FULTECH CONSULTING RISK TECHNOLOGIES

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1 FULTECH CONSULTING RISK TECHNOLOGIES ENTERPRISE-WIDE RISK MANAGEMENT Many global financial services firms rely on their legacy technology infrastructure for critical calculations dedicated to support enterprise-wide risk management such as exposure, initial and variance margin, counter-party credit risk, collateral pricing, and scenario analysis. The challenge facing the industry is batch technology is no longer suitable for today's fast-paced markets as observed by the recent failures at JPMorgan Chase and Knight Capital. The solution lies in next generation technologies that can process terabytes of data sub second to enable risk surveillance in cycles of 10 minutes or less. PARADIGM SHIFT? Perhaps one of the outcomes of the global financial markets meltdown of 2008 is the changing role of Compliance and Risk Management. Previously relegated largely to reporting functions, compliance and risk management are now actively managed, real-time profit centers that can differentiate competitors who can effectively manage their exposure. MODELS, SIMULATIONS, AND CEP ENGINES Compliance and risk management departments are deploying data intensive methods and processes using increasingly complex models, simulations and CEP engines. These processes and models require a combination of intensive CPU/calculation time and have a very large data footprint (terabytes to petabytes). Whether a model or process, the types of computations and processes are similar in risk, compliance, collateral management and trade execution and require technology which has high computational capabilities on ever increasing big data set. Trading, risk, and compliance desks are seeking competitive advantages through the capabilities of processing huge amounts of information. Whether computing a hybrid VaR model using tick data, running Monte Carlo simulations for CVA, running SOX compliance processes via a CEP engine or pricing collateral using a mark-to-model methodology, all of these computations and processes share a similar technical footprint. Performance and scale can only be achieved through the combination of high computational throughput and deterministic, persistent, scalable data storage which is extremely fast. Many solutions have the throughput through grid technologies but lack the data storage component that allows them to scale. The advantage comes when Big Data is as readily processed at the same speeds as small data computations that can be processed on only one server.

2 FULTECH RISK SOLUTION Fultech s Risk Solution combines best-in-class database and data storage technologies resulting in unprecedented performance at the point-of-trade for highly data intensive (> 2 terabyte) operations. Our solution capitalizes on the speed of access to our data storage while maximizing CPU time via our application and database technologies resulting in optimized performance for highly data intensive calculations requiring real-time execution. Highlights Functionality Our solution incorporates a rich set of financial models, processes, and simulation functions to accommodate trading, risk and compliance desks needs in real-time. It is also highly customizable and enabled by the Fultech consulting team to tailor pricing, risk and analytics models per our Clients needs. Speed By applying in-memory, parallelization, vector and columnar technologies of our database and moving data to the storage block, we maximize CPU runtime dedicated to calculations with near-zero wait states meaning data is waiting on the processors. Scalability Linear Scalability as storage scales with data size providing the same data access speeds (5µ latency) for terabytes to petabytes FULTECH PROTOTYPE RESULTS In order to test the performance and scalability of our solution, the Fultech Solutions Team devised a proof-of-concept in the risk management space. The team created a test scenario for portfolio exposure by simulating 10,000 to 50,000 accounts with 3,278 stock positions in each account to determine system performance for calculating portfolio exposure results based on 10-year historical VaR (value-at-risk). In order to process the data and produce the test results, the system would need to complete up to 4.28 billion VaR calculations on 13.5 terabytes of data. To further standardize our test results, we executed the test on 4 quad CPU servers with 4 instances of McObject s extremedb Financial Edition and 4 Kove XPD L2 Storage Units. We also executed Test 1 on one server with 10,000 accounts to establish a baseline result which would fit on one server. Tests 2-4 expanded the number of servers and cores to show performance scaling across multiple servers. The configured solution produced results on the 50,000 accounts in less than 8.5 minutes. That s 428 billion calculations performed on 13.5 terabytes of data in less than 8.5 minutes or 839+ million calculations in one (1) second.

3 Test results are provided below; Performance Test Results Test 1 Test 2 Test 3 Test 4 # Host Server(s) # Cores # XPD(s) # CPU(s) CPU Run Time 99% 99% 99% 99% Data Size (tb) Data Reduction (%) 400% 400% 400% 400% #Funds (Accounts) 10,000 10,000 30,000 50,000 # Securities (Positions) # Days (10+ Years) 2,608 2,608 2,608 2,608 Confidence Level 95% 95% 95% 95% Exposure ($millions) $ (1,043) $ (1,043) $ (1,079) $ (3,203) Delta Store Time (sec) Data Calc Time (sec) Total Proc. Time (sec) # Txns/Calcs (billions) Data Proc. (gb/sec) HFT RISK SOLUTION EXAMPLE Capitalizing on our Risk Solution Architecture, Fultech has proposed a High Frequency Trading Solution to a Tier I Global Bank customizing our technologies to provide real-time limits surveillance, position exposure calculation by account, collateral pricing, and position management. As a result, our Client is able to update risk thresholds intraday, implement a direct interface to the trading entitlements process via a CEP engine, and even establish a synthetic hedging desk to hedge desk exposure upon default of a counterparty. An architecture diagram of the HFT Solution is provided below;

4 MBS RISK MANAGEMENT EXAMPLE COMMITMENTS, LOAN ORIGINATION, & SECURITIES. Applying our technologies to risk management dedicated to mortgage-backed securities, we again will execute similar types of models, simulations and processes. Consequently we will customize our solution needs to consider mortgage commitments to mortgage loan origination including the ability to link individual loans to the actual mortgage-backed security to monitor performance covering the GSE guarantor clause. For the MBS desk, a customized solution will provide the following; Portfolio valuation at the individual loan level Interest rate, credit, liquidity and counterparty risks calculations

5 Actively manage exposure via executions on automated thresholds Run scenarios and simulations on a 5-minute cycle Analyze a portfolio s return through benchmarking and attribution Monitor P&L, VaR, and Balance Sheet in real-time CEP engine to rapidly implement new rules or processes