MIS is an information system that processes data into information. It uses transaction processing systems for input data and generates information that can be used for operations control, strategic planning, management control, and problem solving. There are several functional business areas of an MIS including accounting, human resources, inventory, manufacturing, and other areas. An accounting information system collects, records, and evaluates financial data and communicates it to management. It includes financial, management, and cost accounting systems. A MIS helps managers make timely and effective decisions by providing accurate data across various business functions.
The document discusses testing strategies for stock exchange and trading platforms. It outlines the key challenges in testing, including complex trading scenarios, compliance with regulations, and ensuring performance. It recommends developing test plans with different levels, including business process flows, test scenarios, and test cases. It emphasizes the importance of integration, performance, and failover/recovery testing given the critical need for low latency and high reliability. Finally, it stresses that thorough testing is crucial for stock exchanges to ensure their trading applications can handle increasing volumes, execute trades speedily, and safeguard investors.
This document discusses various financial securities and the role of information technology in stock exchanges. It describes common types of securities like stocks, mutual funds, and foreign currency. It then outlines the history of transaction documentation and discusses current stock exchange technologies like NEAT and BOLT that facilitate high-volume automated trading. The impacts of this change include increased transparency, efficiency and accountability for customers, industries and governments.
ICPAS Breakfast Talk Series - Maximising IT Audit 13 Mar 2013Barun Kumar
This document provides an overview of maximizing IT audits. It discusses planning IT audits by deciding the audit approach, identifying key IT application controls, and determining which IT general controls to test and testing frequency. It also covers executing IT audits by testing control design and operation and selecting samples. When analyzing results, it examines how to assess the impact of IT application control and IT general control deficiencies and whether alternative controls exist. The document emphasizes the importance of understanding interdependencies between different types of IT controls.
This document discusses how computers can be used for controlling business operations and decision making. It defines controlling as monitoring plan implementation and making corrections, and decision making as choosing the best solution from multiple alternatives. Computers are used for inventory management, presentations, communications and more. Transaction processing systems support data entry and record transactions. Management information systems collect and share management data. Decision support systems provide tools to aid management, operations, and planning decisions. Overall, computers make controlling and decision making faster and more effective for management.
Information system in business functions unit ivlaiprabhakar
This document discusses different types of management information systems (MIS) used in business functions like accounting, finance, manufacturing, marketing, and human resources. It provides details on the purpose and components of accounting information systems, financial MIS, manufacturing MIS, marketing MIS, and human resource MIS. These systems collect internal transaction data and external data to generate reports that support decision making, routine activities, planning, and control within each business function.
FinfraG: Opportunities & Challenges for Global Trading PlatformsCognizant
The Swiss Financial Market Infrastructure Act (FMIA), commonly known by its German name, FinfraG, spells out regulations for global derivative trading platforms and central clearing parties, including reporting, clearing, platform trading and risk mitigation. The act also incorporates laws pertaining to insider information/market abuse and shareholdings/public offers.
MIS is an information system that processes data into information. It uses transaction processing systems for input data and generates information that can be used for operations control, strategic planning, management control, and problem solving. There are several functional business areas of an MIS including accounting, human resources, inventory, manufacturing, and other areas. An accounting information system collects, records, and evaluates financial data and communicates it to management. It includes financial, management, and cost accounting systems. A MIS helps managers make timely and effective decisions by providing accurate data across various business functions.
The document discusses testing strategies for stock exchange and trading platforms. It outlines the key challenges in testing, including complex trading scenarios, compliance with regulations, and ensuring performance. It recommends developing test plans with different levels, including business process flows, test scenarios, and test cases. It emphasizes the importance of integration, performance, and failover/recovery testing given the critical need for low latency and high reliability. Finally, it stresses that thorough testing is crucial for stock exchanges to ensure their trading applications can handle increasing volumes, execute trades speedily, and safeguard investors.
This document discusses various financial securities and the role of information technology in stock exchanges. It describes common types of securities like stocks, mutual funds, and foreign currency. It then outlines the history of transaction documentation and discusses current stock exchange technologies like NEAT and BOLT that facilitate high-volume automated trading. The impacts of this change include increased transparency, efficiency and accountability for customers, industries and governments.
