Our Solution

The path to achieving
End-to-End digitization for financial firms
Begins Here

PeerNova’s unique approach enables financial institutions to build a single source of truth for their financial workflows. The data and process integrity that the Cuneiform Platform provides are used to solve complex problems such as post-trade validation and positions management, intraday liquidity management, data monetization, compliance, and regulatory reporting, and data and process governance.

Use Case

Post-Trade Validation
and Position Management

While post-trade processing is a non-differentiated function, a substantial amount of effort and resources are spent to streamline the complex workflows in order to maintain a golden copy of verified and matched data. Examples of this type of data include transactions, positions, payables/receivables, and reference data. Traditionally, data integrity has been achieved by using semi-automated reconciliation processes.

Reconciliation of positions and transactions across various internal systems and market participants (e.g. CCPs, counterparties, middleware, or confirm parties) is crucial for every financial institution to manage risk and remain compliant with regulatory requirements. For example, in cleared trade workflows, an executing broker receives nightly reports from CCPs. The CCP reports have to be reconciled with the internal trade systems of the broker. For cleared derivatives, there’s a need to reconcile with affirmation/confirmation platforms such as MarkitWire™. In many cases, there’s an additional need to reconcile books/position-level compressed reports against the original uncompressed trades.

Post-trade validation and position management: Multilateral reconciliation capabilities shows real-time exceptions for individual trades and position level reconciliations. End-to-end visibility of events ensures faster break detection and resolution.

Interested?

Request a Demo

Use Case

Intraday
Liquidity Management

Intraday Liquidity Management represents a bank’s ability to meet financial obligations through cash flow, funding activities, and collateral management. Intraday liquidity management may include real-time visibility into liquidity risk, funding costs, capital implications, regulatory reporting (per intraday liquidity guidelines), and enhanced liquidity services to customers.

Financial firms need to know the appropriate funding accessible at any given time to meet their payment and security settlement obligations. A firm that fails to manage its intraday liquidity effectively may become unable to meet an obligation, which could affect the firm’s liquidity position and that of other parties. This liquidity risk can then lead to significant funding and capital costs particularly during times of market stress. In order to support these activities, financial institutions are looking for end-to-end transparency of their liquidity flows at both global and granular levels. Data and process integrity guarantees on all liquidity flows is an essential requirement for effective liquidity management.

Intraday liquidity management: Categorized, real-time availability of intraday liquidity funds is key to monitoring financial positions at any time. Timely tracking of intraday exception metrics keeps risks under control.

Use Case

Data
Monetization

Market participants generate revenue from data through numerous channels including exchange feeds, settlement, ask/bid spreads, index fund reports, LEI listings, corporate actions, market aggregates, reference and derived data.

Financial Institutions and market participants create data in the course of operation. Data, as a representation of an asset, a record of a transaction, or the settlement of a trade is transformed and enriched as it moves through complex workflows. Systems aggregate and collect data across its lifecycle as it flows through multiple functional areas.

Since systems are siloed and data is fragmented in these silos, the combination and use of aggregated data for new uses cannot be easily achieved. The ability to generate higher revenues from the monetization of data as an asset by discovering, collecting, and analyzing data from existing fragmented data sources to create new combinations for commercialization becomes an overwhelming challenge. Golden sources with guaranteed data and process integrity lead to better data monetization for financial firms and their clients.

Use Case

Compliance and

Regulatory Reporting

Organizations face growing pressure to provide complete transparency and accountability in a timely manner to meet regulatory reporting requirements such as MIFID II. Financial institutions face crucial data integrity and information management challenges due to data flowing from multiple internal and external systems in various formats. Ensuring data integrity of the extracted datasets from these core systems for the purposes of reporting is time-consuming and expensive. Process integrity needs to be guaranteed to ensure completeness and correctness of all workflow steps governing the data, making reporting even more challenging.

PEERNOVA

Building real-time frictionless financial markets through trust and transparency

End-to-end Digitization with data and process integrity

Use Case

Data and
Process Governance

Financial institutions face many challenges in keeping up with the complexity of data governance policies introduced by new and ever-changing global regulatory initiatives. Consequently, they are constantly looking out for a robust, agile data governance platform that provides assurance of the completeness, accuracy, and consistency of data over its entire lifecycle. Data governance includes the need for the integrity of the data to be trusted. It involves guaranteeing the data integrity of an organization’s existing golden sources. Lack of data integrity leads to multiple reconciliations of data and hence the need to maintain complex workflows.

Datasets become important in terms of how they are used, who uses them and what their use is – all of this information is described in the processes that generate, manipulate and use these data sets. Process governance is a framework that guarantees process integrity. For example, it is essential to identify bottlenecks for high-value orders in a pipeline or whether a workflow meets the latest regulatory requirements. Today, answering these questions requires many manual steps of investigations across functional silos.

An integrated solution that guarantees both data and process governance provides a unified model for a scalable audit trail that provides many benefits: faster time to market for new products, better monetization of data and assets, greater client satisfaction and retention, and reduced operational risk and cost.

PeerNova's Chain in the Valley

Blog on Medium


 

Podcast