IT Services and Solutions for Exchange-Traded Funds

Solutions meant to streamline the creation and rebalancing of ETF baskets in line with their target indices. The software automates index research and replication based on the issuer’s strategies (full, sampling, optimized), substitution rules, and diversification thresholds. It can handle index constituent tracking and data-driven generation of creation and redemption baskets for authorized participants (APs).

Software that enables analytics-driven construction and optimization of multi-asset ETF portfolios, as well as automated control of ETF holdings, exposures, and cash positions across multiple funds. Using such tools, issuers can model portfolio- and lot-level allocations, calculate real-time NAV, track financial outcomes from creation and redemption events, and monitor intraday portfolio drifts.

Such software automatically processes primary market orders related to ETF unit creation and redemption and offers automated generation of asset buy/sell orders according to authorized participants’ instructions. The system handles pre-trade order compliance and exposure checks and can provide analytics-based instructions for ETF portfolio realignment with the target index.

Using such software, ETF managers can connect directly to multiple trading venues and execute basket trades, either ad hoc or automatically based on tailored rules. EMS tools support automated spotting of arbitrage opportunities and smart order routing to the best-fitting venues. Built-in analytics dashboards provide real-time visibility into market data, slippage, and execution efficiency.

Software that automates the breakdown of ETF returns into key contributing factors such as asset selection, allocation volume and timing, and index tracking error. It supports daily and intraday attribution analysis to align with the ETF’s transparency standards. Advanced tools can incorporate artificial intelligence (AI) to auto-pinpoint sources of underperformance and suggest optimization steps.

Digital tools aimed to streamline risk exposure analysis, scenario stress testing, and VaR forecasting across ETF portfolios. Portfolio managers can simulate and quantify the outcomes of chosen hedging strategies, including complex ones that involve hedge overlays and tracking risk. Predictive analytics powered by machine learning (ML) can be applied to accurately project hedge performance.

Solutions used for real-time tracking of ETF liquidity metrics like bid/ask spreads, trade volumes, and iNAV premiums/discounts. They can be configured to immediately notify issuers about unusual spread widening, benchmark price divergence, abnormal tracking error, and other necessary events. Such tools can also auto-pull AP and market maker data and monitor basket liquidity and redemption risk.

Software that automates multi-currency calculations (NAV, P&L, taxes, etc.), fee accruals, bookkeeping, and financial reporting. Custom solutions can support any required ETF structures (e.g., corporation, trust) and accounting standards (IFRS, US GAAP, local standards). They can be integrated with fund admins’ and custodians’ systems for automated gathering and reconciliation of transactional data.

Software that relies on rule-based engines and robotic process automation (RPA) to generate and distribute ETF reports, including regulatory filings (e.g., Form N-PORT, Form N-CEN, 485BPOS) and investor-facing disclosures (daily holdings summaries, ETF fact sheets, iNAV disclosures, etc.). Custom solutions can support any required report formatting and submission timing standards.

Secure digital platforms meant to streamline interaction between ETF issuers and authorized participants. Using a self-service portal, APs can access live basket files, submit unit creation, redemption, and substitution requests, track settlement details, view and download reports. Custom portals can be equipped with APIs for ready-to-go integration with partners’ internal OMS and EMS systems.

With such software, ETFs can automatically monitor operational compliance against internal policies and region-specific sectoral regulations (e.g., the Investment Company Act of 1940, SEC mandates, and CFTC rules for the US). The tools run real-time compliance checks across areas like asset diversification, leverage, and trading and immediately report breaches to compliance specialists.

Intelligent chatbots powered by large language models (LLMs) that aid ETF teams in searching task-relevant data, compiling insights, and drafting documents. They instantly process textual and voice employee inquiries and respond in a manner akin to regular human conversation. Unlike traditional chatbots, LLM-powered assistants can analyze unstructured data and reason on complex investment aspects.

Solutions that automate the integration, validation, enrichment, lineage, and maintenance of disparate data relevant to ETF operations. They can apply intelligent image analysis and machine learning for automated processing of multi-format documents. Centralized, restricted data storage removes data silos and duplication and prevents unauthorized access to sensitive information.

Solutions that enable automated calculation, forecasting, and reporting of chosen metrics across ETF operations, finance, investor experience, and risk management areas. Analytical dashboards offer an aggregated view of area-specific KPIs with slice-and-dice options for multi-dimensional data visualization. Advanced systems can incorporate AI-powered predictive and prescriptive analytics.

Solutions that enable automated execution and immutable recordkeeping of ETF operations on the blockchain. This approach enhances ETF transaction auditability and ensures real-time transparency for regulators and investors. Smart contracts can automate multi-step workflows across unit creation and redemption, fund share transfer, reporting, and operational compliance checks.

Solutions that allow ETF issuers to convert the fund’s shares into tradeable digital tokens. The issuance and trading of tokenized ETFs occur automatically on the blockchain according to the fund’s unique rules coded in smart contracts. By tokenizing ETFs, issuers can enhance fund liquidity, introduce 24/7 trading options for end investors, and attract a broader investor base.