ICPAS Breakfast Talk Series - Maximising IT Audit 13 Mar 2013Barun Kumar
This document provides an overview of maximizing IT audits. It discusses planning IT audits by deciding the audit approach, identifying key IT application controls, and determining which IT general controls to test and testing frequency. It also covers executing IT audits by testing control design and operation and selecting samples. When analyzing results, it examines how to assess the impact of IT application control and IT general control deficiencies and whether alternative controls exist. The document emphasizes the importance of understanding interdependencies between different types of IT controls.
This document discusses how computers can be used for controlling business operations and decision making. It defines controlling as monitoring plan implementation and making corrections, and decision making as choosing the best solution from multiple alternatives. Computers are used for inventory management, presentations, communications and more. Transaction processing systems support data entry and record transactions. Management information systems collect and share management data. Decision support systems provide tools to aid management, operations, and planning decisions. Overall, computers make controlling and decision making faster and more effective for management.
Information system in business functions unit ivlaiprabhakar
This document discusses different types of management information systems (MIS) used in business functions like accounting, finance, manufacturing, marketing, and human resources. It provides details on the purpose and components of accounting information systems, financial MIS, manufacturing MIS, marketing MIS, and human resource MIS. These systems collect internal transaction data and external data to generate reports that support decision making, routine activities, planning, and control within each business function.
FinfraG: Opportunities & Challenges for Global Trading PlatformsCognizant
The Swiss Financial Market Infrastructure Act (FMIA), commonly known by its German name, FinfraG, spells out regulations for global derivative trading platforms and central clearing parties, including reporting, clearing, platform trading and risk mitigation. The act also incorporates laws pertaining to insider information/market abuse and shareholdings/public offers.
This document provides an introduction to data management. It discusses why data should be managed, including benefits like enabling verification, new research, and cost savings. It also covers topics like data entry and manipulation, quality control, and sharing data. Effective data management results in high quality, accessible data that can be cited, reused, and helps researchers gain recognition.
Un base de datos es un almacén que permite guardar y organizar grandes cantidades de información para que los usuarios puedan encontrar y usar los datos fácilmente. Un base de datos tiene características como independencia lógica y física de los datos, redundancia mínima, acceso concurrente por múltiples usuarios, integridad y seguridad de los datos, y consultas optimizadas. Un sistema de base de datos proporciona funciones para describir, manipular y utilizar los datos.
Vinay Kumar M is seeking a position in software architecture and computer security with a B.Tech in Computer Science from Jawaharlal university. He has experience with imperative programming languages and system frameworks. He is currently studying for a M.Tech in Nano Technology at Sreenidhi Institute of Science and Technology. Vinay has skills in Microsoft Visual Studio, Java, HTML, web technologies, Linux, networking, databases, and graphics. He has internship experience developing a GUI interface framework and multi-banking system. In his free time, Vinay engages in volunteer activities and holds a black belt in karate.
As Olimpíadas foram criadas pelos gregos há mais de 2.700 anos em Olímpia como forma de homenagear os deuses. As primeiras Olimpíadas modernas aconteceram em 1896 na Grécia e contaram com a participação de 13 países. Neste ano, o Brasil sediará os Jogos Olímpicos e receberá atletas de todo o mundo para competições como maratona, luta e salto em distância.
Gina Gould writes a letter of recommendation for Joel Watson to highlight his skills as a safety professional. She has worked with Joel for three months on an industrial construction site. Joel has shown knowledge of safety standards and regulations, and ensures his contracting company complies with requirements. He is willing and able to identify, address, and mitigate safety hazards. Joel spends time in the field and is approachable, so workers contact him with concerns. Gina is confident Joel will have a successful career in safety.
This document appears to be contact information for an autorided channel partner named Ashu Group located in India. It provides a phone number +91-7503367689 as the main point of contact.
Critical Success Factors Affecting Project Performance in Turkish IT Sector -...systred
The business contribution part of early findings of the research - presented in PMI EMEA Congress 2013 in Istanbul - that evaluated what do we understand from project success and the effect of success factors.
O documento fala sobre as férias escolares de julho e pede aos moradores que fiquem atentos às crianças nas áreas comuns, repassem as regras de uso e não descuidem da segurança do condomínio nesse período para evitar problemas.
Introduction to DCAM, the Data Management Capability Assessment ModelElement22
DCAM is a model to assess data management capability within the financial industry. It was created by the EDM Council. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239.
