless movement of assets between tokenised and non-tokenised environments will create more opportunities for control functions to ensure that the sum of all representations does not exceed the total underlying assets. In other words, reconciliation becomes the guardian of economic truth.
As Rebecca Reid, senior product director at Trintech, a software vendor puts it: “As firms move into hybrid environments where tokenised and traditional assets coexist, reconciliation becomes the control layer that validates whether the digital record truly reflects the underlying economic reality.”
Even with DLT’s transparency, firms still face challenges with data integrity, system integration, and unresolved breaks. Research shows that more than half of auditors cite data accuracy as their top concern, followed closely by limited integration between reconciliation tools and financial systems. DLT does not eliminate these issues; it simply exposes them faster. Reconciliation remains the mechanism that validates completeness, accuracy, consistency, and finality across both on-chain and off-chain environments.
Root cause of breaks
Breaks don’t begin at the ledger — they begin upstream. Data can be incorrect before it ever enters a DLT platform, which means the platform simply processes and propagates the error. Worse, the faster processing cycle means those breaks can multiply far more quickly than anyone expects. A trade booked incorrectly in the front office, a wrong quantity in a token mint or burn event, a client or securities reference data field with a bad value — any of these can ripple through the DLT data flow and trigger reconciliation failures at speed.
As AI becomes more embedded in capital markets, reconciliation will benefit from intelligent break classification, predictive analytics, and automated root cause analysis. Firms can move beyond simple exception identification and begin anticipating breaks before they occur. This is especially valuable in high volume areas such as payments and securities positions, where early detection can prevent downstream operational risk. AI-enabled reconciliation strengthens audit readiness, reduces manual intervention, and enhances transparency across global operations — all of which are essential in a DLT-driven world.
Ultimately, reconciliation becomes the trust layer in a transparent ecosystem. It ensures that the data reflected on the ledger is not only visible but correct. It validates that tokenised assets are backed by real assets, that smart contracts behave as intended, and that cross-system movements are faithfully captured. It is, in the end, what bridges transparency and truth.
The call to action is clear
Reconciliation must be treated as the primary control tool in the DLT era. Firms would do well to invest in modern, intelligent reconciliation frameworks that operate in real time, integrate seamlessly with both blockchain and legacy systems, and leverage AI to accelerate break resolution. That means adopting standardised data models, strengthening data-mapping capabilities, and ensuring reconciliation processes can interpret and validate data across multiple asset types and currencies. Most importantly, the mindset needs to shift — from reactive break detection to proactive monitoring, using reconciliation not just to identify discrepancies but to continuously confirm the health of their systems.
Vinod Jain is the founder and principal of the financial research and advisory firm Adkrest, and based in New Jersey. His column with PostTrade 360° lets him highlight details worth noting, from various corners of the post-trade operations landscape. Find his PostTrade 360° columns indexed here.
