CPCU 500 Lecture Book Managing Evolving Risks
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
CPCU 500 Lecture Book Managing Evolving Risks 2021 Edition 1
Section 1. Embracing Risktec Topic 1. The Risktech Ecosyste 1 1.a. Traditional Risk Assessment Techniques and Big Dat 1 1.b. Data Captur 1 1.c. Data Storag 1 1.d. Data Analytic 1 1.e. Risktec 1 1.f. New Technologies to Risk Managemen 1 1.g. Preventive Analytic 1 1.h. Connected Ecosystem 1 1.1. Question: The Risktech Ecosyste 1 Topic 2. Emerging Technologies, Smart Products, and Operation 1 2.a. Arti cial intelligence (AI 1 2.b. Sensors/Sensor Networ 1 2.c. Digital Twi 1 2.d. Computer Visio 1 2.e. Smart Product 1 2.f. Smart Operation 1 2.1. Question: Emerging Technologies, Smart Products, and Operation 2 Section 2. Creating a Stronger RM Foundatio Topic 3. Risk Management Process and Classi cations of Ris 2 3.a. Concept of Risk Management Proces 2 3.b. Process for Managing Ris 2 3.c. Scan the Environmen 2 3.d. Identify Risk 2 3.e. Classi cations of Ris 2 3.f. Pure and Speculative Ris 2 3.g. Subjective and Objective Ris 2 3.h. Diversi able and Nondiversi able Ris 2 3.i. Quadrants of Risk: Hazard, Operational, Financial, and Strategi 2 2 k fi fi 4 h fi s 4 n e e s s 2 8 s 7 n s 2 3 9 6 s k t s 5 8 9 k k ) k 5 7 6 7 k fi 7 5 7 m 8 s m h k t 6 4 4 8 2 a 2 fi n c s 9 1
3.1. Question: Classi cations and Categories of Ris 3 Topic 4. Risk Management Objectives, Bene ts, and Basic Measure 3 4.a. Risk Management Objective 3 4.b. Tolerable Uncertaint 3 4.c. Pro tability and Growt 3 4.d. Reduced Deterrent Effects of Hazard Risk 3 4.e. Basic Risk Measure 3 4.1. Question: Risk Management Objectives, Bene ts, and Basic Measure 3 Section 3. Identifying and Analyzing Costly Risk Topic 5. Holistic Risk Identi catio 3 5.a. The Holistic Approach to Identifying Risk 3 5.b. De ning Enterprise-Wide Risk 3 5.c. Technology’s Effect on Holistic Risk Managemen 3 5.d. Measuring Risk Variable 3 5.e. Risk Identi cation as a Tea 4 5.f. Facilitated Workshop 4 5.g. Delphi Techniqu 4 5.h. Scenario Analysi 4 5.1. Question: Holistic Risk Identi catio 4 Topic 6. Introduction to Risk Analysi 4 6.a. The Nature of Risk Analysi 4 6.b. Qualitative and Quantitative Analysi 4 6.c. Assessing Control 4 6.d. Traditional Accident Analysi 4 6.e. Sequence of Events (Domino Theory 4 6.f. Energy Transfer Theor 4 6.g. Technique of Operations Review (TOR) Approac 4 6.h. Change Analysi 4 6.i. Job Safety Analysi 4 6.1. Question: Introduction to Risk Analysi 4 Topic 7. Root Cause Analysi 5 3 fi fi s 2 fi s fi e s s s 8 s y s y 5 1 2 6 8 h s 3 4 1 7 m s s s fi 2 9 0 5 s fi s 8 6 n ) s s 3 7 1 n s s 5 9 fi s k 4 8 8 h t 0 8 5 fi 8 s s 6
7.a. Apply the root cause analysis process 5 7.b. The Nature of Root Cause Analysi 5 7.c. Root Cause Analysis Approache 5 7.d. Steps in the Root Cause Analysis Proces 5 7.e. Root Cause Analysis Exampl 5 7.1. Question: Root Cause Analysi 5 Section 4. Leveraging Tech and Insuranc Topic 8. Risk Treatmen 5 8.a. Risk Treatment Proces 5 8.b. Risk Treatment Technique 5 8.c. The Prouty Approac 5 8.d. Developing a Risk Treatment Pla 5 8.e. Technology’s Impact on Risk Modi catio 5 8.f. Technology’s Impact on Risk Transfe 5 8.g. Insurers Embrace Io 6 8.h. Technology’s Impact on Financial Transaction 6 8.1. Question: Risk Treatmen 6 Topic 9. Risk Treatment Application 6 9.a. Hazard Risk: Creating a New Produc 6 9.b. Operational Risk: Data Breac 6 9.c. Financial Risk: Extending Credit to Customer 6 9.d. Strategic Risk: Entering a New Marke 6 9.e. Insurance as a Risk Management Techniqu 6 9.f. Insurable Risks and Loss Exposure 6 9.g. Ability to Meet Risk Financing Goal 6 9.1. Question; Risk Treatment Application 6 9.2. Question; Insurance as a Risk Management Techniqu 6 Topic 10. Noninsurance Contractual Risk Transfer and Large Deductible Plan 7 10.a. Noninsurance Transfers for Risk Contro 7 10.b. Leasin 7 10.c. Contracting for Service 7 4 g 0 T h s s t s s 6 8 0 1 1 t e h s 7 6 0 s n s s 2 3 4 3 fi s r t . s t 1 9 9 7 8 s n l e 1 2 2 5 9 0 s s s 9 6 2 0 4 e e 9
10.d. Waiver, Exculpatory Clause, and Disclaimer of Warrantie 7 10.e. Hold-harmless Agreement 7 10.f. Purpose and Operation of Large Deductible Plan 7 10.g. Operation of a Large Deductible Pla 7 10.h. Large Deductible Versus Self-Insured Retentio 7 10.i. Use of Large Deductible Plan 7 10.j. Bene ts of Large Deductible Plan 7 10.k. Ability to Meet Risk Financing Goal 7 10.1. Question: Noninsurance Contractual Risk Transfe 7 10.2. Question: Large Deductible Plan 7 Section 5. Preparing for Hazard Topic 11. Sources of Property Ris 7 11.a. Natural Risk Source 7 11.b. Human Risk Source 7 11.c. Natural Disaster Loss Contro 7 11.d. Windstor 7 11.e. Tornad 7 11.f. Earthquak 8 11.g. Floo 8 11.1. Question: Sources of Property Ris 8 Topic 12. Life Safety and Valuing Physical Propert 8 12.a. Life Safet 8 12.b. Human Characteristic 8 12.c. Building Occupancie 8 12.d. Fire Safety Standard 8 12.e. Valuing Physical Propert 8 12.f. Book Valu 8 12.g. Replacement Cos 8 12.h. Market Valu 8 12.i. Economic Valu 8 12.1. Question: Life Safet 8 12.2. Question: Valuing Physical Propert 8 5 fi d o 0 y m e e e 9 9 0 2 6 e 7 7 t y s s s s 6 s y 8 8 3 4 5 8 s s l 2 5 s s k 3 8 y s n 4 6 1 9 k s 3 4 8 n s r 3 2 5 s y 1 2