The environment of physical energy and non-energy commodity trading and marketing has grown increasingly complex, marked by globalization bringing about rapid changes in supply and demand patterns, increased regulatory scrutiny and evolving trading and reporting rules, volatility along the entirety of the physical supply chain, and increasing uncertainty as to future price movements. In order to react to these changes quickly and appropriately, participants in these markets must increasingly rely on a sophisticated infrastructure of software and technologies to ensure a complete view of their trading positions and external market conditions that can quickly and severely impact their values. The core component of these now requisite trading and marketing technologies are energy and commodity trading and risk management (CTRM) systems. As market complexity has increased and multi-commodity trading has become more common, CTRM solutions have had to become more sophisticated and provide a greater depth of capability in order to capture and value the unique characteristics of the multitude of physical commodities being transacted along the physical supply chain, from source to market. Given the capabilities of these CTRM systems, they do represent a significant investment for any trading or marketing organization, generally trailing only the large scale ERP solutions, like SAP, in terms of costs to purchase and implement. Allegro Development, one of the world’s largest CTRM solutions providers, engaged Commodity Technology Advisory to conduct a survey of a number of their clients to determine their views as to the value of their investment and the operational and financial impacts of deploying Allegro’s CTRM solution. This report summarizes the results of that survey and discusses the key considerations for any company seeking to develop their own assessment of the value of their CTRM technology investment via a Return on Investment (ROI) calculation.
The document discusses implementing a comprehensive ETRM (Energy Trading and Risk Management) system to provide a 360-degree view of trading and risk management activities. It outlines how ETRM systems have become more sophisticated over time to meet evolving needs. Key aspects of a successful ETRM implementation include defining clear business requirements, evaluating existing systems and processes, selecting appropriate software, and implementing in a phased approach with user acceptance testing. Consulting firm PA provides expertise to help companies with all stages of ETRM system selection and implementation.
Transaction processing systems carry out the processes involved in organizational transactions, such as exchanging goods or services for payment. They have certain key properties to ensure transactions are properly processed, including being atomic, consistent, isolated, and durable (ACID properties). Transaction processing can occur through either batch processing, where data is collected and updated later in batches, or real-time processing, where updating occurs immediately. Proper data validation, storage and retrieval, as well as backup procedures, are important components of transaction processing systems. Issues related to these systems include the changing nature of work, potential for bias, and ensuring data security, accuracy and integrity.
Trading has changed from local to global and so have the processes from paper to Online. The result is change in process from T+3 to T+1 and real time trading and settlement of a trade.
The document discusses the role of information technology (IT) in supply chain management. It makes several key points:
1) Information is crucial to supply chain performance as it allows processes and decisions to be coordinated across the supply chain.
2) IT consists of the hardware, software, and people that gather, analyze and use information to help management make decisions.
3) Successful companies like Amazon and Walmart rely on the availability and analysis of supply chain information.
The document then goes on to describe frameworks for IT in areas like customer relationship management, internal supply chain management, and supplier relationship management. It also discusses principles of supply chain information and how IT can help with integration.
A transaction processing system (TPS) collects, stores, modifies, and retrieves business transaction data. TPS are designed to efficiently process high volumes of routine transactions like reservations, payments, and account processing. Transactions represent business activities like orders, payments, and invoices. Early systems like SABRE processed thousands of transactions daily. For a system to qualify as a TPS, transactions must pass the ACID test ensuring atomicity, consistency, isolation, and durability. Key features of TPS include rapid response, continuous availability, data integrity, and ease of use.
The document discusses regulatory requirements for trade reporting and monitoring from FINRA, NASDAQ, and other agencies. It covers requirements around accepting trades within 20 minutes on NASDAQ, reporting trades to the Order Audit Trail System (OATS) according to specific data elements and timestamps. FINRA can measure compliance for OATS and TRACE (Trade Reporting and Compliance Engine) based on metrics like late submissions and unmatched reports. The document also provides an example audit approach and discusses direct market access (DMA) tools, associated risks, and evolving governance/regulations.
ConceptOne - Whitepaper - Achieving Regulatory Alpha Through Regulatory Risk ...Gary S. Kaminsky
This document summarizes a whitepaper on achieving regulatory compliance through implementing a robust Regulatory Enterprise Risk Management (RegERM) system. It discusses the increased global regulatory requirements asset managers now face. It recommends managers focus on regulatory compliance costs rather than just direct compliance costs. The document outlines key components of an effective RegERM system, including consolidating data from multiple sources, transforming the data for reporting requirements, and electronically transmitting reports. It emphasizes the importance of coordination among service providers, technology, and regulatory advisors to streamline the reporting process.
