TOWARD A STANDARDIZED APPROACH TO RISK AGGREGATION Starting with Balance Sheet Management Dominique GENDT Head of Cross Asset Risk Platform Development ACTIVEPIVOT USER GROUP PARIS 12TH JUNE 2015
Agenda Introduction HSBC Cross-Asset Risk Balance Sheet Management The Project Functional goals Technical requirements Process flow ActivePivot Technical Considerations Functionalities Benefits User Interface Perspectives Challenges Next Steps Items for the future 2
Introduction HSBC Cross-Asset Risk Balance Sheet Management 3
HSBC (*) Big on history, big on scale Founded in 1865 6,900 offices 84 countries and territories 250,000 staff worldwide 220,000 shareholders in 134 countries and territories Serves more than 60 million customers (*) As of 2014 4
Cross-Asset Risk initiative Standard Components Analytics / Calculation Engine Trade Feeds / Market Data Risk Store Aggregation of Common Analytics Standardisation of sensitivity outputs Intraday / near Real-Time Aggregation with large volumes Visualisation Common Technology Choices Unique per component Implementation could vary across business lines 5
Balance-Sheet Management (BSM) Treasury function for the Bank Covers GBM and also the Retail Bank Mandate to trade IR products and Bonds issuance Managing the IR risk of the Bank Large presence in many countries Desks in 70 locations Manages in London a $ 1.5 T balance-sheet size Uses a big variety of trading platforms Prototype for a larger roll-out of a Strategic Risk Infrastructure Plain Vanilla products across Rates and Fx Fixed Income Analytics to generate Rates sensitivities Initial focus on London desk 6
The Project Functional goals Technical requirements Process flow 7
Functional goals Intraday Risk Management for the traders in the Front Office Sensitivities generated by internal Pricing Library Consistency across all product types IR Analytics in the first phase Periodic full recalculation Display in a custom UI Drill-through + Trade Analysis EOD Risk feeds for Market Risk and Finance Sub-set of the EOD Analytics sent to downstream systems Same models as the FO, potentially different curve assumptions 8
Previous situation Limited Intraday Capacity Manual process Limited scope, focused on main assets End-User Computing Manuel process and tool designed by FO XL-based limiting the adoption on a larger scale Inconsistent EOD Calculations done in different Trading Systems Not always consistent (Market Data, Cut-Off time,..) 9
Technical requirements NFR On-the-fly aggregation Notification of trade events Integration with HSBC infrastructure Existing Trading Systems and trade feeds Re-use of existing mature Market Data and Analytics Existing FO User Interface Standardisation and Scalability Generic solution, not asset-alignment Volume expansion up to a factor of 10 10
Functional flow Trades and Positions Reference Data Market Data ActivePivot UI Risk and Valuation Engine Risks Risks PnL Grid (Rates Analytics) (Fx Analytics) Calculation Distribution 11
ActivePivot Technical Considerations Functionalities Benefits User Interface 12
ActivePivot - Technical Considerations Server Specifications 8 cores (2x4 cores) / 256 Gb RAM Intel Xeon CPU @ 3.30GHz Active Pivot 4.4.9 Java 7 / Tomcat 7 Load balancing Using F5 load balancer between 2 live-live AP instances Disaster Recovery QIP between Production and DR 13
ActivePivot Features 1/3 Vectorisation Capacity to sum-up vectors as a native type Post-Processors Analysis Dimension Member of arrays exposed as a native measure Currency Conversion Comparator (Percentiles, Top 10) Relational Store Data join, cascade reaction 14
ActivePivot Features 2/3 Transaction Handler Build additional risk measures based on deal level business rules Perform data look-up (join on an heterogeneous selection of attribute) Drill-Through Ad-hoc post-processor (to extract specific measures from vectors) Aggregation Just in time Trade ID as dimension 15
ActivePivot Features 3/3 Embedded Webservices Complex reporting service based on data mapping business-rules Store-based reconciliations Ad-hoc UI Service Data Model Status cube for Error Management Time snap-shot for Run-Selector Access Control Multiple user profiles Multiple business with segregation of data 16
ActivePivot - User Interface (1/3) Portfolio View Standard tree view consolidating PV, accrual and IR Risk Filters per product type, portfolio, intraday trades Drill-through, reporting currency 17
ActivePivot - User Interface (1/3) - Portfolio View 18
ActivePivot - User Interface (2/3) Aggregated view per risk type Main view for Risk Management Filters per product type, portfolio, intraday trades Drill-through, reporting currency 19
ActivePivot - User Interface (2/3) - Risk View 20
ActivePivot - User Interface (3/3) Trade Blotter Real-time view of the trade activity Consolidation across Trading Systems Trade Detail view 21
ActivePivot - User Interface (3/3) - Trade Blotter 22
Benefits For business users Periodic, consistent and full recalculation of their book No manual effort. Time is spent in managing the risk Fine granularity Quotes? For IT Component standardisation Gained valuable expertise and experience on a relatively simple use-case 23
Perspectives Challenges Next Steps Items for the future 24
ActivePivot Open Points Load Balancing That means instances are independent Clustering No clustering means we are running with 2 instances that could be de-synchronised Ad-hoc post-processor (would benefit from a native implementation) File Management Ideal for dev. Difficult to manage for Production Persistance Required by many regulations / business requirements Big Data 25
Cross-Asset Initiative Next Steps Upgrade to ActivePivot version 5.1 Scalability improvements / Performance Other data sources e.g. limit management (ActivePivot Sentinel) Long-term storage and access Connect ActivePivot to a solution to store historical data On-boarding Strategy Other locations, other product lines 26
Summary Front Office uses ActivePivot for Intraday Risk Management Part of a strategic standardisation initiative across the bank Connected to in-house Risk Services Offers scalability and performance to aggregate risk data Current usage is limited to a particular business Working on a strategy for a broader adoption 27
TOWARD A STANDARDIZED APPROACH TO RISK AGGREGATION Starting with Balance Sheet Management Dominique GENDT Head of Cross Asset Risk Platform Development