Topic 13. Management Liability and Human Resource Ris 9 13.a. Management Liability Ris 9 13.b. Directors and Of cers Liabilit 9 13.c. Treatment for Directors and Of cers Risk 9 13.d. Risk Related to Employment Practice 9 13.e. Risks Related to Fiduciary Dutie 9 13.f. Human Resource Ris 9 13.g. Assessing Human Resource Ris 9 13.h. Treating Human Resource Ris 9 13.1. Question: Management Liabilit 9 13.2. Question: Human Resource Ris 9 Section 6. Uncovering Operational Risk Topic 14. Operational Risk Categories and Indicator 10 14.a. Operational Risk Categorie 10 14.b. Strategies to Mitigate People Ris 10 14.c. Reduction of Operational Risk Through Blockchai 10 14.d. External Event 10 14.e. Operational Risk Indicator 10 14.f. Risk Indicators by Operational Risk Clas 10 14.g. Exposure Indicators and Control Indicator 10 14.h. Relating Indicators and Outcome 10 14.1. Question: Operational Risk Categorie 10 14.2. Question: Operational Risk Indicator 10 Topic 15. Self-Assessing Operational Risk and Emerging Technolog 10 15.a. Self-Assessing Operational Ris 10 15.b. Risk Assuranc 10 15.c. Control Risk Self-Assessment (CRSA 10 15.d. Risk Management Monitoring and Reportin 10 15.e. Emerging Technology and Operational Ris 11 15.f. Blockchain Technolog 11 6 0 y e s 8 fi 2 8 k y 4 k 0 s s 0 y k k 0 3 fi y k k s k s 1 5 6 8 ) s s s 3 4 7 1 5 s s 2 s k 6 7 9 g 1 0 4 5 n 9 s 2 s 0 k
15.g. Robotic Process Automation and Operational Ris 11 15.1. Question: Self-Assessing Operational Ris 11 15.2. Question: Operational Risk and Emerging Technolog 11 Section 7. Making Sense of Financial Ris Topic 16. Types of Financial Risk and Securitizatio 11 16.a. Types of Financial Ris 11 16.b. Securitizatio 11 16.c. Special Purpose Vehicl 11 16.d. Income-Producing Assets and Securitization Mode 11 16.1. Question: Types of Financial Risk and Securitizatio 11 Topic 17. Assessing a Balance Shee 12 17.a. Balance Shee 12 17.b. Assets: Balance Shee 12 17.c. Liabilities: Balance Shee 12 17.d. Shareholders' Equity: Balance Shee 12 17.e. Liquidity Ratio 12 17.f. Leverage Ratio 12 17.1. Question: Assessing a Balance Shee 12 Section 8. Optimizing Risk for Strategic Advantag Topic 18. Strategic Risk and Managemen 12 18.a 12 18.b. Strategic Risk Factor 12 18.c. Assessing Strategic Ris 12 18.d. Strategic Managemen 12 18.e. SWOT, PESTLE, and Porter’s Five Forces Analysi 13 18.1. Question: Strategic Risk and Managemen 13 Topic 19. Applying Strategic Risk Managemen 13 19.a. Risk and Strateg 13 19.b. Incorporating Risk Into Strateg 13 19.c. Meeting Strategic Goal 13 19.d. Strategic Management Proces 13 7 . 6 n t s s y 7 0 2 3 t s k t e 3 k s t 6 7 1 7 8 9 5 s 1 y 4 5 t t 1 4 k t t 2 1 0 k s t n l y k 1 8 9 0 6 t 3 n 3 e 6
19.e. Risk Appetite and Risk Toleranc 13 19.f. Risk Assessmen 13 19.g. Risk Contro 13 19.1. Question: Applying Strategic Risk Managemen 13 Section 9. Breaking Down Risk Modelin Topic 20. Probability Analysi 14 20.a. Nature of Probabilit 14 20.b. Law of Large Number 14 20.c. Probability Distributio 14 20.d. Central Tendency and Dispersio 14 20.e. Normal Distributio 14 20.f. Practical Application of Normal Distributio 14 20.1. Question: Probability Analysi 14 Topic 21. Value at Risk and Trend Analysi 14 21.a. Value at Ris 14 21.b. Earnings at Ris 15 21.c. Trend Analysi 15 21.d. Charting a Linear Regression Lin 15 21.e. Analyzing Event Consequence 15 21.f. Decision Tree Analysi 15 21.g. Event Tree Analysi 15 21.1. Question: Value at Risk and Trend Analysi 15 Section 10. Diving Into Dat Topic 22. Big Data and Traditional Data Analysi 15 22.a. Big Data Characteristic 15 22.b. Internal and External Dat 15 22.c. Structured and Unstructured Dat 16 22.d. Traditional Data Analysi 16 22.e. Common Data Analysis Technique 16 22.f. Exploratory Data Analysi 16 22.g. Classi cation Tree 16 8 fi k l s k t s 7 9 1 s n y s s n 7 0 4 4 s s s a 0 1 2 5 3 8 s s 9 1 3 e n a e s a s 8 3 6 4 2 0 2 0 s n 7 5 t s 8 g 9 s 8
22.h. Cluster Analysi 16 22.1. Question: Big Data and Traditional Data Analysi 16 Topic 23. Modern Data Analysis and Data-Driven Decision Makin 16 23.a. Modern Data Analysi 16 23.b. Text Minin 16 23.c. Neural Network 16 23.d. Social Network Analysi 16 23.e. Data Science and Data-Driven Decision Makin 16 23.f. A Model for Data-Driven Decision Making in Risk Managemen 16 23.1. Question: Modern Data Analysis and Data-Driven Decision Makin 17 Section 11. Building Consensu Topic 24. Communicating and Collaborating About Ris 17 24.a. Fundamentals of Effective Communicatio 17 24.b. The Communication Proces 17 24.c. Delivering Dif cult Message 17 24.d. Active Listenin 17 24.e. Communicating and Collaborating About Ris 17 24.1. Question: Communicating and Collaborating About Ris 17 Topic 25. Collaborating With Experts About Risk and Delivering Your Messag 17 25.a. The Importance of Collaboration in Risk Managemen 17 25.b. Motivate Worker 17 25.c. Collaborating With Experts About Ris 17 25.d. Delivering Your Messag 17 25.e. Convey Nonverbal Message and Lead Effective Meeting 17 25.f. Resolve Common Problem 17 25.1. Question: Collaborating With Experts About Risk and Delivering Your Messag 180 9 2 e g 6 g fi g s s s 6 s 4 7 3 7 s e s 6 e s s 8 8 9 2 3 7 k s n 8 k g 2 s 9 4 t 5 k s 7 t 5 9 g 9 k 0
10