This presentation summarizes the investment strategy, risk management practices, and performance of a commodity trading advisor (CTA). The CTA uses systematic trading programs developed through extensive research testing multiple algorithms over many years of market data. Portfolios are diversified across over 40 global futures markets and risk is controlled through stop losses on all trades and adjusting position sizes based on volatility. While past performance is not indicative of future results, the CTA has achieved annualized returns of over 16% since inception with balanced winning and losing months.
This document provides an introduction to data management. It discusses why data should be managed, including benefits like enabling verification, new research, and cost savings. It also covers topics like data entry and manipulation, quality control, and sharing data. Effective data management results in high quality, accessible data that can be cited, reused, and helps researchers gain recognition.
Un base de datos es un almacén que permite guardar y organizar grandes cantidades de información para que los usuarios puedan encontrar y usar los datos fácilmente. Un base de datos tiene características como independencia lógica y física de los datos, redundancia mínima, acceso concurrente por múltiples usuarios, integridad y seguridad de los datos, y consultas optimizadas. Un sistema de base de datos proporciona funciones para describir, manipular y utilizar los datos.
Vinay Kumar M is seeking a position in software architecture and computer security with a B.Tech in Computer Science from Jawaharlal university. He has experience with imperative programming languages and system frameworks. He is currently studying for a M.Tech in Nano Technology at Sreenidhi Institute of Science and Technology. Vinay has skills in Microsoft Visual Studio, Java, HTML, web technologies, Linux, networking, databases, and graphics. He has internship experience developing a GUI interface framework and multi-banking system. In his free time, Vinay engages in volunteer activities and holds a black belt in karate.
As Olimpíadas foram criadas pelos gregos há mais de 2.700 anos em Olímpia como forma de homenagear os deuses. As primeiras Olimpíadas modernas aconteceram em 1896 na Grécia e contaram com a participação de 13 países. Neste ano, o Brasil sediará os Jogos Olímpicos e receberá atletas de todo o mundo para competições como maratona, luta e salto em distância.
Gina Gould writes a letter of recommendation for Joel Watson to highlight his skills as a safety professional. She has worked with Joel for three months on an industrial construction site. Joel has shown knowledge of safety standards and regulations, and ensures his contracting company complies with requirements. He is willing and able to identify, address, and mitigate safety hazards. Joel spends time in the field and is approachable, so workers contact him with concerns. Gina is confident Joel will have a successful career in safety.
This document appears to be contact information for an autorided channel partner named Ashu Group located in India. It provides a phone number +91-7503367689 as the main point of contact.
Critical Success Factors Affecting Project Performance in Turkish IT Sector -...systred
The business contribution part of early findings of the research - presented in PMI EMEA Congress 2013 in Istanbul - that evaluated what do we understand from project success and the effect of success factors.
O documento fala sobre as férias escolares de julho e pede aos moradores que fiquem atentos às crianças nas áreas comuns, repassem as regras de uso e não descuidem da segurança do condomínio nesse período para evitar problemas.
Introduction to DCAM, the Data Management Capability Assessment ModelElement22
DCAM is a model to assess data management capability within the financial industry. It was created by the EDM Council. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239.
The environment of physical energy and non-energy commodity trading and marketing has grown increasingly complex, marked by globalization bringing about rapid changes in supply and demand patterns, increased regulatory scrutiny and evolving trading and reporting rules, volatility along the entirety of the physical supply chain, and increasing uncertainty as to future price movements. In order to react to these changes quickly and appropriately, participants in these markets must increasingly rely on a sophisticated infrastructure of software and technologies to ensure a complete view of their trading positions and external market conditions that can quickly and severely impact their values. The core component of these now requisite trading and marketing technologies are energy and commodity trading and risk management (CTRM) systems. As market complexity has increased and multi-commodity trading has become more common, CTRM solutions have had to become more sophisticated and provide a greater depth of capability in order to capture and value the unique characteristics of the multitude of physical commodities being transacted along the physical supply chain, from source to market. Given the capabilities of these CTRM systems, they do represent a significant investment for any trading or marketing organization, generally trailing only the large scale ERP solutions, like SAP, in terms of costs to purchase and implement. Allegro Development, one of the world’s largest CTRM solutions providers, engaged Commodity Technology Advisory to conduct a survey of a number of their clients to determine their views as to the value of their investment and the operational and financial impacts of deploying Allegro’s CTRM solution. This report summarizes the results of that survey and discusses the key considerations for any company seeking to develop their own assessment of the value of their CTRM technology investment via a Return on Investment (ROI) calculation.
