Trading

Trading Management Information (MI) from real time monitoring to historic trend analysis. Visual analysis delivered through agile dashboards, allow trading anomalies to be quick identified, and acted upon. Trading blotters can be enriched with high density visualizations, allowing traders to quickly assimilate their position and market impact, by moving them from huge tables of numbers to visual pattern detection.

Flexible analysis of trading data supports performance transparency around best execution aligning to the regulatory goals of Mifid II and Reg NMS.

Trading MI ranges across the trading lifecycle from pre to post trade. Existing usage within customers includes:

  • Order Book – Monitoring and analysis of consolidated order books across available liquidity pools
  • Pricing (FX) – Consolidated pricing across FX ECNS, identifying broker liquidity positions, dependencies and pricing latency, especially to market events
  • Flow / Hit Ratio – Monitoring, and trend analysis of RFQ trading activity across all e-trading channels
  • Pre-Trade – Basket risk / return analysis from historic trading activity
  • TCA – Real time and historic Transaction Cost Analysis, analyzing best execution across fragmented liquity pools, and through all algo types, books, counterparties, and instruments
  • P&L Monitoring and Analysis of Real Time and historic P&L
  • Trader Performance – Trading effectiveness measurement and trend analysis

Typically connecting and leveraging to CEP, Messaging & Tick history databases.

Key Technology Partners: kx, OneTick, Tibco.

 

Risk & Finance

Intra-day and historic management information (MI) across the trading book in risk and finance. Visual analysis delivered through agile dashboards, allow risk and P&L anomalies to be quickly identified and acted upon. The use of visual pattern detection allows risk and finance analysts to quickly identify the overall Bank position, identify abnormalities, and investigate them, however deep they are within the selected risk hierarchy. The enriched transparency of the risk metrics, supports the principles of BCBS 239 for accuracy and timely reporting across risk type and BCBS 248 for intra-day reporting.

Risk & Finance I ranges across the risk types. Existing usage within customers includes:

  • Liquidity – Intra day and historic liquidity analysis and reporting in accordance with BCBS 248
  • Data Quality – Analysis of the risk metrics and dimensions that constitute risk reporting
  • Market –Intra day and historic VaR & sensitivity reporting and trend analysis across book and instrument hierarchies
  • Credit / Counterparty – Intra day and historic exposure reporting and trend analysis across business, and counterparty legal hierarchies
  • Operational – Operational risk reporting, aligned to system utilization and problem impact
  • P&L Attribution – Intra-day and historic analysis of P&L, focusing on the impact of high frequency trading, and aligning the attributed P&L to the market risk metrics
  • Trading Limits – Real Time monitoring and analysis of front office trading limits, comparing current market activity to historic trading profiles, allowing trading desks to proactively identify changes to risk profiles

Typically connecting and leveraging to Real Time Cubes

Key Technology Partners: QuartetFS.

 

Compliance

Compliance Management Information (MI) from intra-day and T+1 monitoring to historic investigations across all asset classes and regions in support of the principles under Mifir II / MAD II and Dodd Frank. Usage covers both reactive backwards looking investigations, proactive monitoring, and forward looking proactive risk profiling. In all cases, visual analysis delivered through agile dashboards, allow trading abnormalities to be quickly identified and acted upon. Existing reporting can be enriched with high density visualizations, allowing compliance analysts to quickly assimilate normal trading activity, and importantly deviations from the norm, by moving them from summaries and tables to visual pattern detection.

Compliance MI use cases range across Market Abuse and Unauthorized Trading. Existing usage within customers is being driven by the impact of regulatory change, and as a consequence the implementation are evolving from a trade focus to a trader focus.

  • Trade Surveillance – Analysis of surveillance alerts, whether spoofing, quote stuffing, wash trades etc in context of the order book. Playback through the trading day; tick by tick. Trading activity, including market health analysis.
  • Alert Consolidation – Intra day and historic alert reporting and trend analysis consolidating alerts across traders, regions and asset classes
  • Holistic Surveillance – Analysis across alerts generated from both trade surveillance and comms surveillance, correlating the different components of fraudulent behavior, supporting trade reconstruction as outlined in Dodd Frank, and critically adding context to existing alerts, producing higher value alerts with more efficient investigation.
  • Behavioral Risk Pricing – Holistic surveillance of traders together with trading and risk positions, and security alerting. Traders are risk scored, and compared to past performance and their peers. Trader interaction networks are investigated to speed understanding of past activity, and again identify behavioral abnormalities.

Typically connecting and leveraging to CEP & Tick history databases

Key Technology Partners: kx, OneTick, Nasdaq SMARTS

 

Operations

Trading Operations Management Information (MI) from real time monitoring to historic trend analysis. Visual analysis delivered through agile dashboards, allows abnormalities in the trading environment to be quickly identified and acted upon. The displays of Trading Operations can be enriched with high density visualizations allowing staff to quickly identify trading problems, by moving them from summary dials, and tables to visual pattern detection.

Trading Operations MI usage differs if a broker, or an exchange / ECN. Existing usage within customers includes:

  • Trading Health – Monitoring of trading infrastructure responsiveness to flow
  • Latency Analysis – Analysis of quote and order latency across the trading infrastructure by trade type, trading algorithm, liquidity pool and market volatility
  • System Utilization – Monitoring and trend analysis of system utilization and correlation with trading flow

 

Typically connecting and leveraging to CEP, Messaging & Tick history databases

Key Technology Partners: kx, OneTick, Tibco

 

Investment Management MI

Investment Management MI, consisting of the analysis of fund and consistent performance related to peers and across time. Replacing the need to read through detailed multi-page reports, with visually rich dashboards allowing portfolio managers to visually pattern match to quickly identify outliers and constituent correlations and investigate underlying causes. Agile creation of interactive analytical dashboards allows effective and flexible analysis across latest returns plus historic trend analysis.

Investment Management MI ranges across both risk and return analysis. Existing usage within customers includes:

  • Performance analysis, both absolute, and relative to benchmarks.
  • Risk analysis combining risk metrics, whether intra day or T+1 to produce a complete risk view of the portfolios.
  • Attribution of returns.
  • ‎Customer money flow analysis

This is performed both internally within the fund, and provided externally by the fund to relevant customers.

 

IoT & Sensor Analytics

Visual analysis delivered through agile dashboards allow sensor anomalies to be quickly identified and acted upon. Sensor displays can be enriched with high density visualizations, allowing operational staff to quickly assimilate the overall situation, and the impact of the anomalous sensor readings in context. This is achieved by moving from detailed sensor views, and huge tabular displays, to visual pattern detection.

  • Flexible analysis of both real time, intra-day and historical data, supports operational transparency, allowing problems to be quickly identified and investigated.
  • IoT MI ranges across industry, where sensors are recording intra-day, and being stored
  • Utilization – Monitoring & Analysis of system / grid / network utilization
  • Fraud – Analysis of anomalous activity in relation to peers and geography
  • Pricing – Correlation analysis of pricing to customer demand profiles
  • Capacity Planning – Trend analysis of utilization based on defined scenarios
  • Predictive Maintenance – Performance monitoring of key infrastructure, identifying optimal time windows for maintenance

 

Typically connecting and leveraging to CEP, Messaging & Tick history databases

Key Technology Partners: kx, Tibco

 

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