SECTION 1. EMBRACING RISKTECH Topic 1. The Risktech Ecosyste Topic 2. Emerging Technologies, Smart Products, and Operation 11 m s
Section 1. Embracing Risktech Topic 1. The Risktech Ecosyste Reference: CPCU 500 Online 1st edition, Assignment 1. Module 1, 1.a. Traditional Risk Assessment Techniques and Big Dat Traditional risk assessment techniques focus on root cause analysis (RCA), which identi es a loss's predominant cause. The inherent weakness of this approach is obvious: RCA can only look backward. Plus, it might not identify all root causes and the related events that contribute to a loss and can only be performed periodically. Today, however, a universe of data about past events can empower decision making that is further re ned through data about previously imperceptible risk factors. The three components that are fueling the big data revolution are data capture, data storage, and data analytics. 1.b. Data Captur Data capture is enabled primarily by smart products that sense their environment, process data, and communicate with other smart products and smart operations through the Internet of Things (IoT). These interactions generate the data to which advanced analytics can be applied. The availability and sophistication of smart products and the IoT’s continued growth have led to an explosion of risk management innovation. 1.c. Data Storage The decision-making value of data produced by smart products, the IoT, and other data-capturing technology can be undermined by its volume, velocity, and veracity; more and faster is not necessarily better. Cloud computing (Information, technology, and storage services contractually provided from remote locations, through the internet or another network, without a direct server connection) enables the storage and sharing of vast amounts of data. Think of the blockchain as a virtual distributed ledger that maintains a list of dynamically updated data records (blocks). These records are not actually recorded in the ledger, however, until the veracity of data within them is con rmed and veri ed through a consensus process called mining. This veri cation process removes intermediary validation and establishes trust without the use of a centralized authority. After a block is con rmed and the data within it is veri ed through mining, the block is timestamped and added to the preexisting blocks in the chain-hence the term "blockchain." The blockchain is encrypted and protected against tampering and revision. The risk management applications of the blockchain are a by-product of the medium's immutability; security; transparency; scalability; and ability to facilitate the sharing of veri ed, quality data. 12 fi fi fi fi e fi fi fi m 2 fi a
Topic 1. The Risktech Ecosystem 1.d. Data Analytic Collected and stored data can also be used to reveal forward thinking risk management strategies when that data is organized and analyzed through methods that use arti cial intelligence, such as machine learning and data modeling. In short, insurers and risk managers can improve their business results through data-driven decision making in an ever-increasing variety of ways, such as these: 1. Organizing large A risk manager could organize data according to volumes of new data multiple characteristics, such as the information provided by vehicle telematics, which can include speed, braking patterns, left turns, and distance traveled. 2. Discovering new A risk manager could identify the characteristics relationships in data of workers who have never had a workplace accident and use that information to identify how to improve safety for all workers. 3. Exploring new Text mining can be used to compare documents sources of data and analyze notes for various purposes. 4. Developing new The increasingly accurate predictive modeling of products hazards, particularly catastrophe modeling, enabled by sources of shared, comprehensive data about the complex interactions of contributing factors, has led to product innovation. One notable example is parametric insurance, coverage that pays a predetermined amount to the insured if a particular set of parameters occur, such as a hurricane’s wind speed. 13 s fi
Section 1. Embracing Risktech 1.e. Risktec Risk monitoring and mitigation technology is known as risktech. It is similar to insurtech, and many of the technologies used in both realms are identical. However, risktech goes one step beyond insurtech by expanding its focus on how to make risk nancing more ef cient to include how to prevent and mitigate risk in a variety of industries. Risktech is largely the result of emerging technologies coupled with smart products. Their interactions generate big data, to which advanced analytics can be applied, ultimately reducing the uncertainty associated with predicting future events. The application of emerging technologies to risk assessment and control is largely being driven by the Internet of Things (IoT), which consists of IoT objects that collect and transmit data through the internet, primarily through the use of sensors. For example, sensor data can inform a supply chain manager that weather conditions have interrupted the production of parts or that cargo has been stolen. 