The document discusses implementing a comprehensive ETRM (Energy Trading and Risk Management) system to provide a 360-degree view of trading and risk management activities. It outlines how ETRM systems have become more sophisticated over time to meet evolving needs. Key aspects of a successful ETRM implementation include defining clear business requirements, evaluating existing systems and processes, selecting appropriate software, and implementing in a phased approach with user acceptance testing. Consulting firm PA provides expertise to help companies with all stages of ETRM system selection and implementation.
Transaction processing systems carry out the processes involved in organizational transactions, such as exchanging goods or services for payment. They have certain key properties to ensure transactions are properly processed, including being atomic, consistent, isolated, and durable (ACID properties). Transaction processing can occur through either batch processing, where data is collected and updated later in batches, or real-time processing, where updating occurs immediately. Proper data validation, storage and retrieval, as well as backup procedures, are important components of transaction processing systems. Issues related to these systems include the changing nature of work, potential for bias, and ensuring data security, accuracy and integrity.
Trading has changed from local to global and so have the processes from paper to Online. The result is change in process from T+3 to T+1 and real time trading and settlement of a trade.
The document discusses the role of information technology (IT) in supply chain management. It makes several key points:
1) Information is crucial to supply chain performance as it allows processes and decisions to be coordinated across the supply chain.
2) IT consists of the hardware, software, and people that gather, analyze and use information to help management make decisions.
3) Successful companies like Amazon and Walmart rely on the availability and analysis of supply chain information.
The document then goes on to describe frameworks for IT in areas like customer relationship management, internal supply chain management, and supplier relationship management. It also discusses principles of supply chain information and how IT can help with integration.
A transaction processing system (TPS) collects, stores, modifies, and retrieves business transaction data. TPS are designed to efficiently process high volumes of routine transactions like reservations, payments, and account processing. Transactions represent business activities like orders, payments, and invoices. Early systems like SABRE processed thousands of transactions daily. For a system to qualify as a TPS, transactions must pass the ACID test ensuring atomicity, consistency, isolation, and durability. Key features of TPS include rapid response, continuous availability, data integrity, and ease of use.
The document discusses regulatory requirements for trade reporting and monitoring from FINRA, NASDAQ, and other agencies. It covers requirements around accepting trades within 20 minutes on NASDAQ, reporting trades to the Order Audit Trail System (OATS) according to specific data elements and timestamps. FINRA can measure compliance for OATS and TRACE (Trade Reporting and Compliance Engine) based on metrics like late submissions and unmatched reports. The document also provides an example audit approach and discusses direct market access (DMA) tools, associated risks, and evolving governance/regulations.
ConceptOne - Whitepaper - Achieving Regulatory Alpha Through Regulatory Risk ...Gary S. Kaminsky
This document summarizes a whitepaper on achieving regulatory compliance through implementing a robust Regulatory Enterprise Risk Management (RegERM) system. It discusses the increased global regulatory requirements asset managers now face. It recommends managers focus on regulatory compliance costs rather than just direct compliance costs. The document outlines key components of an effective RegERM system, including consolidating data from multiple sources, transforming the data for reporting requirements, and electronically transmitting reports. It emphasizes the importance of coordination among service providers, technology, and regulatory advisors to streamline the reporting process.
This presentation summarizes the investment strategy, risk management practices, and performance of a commodity trading advisor (CTA). The CTA uses systematic trading programs developed through extensive research testing multiple algorithms over many years of market data. Portfolios are diversified across over 40 global futures markets and risk is controlled through stop losses on all trades and adjusting position sizes based on volatility. While past performance is not indicative of future results, the CTA has achieved annualized returns of over 16% since inception with balanced winning and losing months.
Kermit is an analytics platform that provides real-time data on implantable medical device transactions to surgeons, supply chain personnel, and executives. It allows teams to access reports and audits in real-time from anywhere. Executives can get accurate views of profitability and issues. Consultative experts are available to help uncover opportunities to improve quality care and save millions. Kermit provides the tools needed to reduce costs and improve margins under new bundled payment programs through detecting upcharging and providing foundational analytics.
- Modern market surveillance should be able to monitor multiple exchanges and asset classes in real-time, handle large volumes of structured and unstructured data, discover patterns of potential market abuse, and support the full surveillance investigation and enforcement lifecycle.
- Typical surveillance products are limited in their ability to handle large amounts of data, integrate human and machine intelligence, focus only on structured data, and connect to the full surveillance process.
- A comprehensive surveillance solution is proposed that can monitor real-time trading at high speeds, analyze both structured and unstructured data, statistically detect patterns of abuse, and help identify relationships across complex data.
Why You Should Prioritize Third Party Risk Management (TPRM) in Today's Marke...Resolver Inc.
Did you know that 63% of data breaches are linked to third party access, and this number is on the rise? This presentation explores the increasing priority of Third Party Risk Management (TPRM) in today’s marketplace. Learn why TPRM should play a critical role in your overall Corporate Risk Management Strategy and best practices for how to implement a successful TPRM program in your own organization.
Performance measurement and exception management in investment processingNIIT Technologies
This document provides an overview of NIIT Technologies' performance measurement and exception management solution for investment processing. It discusses the challenges of straight-through processing for financial transactions due to increasing volumes, complex products, and regulatory requirements. The solution captures all incidents and exceptions during trade processing, classifies and enriches the data with reasons, generates reports to analyze performance on metrics like accuracy and productivity, and provides dashboards to view the information. NIIT Technologies has experience implementing this solution for large financial clients to improve operational efficiency and meet service level agreements.
Market data providers distribute real-time trade-related data from global markets, including prices, quotes, and volumes on stocks, indices, forex and commodities. This data is used by traders to assess asset values and inform trade decisions. While the timely delivery of market data is important for trading, latency issues can sometimes occur when distributing data from venues worldwide.
This document provides an overview of information technology management in supply chain operations, using Walmart as a case study. It discusses key concepts like traditional vs integrated supply chain views, the importance and benefits of IT in supply chain management. It also describes various types of IT systems used in supply chains, including ERP, transportation management, inventory management, EDI, barcoding, RFID and e-commerce systems. Finally, it discusses management of supply chain information systems and the development process.
Taming the regulatory tiger with jwg and smartlogicAnn Kelly
From CEOs to board members to operational managers, regulatory compliance is an ongoing concern. In a rapidly changing marketplace where complex regulations come from multiple regulatory bodies, the consequences of non-compliance can be costly to the enterprise in time, money and damage to their reputation.
JWG, a London think tank, has created RegDelta – a state-of-the-art regulatory change management platform - that allows individual stakeholders to quickly understand the impact of regulations and maintain a single source of truth for their regulatory obligations.
Hear Elliot Burgess, Head of Product and Client Services at JWG and Paul Gunstone, Sales Director at Smartlogic discuss the challenges organizations face identifying and complying with relevant regulations, JWG’s approach to taming the regulatory tiger with semantics and see a demo of the JWG RegDelta platform.
Keeping up with Sec T+1 Settlement Cycle!Emily Jones
Magic FinServ delves into the transition from the previous SEC T+2 Settlement Cycle to the current SEC T+1 Settlement Cycle and discusses its implications for investors and market participants. It highlights the advantages of the shorter settlement period, such as reduced risk and improved operational efficiency.
This document provides an overview of robotic process automation (RPA) in finance, including key areas where RPA can be applied and benefits realized. It discusses popular adoption methods, examples of processes that are good candidates for RPA in banking, capital markets, and insurance. The document also outlines a strategy for developing an RPA program, including assessing automation opportunities, building a business case, determining the operating model, identifying partners, and planning the roadmap. Benefits of RPA include increased productivity, accuracy, scalability, compliance, business continuity, and cost savings.
A multi-cloud strategy offers hardware, software, and infrastructure redundancy that optimizes fault tolerance and allows traffic to be steered through the fastest parts of the network. Different clouds perform better for different tasks, such as handling many small requests or fewer large requests. A multi-cloud approach prevents failures from causing significant service disruption by distributing services across multiple cloud providers. While storage is fragmented across providers, segregating file types to specific clouds makes files easily findable.
Cognitive analytics aims to emulate the human brain's abilities for perception, action, and cognition. It relies on machine learning, natural language processing, and distributed computing to analyze large and complex data in real time. Unlike traditional analytics which uses predefined rules, cognitive analytics generates hypotheses from a variety of relevant information and improves as more data is processed. While still developing, cognitive analytics has potential to gain insights from data in new ways that were previously impossible by learning from experience like humans. However, most companies currently only use basic descriptive analytics.