1.f. New Technologies to Risk Managemen 1. Wearables Wearables such as helmets that monitor fatigue or wristwatches that measure vital signs can sense, monitor, report, and analyze workers’ health or well- being and their surrounding environments. 2. Drones Drones can be used in surveillance and aerial photography; being unmanned and highly versatile makes them ideal for assessing conditions or risks in dangerous or unfamiliar areas. 3. Robots Robots can measure, respond to, and produce data for monitored hazards or changing environmental conditions. And by performing certain activities, they can reduce the frequency of human error. 4. Smartphones Smartphones can measure acceleration, light, temperature, humidity, pressure, proximity, and location; all particularly relevant in transportation and workplace safety. 14 h fi fi t
Topic 1. The Risktech Ecosystem 1.g. Preventive Analytic It is statistical and analytical techniques used to in uence or prevent future events or behaviors. Using the data provided by technologies and smart objects, businesses can practice preventive analytics. Preventive analytics leverages modern technology, big data, and advanced analytics to identify root causes and their interactions. It is particularly effective because it can continuously monitor activity; whether arising from humans or machines. By learning patterns, a machine can identify situations or behaviors that are unexpected or will likely produce an unexpected result. Therefore, preventive analytics is forward looking. Consider how computer-vision technology in an auto identi es and analyzes risks, which can then lead to preventive actions. For example, a truck’s brakes may automatically be applied because a front- facing camera determines that a vehicle has stopped directly in front of the truck. 1.h. Connected Ecosystem A useful way to think about emerging technologies and their application to risk assessment and control is to view them as part of a connected ecosystem. An ecosystem is a system of interconnected parts, and the risktech ecosystem includes emerging technologies, smart products and smart operations, and big data analytics. However, emerging technologies and smart products also connect the physical and virtual domains, resulting in connected ecosystems for a variety of risk management specialties, including property, supply chain, transportation, catastrophe, and workplace safety. Overall, these connections enhance risk management decision making, as they allow property managers to detect leaks and malfunctions, transportation managers to respond to drivers’ issues in real time, more people to be evacuated before an impending catastrophe, and prevention of countless other injuries and damages. 15 fi s s fl
Section 1. Embracing Risktech 1.1. Question: The Risktech Ecosyste 1. The traditional de nition of risk management re ects the traditional concept of risk as Negative. 2. The de nition of risk has evolved to include positive as well as negative attributes. 3. Helmets that monitor fatigue is an example of a wearable. 4. Risks from accidental loss, including the possibility of loss or no loss de nes Hazard risk. 5. Attracting investor interest is a positive risk for a start-up business. 6. Blockchain is described as a distributed database that serves as a collectively shared ledger. 7. Text mining is a tool that can be used by fraud investigators to compare documents and analyze notes. 8. Internet of Things as data capture tools has led to an explosion of risk management innovation by allowing smart products to transmit data to each other and to central hubs. 9. Risk managers today differ from traditional risk managers because they attempt to minimize threats and optimize opportunities. 10. Risk has different meanings within the risk management and insurance communities. 11. Preventive analytics uses smart products and data analytics to identify root loss causes and their implications. 12. The science of designing work spaces based on the health concerns of those who will operate in the work space is called Ergonomics. 13. The emerging technologies applied to risk assessment and control link the physical domain to the virtual domain. Together, these domains linked by the emerging technologies create a Connected ecosystem. 14. The difference between risk tech and insurtech is that Risk tech goes beyond insurtech by expanding its focus to making risk nancing more ef cient and preventing and mitigating losses in a variety of industries. 15. The sensors transmit data to and from each other, and the manufacturing environment is continuously adjusted to assure production is successful. The network of sensors transmitting data and the autonomous corrective actions without human interaction is called The Internet of Things. 16. Southwest Interstate Railroad (SIR) is concerned about the number derailments in recent years. In the past six months, the drones detected a track blockage caused by a rock slide and damage to tracks in a remote area cause by an earthquake. SIR dispatched work crews to make the tracks once again passable, and no derailments occurred. SIR's use of drones, video, real-term video scanning, and computer analysis illustrates Preventative analytics. 16 fi fi fi fi m fl fi