The document discusses nurturing a data-driven culture in organizations. It notes that while many businesses say they want to be more data-driven, actually making the transition can be challenging. A data-driven culture means putting data and insights into the hands of front-line staff across the organization to power fact-based decisions. The document outlines several challenges to creating a successful data-driven culture, such as examining infrastructure to support effective data use, ensuring buy-in and commitment, fostering professional development, leading by example, establishing regular data meetings, and removing barriers to expansion.
The document discusses strategies for effective collaboration between IT and business teams. It recommends that IT teams focus on solving business problems rather than users' envisioned solutions, divide work based on user stories instead of developer specialties, and provide working demos each sprint to validate requirements. It also suggests implementing "walk-in" hours for developers to interact with business users to clarify assumptions and synchronize with business needs. Modeling complex business rules together with business users can help ensure solutions meet both functional and technical requirements.
Commodity trading and risk management functions are critical for business performance, but many companies fail to adequately define their data and information architecture to support these functions. A robust data architecture is needed to determine the required systems configuration to deliver timely, accurate, and relevant data to front, middle, and back office staff. Additionally, commodity trading and risk management systems often fail to efficiently handle market data, lack expertise in big data and analytics, and have opaque forward curve building methodologies, undermining returns on investment. Integrating third-party applications for these missing capabilities can be worthwhile despite additional costs.
Application integration has become more vital as companies transition to digital models and information is shared across employees, suppliers, and customers. An integration strategy involves coordinating workflows and components between applications. Integration provides benefits like increased automation, scalability, customer service, and data accuracy across systems. However, gaining stakeholder buy-in can be challenging as integration is less exciting than new applications and requires optimizing existing systems.
2. CTRM/ETRM- THE SCORECARD
• Physical position reports for each location and commodity including
long and short status. (Position reports may be for current and
forward time periods.).
• Estimated profit and loss on completed transactions and processes
forecast present and future cash flows •
• Price risk exposure associated with current and forward positions •
• Credit risk exposure associated with current and forward positions •
• Operational risk exposure •
• Information required for regulatory compliance in areas such as
financial accounting, futures, exchange activity, price transaction
reporting, and government reporting.
3. THE SCORECARD DEPENDENCY-ON MARKET DATA
• ETRM system effectiveness depends on
accurate and timely reporting and market
information. Successful ETRM utilization
involves effective reporting and analysis to
navigate and improve trading performance.
4. The ETRM /CTRM system is a trading organization’s scorecard-Report
• Physical position reports for each location and commodity including long
and short status.
• (Position reports may be for current and forward time periods.)
• Estimated profit and loss on completed transactions and processes •
• Forecast present and future cash flows •
• Price risk exposure associated with current and forward positions •
• Credit risk exposure associated with current and forward positions •
• Operational risk exposure •
• Information required for regulatory compliance in areas such as financial
accounting, futures •
• Exchange activity, price transaction reporting, and government reporting.
5.
6. ETRM/CTRM-DATA CHALLANGES
• Maintaining up to date market data overtime
and adding it to when needed is a significant
challenge for ETRM/CTRM sys-admin.
• Unexpected data changes.
• Market data provider supplies a correlation to
a previously published rate , the ETRM system
has to recognize the exception. In many cases
ETRM system finds it difficult to handle.
7. Data aggregator
CTRM/ETRM –Transaction life cycle
Capturing infrastructure, contracts and
counterparties
Pre-deal analysis
Deal capture
Scheduling operations and logistics
Risk analysis.
Settlement and Invoicing.
Market data
All commodity transactions companies would ultimately will require the
service of an external Data aggregation services to handle multi-
commodity, multi-source and multi-format market data.
8. External data dependency
Where trading is conducted with an exchange
rather than a company, exchange commodity
details and contracts have to be captured. These
include contract termination dates and delivery
timing, as well as broker intermediary details.
The quantity of information to be captured and
entered into the ETRM system before a
transaction occurs varies widely with the
business profile of the trading company.
Capturing infrastructure,
contracts and counterparties
9. External data dependency
Before executing a trade and entering the transaction into
the ETRM system, pre-deal analysis is usually performed.