Topic 2. Emerging Technologies, Smart Products, and Operations Topic 2. Emerging Technologies, Smart Products, and Operation Reference: CPCU 500 Online 1st edition, Assignment 1. Module 3, 2.a. Arti cial intelligence (AI Arti cial intelligence (AI) refers to the ability of machines to simulate human intelligence. It enables computers to perform tasks that require critical thinking, such as making decisions for risk assessment and control. It allows robots to work collaboratively alongside humans in factories, cars to operate without human drivers, and claims adjusters to be quickly deployed in the event of a natural catastrophe. Deep learning, an extension of AI, attempts to understand and mimic neural networks in the brain through software that simulates image and speech recognition. One example of deep learning is IBM’s Watson computer, which can be trained in many different areas—such as understanding medical information and its implications to assist medical personnel in crucial decision making. A more common example is improved voice-search capabilities on smartphones. 2.b. Sensors/Sensor Networ Sensors assess risk by detecting and measuring objects or conditions on a continuous basis; this provides early warnings of impending problems or malfunctions and determines whether expected results have occurred. Smart sensors may even trigger remedial actions, thereby controlling risk and helping reduce losses. With the expanding number, type, and speci city of sensors offered (and their ability to work together in network) sensors will continue to play an important role in assessing and controlling risk. Specialized sensors include transducers, actuators, and accelerometers. These and other types of sensors are widely used in factories and many industries (such as construction, medicine, retail, and transportation). Sensors can be categorized by their functions and applications for risk assessment and control. These classi cations include mechanical, thermal, radiant, and biochemical sensors. 17 fi fi fi s k ) 4 fi
Section 1. Embracing Risktech 2.c. Digital Twi Sensors also enable the digital twin, which is a separate digital pro le of a physical object that helps identify risks arising from the object. Sensors on the physical object generate data that is used by the digital twin to analyze risk and provide alerts or take automated actions, when necessary, such as triggering actuators on the physical object to prevent loss. A digital twin allows data taken from the physical object to be analyzed. This analysis can lead to improvements in processes and mechanisms, such as in the manufacturing realm. It also provides orientation and training opportunities without the risk of employee injury or object damage. 2.d. Computer Visio Computer vision is a technology that simulates human vision. It gains an understanding of images and then tries to help a machine not only recognize an object but also give that object context and respond to it as a human would. Computer vision is used in automobiles that are able to read traf c signs or detect pedestrians and other objects. Computer vision involves detecting, extracting, and analyzing images to better understand them. It does this by developing and using algorithms that can automatically provide visual understanding. One of the early tenets of computer vision was segmentation, or how images are seen and mapped. When combined with deep learning, this mapping of features through an algorithm relates to a commensurate action. Computer vision has been used in this way with self-driving vehicles for both risk assessment and risk control. Computer vision and AI can be used in facial recognition software. Cameras capture images of faces, which are matched with le photos or information from other databases. The software then segments the person’s face so that it can be easily compared with others. It can even assess a person’s emotions from his or her facial expressions. This technology has potential uses in identifying criminals in a crowd or quickly and accurately con rming identities of people boarding an aircraft or entering a secure area. These examples give a glimpse of the many risk assessment and control opportunities offered by this emerging technology. 18 n n fi fi fi fi
Topic 2. Emerging Technologies, Smart Products, and Operations 2.e. Smart Product 1. Wearables are designed with ergonomics in mind; they sense, monitor, report, and analyze workers’ health or well-being and their surrounding environments. To be labeled a wearable technology, the product needs to be a type of clothing or accessory that is worn on the body, not carried. To be considered a smart wearable, the device must contain sensors that detect and measure impulses and convert them to useable data, microprocessors that change this data into a transmittable form, and transmitters that wirelessly relay the data for appropriate processing or further use. 2. Drones generally contain one or more cameras, batteries, and sensors, as well as a remote controller for the user and a communication source (usually Wi-Fi) that can accommodate smartphones or other devices. Infrared and thermal sensors in cameras can detect high temperatures, which can reveal overheating equipment and warn employees to move away from an area. Chemical sensors attached to drones can monitor the concentration of certain gases or other particles, and if dangerous amounts are detected, the sensors can report this through a connected transducer. 3. Robots are another type of smart product. They may be either xed (containing moveable parts but unable to travel) or mobile equipped to travel to immediate, adjacent, or even distant environments. Robots have evolved from simple machines built to resemble humans to valuable tools of various design that can collaborate with human workers. Robots also assist humans by performing dangerous tasks and monitoring environmental conditions. 2.f. Smart Operation Smart products are increasing the information risk managers have on hand: information about dangerous chemicals in the air, shipping malfunctions, exhausted workers, or almost any other facet of an organization’s operations. This information is already improving risk mitigation in many industries, and their success will lead to more operations becoming connected ecosystems. Here are some examples: 19 s s fi
Section 1. Embracing Risktech 1. Property Property managers use drones for surveillance and management monitoring. This is a cost-ef cient way to proactively identify damage or security risks at separate locations. Consider the cost difference in scaffolding a building to inspect it versus using a drone. 2. Supply chain Smart glasses can be used to provide inventory management details to order pickers. They can also convey instructions and even training aids to wearers. Organizations are also exploring deliveries by drone. Robotics increase productivity and reduce risk on the warehouse oor. 3. Transportation Wearables have many bene ts for the transportation management industry. They can analyze an operator's driving habits or physical condition in real time. Accelerometers can detect excessive vibration in a vehicle and warn transportation managers of vehicle conditions. Drones can take detailed photos of routes. But the most signi cant change to transportation management may come from autonomous, or robotic, vehicles. 4. Catastrophe With the increased use of sensors in smart objects, management the effects of catastrophes can be mitigated more effectively. Drones increase awareness of potentially dangerous situations as well. The American Red Cross promotes the use of wearables and smartphones in search-and-rescue missions, and robots can be used in unsafe environments. 5. Workplace Thanks to wearables, sensors can be incorporated safety into safety vests or other gear, leaving workers’ management hands free to do their jobs. Drones provide information and help assess and control risks by going into unknown and potentially dangerous areas. Robots operate in close proximity to workers but do more of the repetitive and heavy-lifting jobs. This allows workers to better use their skills and protects them from injury. 20 fl fi fi fi
Topic 2. Emerging Technologies, Smart Products, and Operations 2.1. Question: Emerging Technologies, Smart Products, and Operation 1. Drones may be equipped with cameras that relay data in real-time. 2. Catastrophes such as recent earthquakes and the 2011 tsunami in Japan pointed out a need for many organizations to evaluate and manage their Supply-chain risk. 3. The pulse and respiration monitors and the sensors that are part of the protective gear are called Wearable technologies. 4. The sensors make sure water is owing properly and that there are no leaks or clogs which could produce a loss. These types of sensors are Mechanical sensors. 5. In addition to metal detectors, many airports have installed a second type of scanning technology for checked baggage and cargo. The checked bags and cargo pass through a portal with scanners programmed to detect and test for explosive trace fumes. These scanners, which detect explosives based on air samples, are an example of Biochemical sensors. 6. These smart products, which can be xed or mobile, reduce repetitive motion injuries that humans might suffer. They can also be used to perform dangerous tasks and in heavy-lifting jobs. These smart products are called Robots. 7. Tsunami detection buoys are placed in the sea and they are equipped with sensors to detect high wave levels so that an early warning can be given to a coastal area if an evacuation is needed. This application of the use of smart products illustrates their use in Catastrophe management. 8. William is a risk manager for Green Mountain Trucking. He has always analyzed auto loss frequency and severity rates for the eet. William would like to collect data on vehicle speeds, braking patterns, and distance traveled and compare that with the loss history. Vehicle telematics would help William capture and analyze this data. 9. Mutual Fund Company (MFC) offers a wide array of mutual fund options to investors. The computer algorithm continuously monitors each fund's compliance with investment guidelines. If a fund manager violates the investment guidelines, the computer immediately noti es MFC's internal control director, and corrective action is taken. MFC's use of the computer algorithm to monitor investment compliance and to provide noti cation when corrective action is necessary illustrates use of Arti cial intelligence. 10. For example, the technology would detect a presence in a crosswalk, extract the image, and a computer would analyze the image. When the image was determined to be a human being, the vehicle would slow down or stop until the crosswalk was clear. This technology, which is designed to capture and analyze images, and to act on the recognition of the image; is called Computer vision. 21 s fl fi fi fi fl fi