Traders analyze current market prices and fundamentals to
identify optimal timing and pricing mechanisms for the
trade. Data requirements for pre-deal analysis, in particular
access to historical market prices and fundamental
information such as storage and weather data, are not well
served in ETRM/CTRM systems. Instead, analysts typically
use outside software tools that contain broader market
information. Access to market data within ETRM systems is a
challenge because the system tends to contain only the
market data needed to manage existing trades.
Pre-deal analysis
10. External data dependency
Deal capture includes all relevant transaction details. Typical
details might include trade number, quantity, commodity,
units of measure, counterparty, contract, delivery timing,
buy or sell, location, financial or physical, trader name, price
mechanism, transaction frequency, and link to other trades.
Data management challenges arise when deal volume is
high and errors in the details creep into the ETRM system,
even with automation. Deal entry errors are time consuming
to fix, render the scorecard inaccurate and threaten ETRM
system integrity.
Deal capture
11. External data dependency
Scheduling logistics require data interaction (often on paper)
with third-party transportation systems. Without up-to-date
scheduling and logistics information, the ETRM scorecard
cannot present accurate position reports to management.
The data management challenge in scheduling and logistics
is capturing data from third-party transportation,
processing, and scheduling systems. Data may not be
available in a timely fashion, and changes or corrections to
volumetric measures may occur without notice.
Scheduling operations and
logistics
13. Market data management best practices
• Use straight-throughput processing and
automation to eliminate manual efforts •
• Reduce data feeds to a minimum •
• Ensure timely data updates •
• Perform pro-active data quality control •
• Maintain audit trails of data changes and track
corrections •
• Manage data permissions to ensure data
integrity
14. Pre-deal Analysis
• Traders analyze especially historical data.
• Manages only market data required for the
trade as against the broader market
information.
Pre-deal analysis
15. Deal capture
• Errors in the details creep into the ETRM
system even with automation for high deal
volume. Deal entry errors are time consuming
to fix, render the scorecard inaccurate and
threaten ETRM system integrity.
Deal capture
Data from third party transportation , processing and scheduling systems poses a quite a challenge
for the ETRM sys-admin.
16. Risk management
RISK MANAGEMENT
1. Market risk(price risk).
2. Operational risk.
3. Counterparty risk.
4. Regulatory risk.
•Market data to manage market risk is primarily pricing. Generating daily forward curve
prices from market data (mark to market) –Risk reporting.
•A forward curve for each forward position in the trading portfolio.
•Many commodities and in particular for periods further out into the future , no market
data is available .
RISK MANAGEMENT CHALLENGES
Market data from multiple
sources
Data often poorly
organized
Data requires
Further
massaging
ETRM
Forward curve- built
outside
SOLUTION
VAR calculation is data intensive where they use simulation method
Data manipulation in excel
18. Counter party –credit risk
•Market data from credit rating agencies.
•Financial reports.
Third party data collection.
Challenges
Note : Clearing houses removes counter party credit risk but incur overhead cost to manage the clearing process
And meet daily margin calls.
19. Regulatory risk
• To comply with regulation, it is necessary to
understand where outside data originates and
track any changes occurring en-route to
ETRM.
Access to original set of data is an important advantage in this process.
20. Associated contract
Trading
infrastructure
CTRM/ETRM- transaction life cycle
ETRM
Data set-up
Market data
Data
Aggregator
Transaction life cycle
CONTRACTS
Credit limit
Qty
Price
Delivery
Standard contracts derived from International swaps and derivatives association (ISDA). North
America energy standard boards (NAESB).
21. Best practices of market data management
• Use straight-through processing.
• Reduce data feeds to minimum.
• Ensure timely data updates are available.
• Pro-active data quality control.
• Maintain audit trails of data changes and track
corrections.
• Manage data permissions.
22. In a era of “Free fall of crude oil prices , “cost management” has become the priority for energy companies /traders
Scope of cost optimizationCost centers
1.Product and commercial cost 1.Reduce number of product approvals.
2.Streamline portfolio (product overlapping
activities).
3.Standardize front office set up /systems.
2.Support cost(including control
requirements)
1.Reduce control and reporting
requirements by way of maximum
automation.
2.Streamline trade process and increase end
to end automation.
3.Consolidate functions and evaluate near
off shoring and outsourcing
3.Information and Technology Cost
1.Eliminate high cost /low benefit projects.
2.Streamline application landscape.
4.Location Cost
1.Optimize location set-up/spread of
departments.
2.Increase building utilization.