Section 1. Embracing Risktech 11. Last year, three Metro City remen died responding to a re at a chemical plant, when they were overcome by toxic fumes. In response, Metro City is purchasing advanced rst responder gear. It includes special ame retardant suits with chemical and explosive fume sensors, air quality sensors, and heat sensors. Responders will also wear special watches that will track a responder's pulse, respiration, and blood pressure; and helmets that include video cameras. All of these sensors will feed data to a computer in real-time. The computer will analyze the data and issue threat levels and evacuation orders, if necessary. The protective gear Metro City will purchase and the data transmission and analysis capability illustrate the use of Smart products. 22 fi fi fi fl
SECTION 2. CREATING A STRONGER RM FOUNDATION Topic 3. Risk Management Process and Classi cations of Risk Topic 4. Risk Management Objectives, Benefits, and Basic Measures 23 fi
Section 2. Creating a Stronger RM Foundation Topic 3. Risk Management Process and Classi cations of Risk Reference: CPCU 500 Online 1st edition, Assignment 2. Module 1, 3.a. Concept of Risk Management Process The rst thing you should know about the risk management process is that it isn’t actually a process; at least not in its application. Rather, it’s a set of interconnected simultaneously and sequentially occurring activities that de ne an organization’s holistic approach to managing risks. It also differs from organization to organization. This is because each organization’s risk management framework is re ned based on how well it’s working and on signi cant changes in the organization’s external and internal environments. Despite differences in its implementation, however, the process's success always relies on effective communication and collaboration among key stakeholders. Your ability to facilitate and maximize the value of those interactions brings the process to life. 24 fi fi fi fi fi 2
Topic 3. Risk Management Process and Classi cations of Risk 3.b. Process for Managing Risk 1. Scan the Risk management professionals should conduct speci c, Environment detailed reviews of both the internal and external environments of an organization. 2. Identify The purpose of risk identi cation is to develop a Risks comprehensive list of risks that could affect the organization’s objectives. Identifying all risks is not feasible or practical, but identifying key and emerging risks is essential. 3. Analyze Risk analysis involves applying the de ned risk criteria Risks to determine the source, cause, likelihood, and potential consequences of each of the identi ed risks. Depending on the circumstances, this analysis can be quantitative, qualitative, or both. Quantitative analysis, in particular, may entail interacting with experts. 4. Treat Risks When no regulatory requirements are present, an organization should compare the total level of risk determined during the risk analysis with the established risk criteria. This comparison will guide decisions regarding risk treatment. These are the major options available for risks: (1) Avoid the risk (2) Modify the likelihood and/or impact of the risk (3) Transfer the risk (4) Retain the risk (5) Exploit the risk. 5. Monitor Effective risk management processes include ongoing and Review monitoring with periodic review of results. These are the key purposes of monitoring: (1) Determine the effectiveness of controls (2) Obtain information to improve risk assessment (3) Analyze events and their consequences to understand trends, successes, and failures (4) Observe changes in internal and external environments (5) Identify emerging risks. 25 fi fi fi fi fi
Section 2. Creating a Stronger RM Foundation 3.c. Scan the Environmen For example, risk management processes around employee safety in the United States include the legal and regulatory requirements of the Occupational Safety and Health Administration (OSHA) and state or federal workers compensation statutes, as well as external stakeholders’ procedures (such as insurers’) and the organization’s internal procedures. Scanning the environment includes evaluating how each of an organization’s risk management processes aligns with its overall objectives. Additionally, risk management professionals should collaborate with the organization's internal stakeholders to de ne its risk criteria. These criteria should be aligned with the organization’s objectives, resources, and risk management policy and should consider these factors: (1) Causes of risk (2) Effects of risk (3) Metrics used to measure effects of risk (4) Timeframe of potential effects (5) Methods to determine level of risk (6) Approach to combinations of risk. 3.d. Identify Risks This process relies on the risk professional's ability to perform or facilitate several key tasks involving communication, including these: (1) Asking the right questions of departmental stakeholders to understand their perspectives on the most pressing risks they face (2) Finding external experts who can shed light on emerging risks that the organization may not have anticipated previously and knowing how to speak their language to get the most from interactions with them (3) Collaborating with senior management and the board to ensure that risk associated with the organization's strategy are identi ed. Identifying risk interactions is also important. For example, the risk of a customer being injured by an organization’s product may traditionally have been viewed as a hazard risk. However, in an enterprise-wide process, related risks in other quadrants can be identi ed; such as reputational risk from publicity about the injury, which could have both strategic and nancial effects. If a product recall becomes necessary, operational and nancial risks would result. 26 fi t fi fi fi fi
Topic 3. Risk Management Process and Classi cations of Risk 3.e. Classi cations of Risk One essential attribute of anyone who manages risk is the ability to classify it. Classi cation can help with assessing risks because many risks in the same class have similar attributes. It also can help with managing risk, because many risks can be managed with similar techniques. Finally, classi cation helps with the administrative function of risk management by helping to ensure that risks in the same class are less likely to be overlooked. These classi cations of risk are some of the most commonly used: (1) Pure and speculative risk (2) Subjective and objective risk (3) Diversi able and nondiversi able risk (4) Quadrants of risk (hazard, operational, nancial, and strategic) 3.f. Pure and Speculative Risk A pure risk is a chance of loss or no loss, but no chance of gain. For example, the owner of a commercial building faces the risk associated with a possible re loss. But speculative risk involves a chance of gain. As a result, it can be desirable, as evidenced by the fact that every business venture involves speculative risks. Speculative risk is highly affected by these factors: (1) Price risk: Uncertainty the cost of raw materials and other inputs (such as lumber, gas, or electricity), as well as cost-related changes in the market for completed products and other outputs. (2) Credit risk: Although a credit risk is particularly signi cant for banks and other nancial institutions, it can also be relevant to any organization with accounts receivable. Financial investments, such as the purchase of stock shares, involve a distinct set of speculative risks. Insurance deals primarily with risks of loss, not risks of gain—that is, with pure risks rather than speculative risks. However, the distinction between these two classi cations of risk is not always precise. Many risks have both pure and speculative aspects. For example, although a commercial building owner faces a pure risk from causes of loss such as re, that owner also faces the speculative risk of the building’s market value increasing or decreasing during any one year. 27 fi fi fi fi fi fi fi fi fi fi fi fi fi
Section 2. Creating a Stronger RM Foundation 3.g. Subjective and Objective Risk Because it is based on opinion, subjective risk may be quite different from the actual underlying risk that is present. In fact, subjective risk can exist even where objective risk does not. The closer an individual’s or organization’s subjective interpretation of risk is to the objective risk, the more effective its risk management plan will likely be. These are some ways that subjective and objective risk can differ: 1. Familiarity and control: For example, although many people consider air travel (over which they have no control and likely low familiarity) to carry a high degree of risk, they are much more likely to suffer a serious injury when driving their cars, where the perception of control and degree of familiarity are much greater. 2. Consequences over likelihood: People often have two views of low- likelihood, high-consequence events. The rst misconception is the “It can’t happen to me” view, which assigns zero probability to such low-likelihood events as natural disasters, murder, res, and accidents. The second misconception is overstating the probability of a low-likelihood event; this is common with people who were previously exposed to such an event. This perception may be enhanced by increased media coverage given to high- severity events. 3. Risk awareness: Because organizations have different levels of risk awareness, they perceive risks differently. An organization that is not aware of its risks, for example, would perceive the likelihood of something happening as very low. 3.h. Diversi able and Nondiversi able Ris Diversi able risk is not highly correlated—that is, its gains or losses tend to occur randomly and be isolated. Such risk can be managed through diversi cation, or spread, of risk. An example of a diversi able risk is a re, which is likely to affect only one or a small number of businesses. So an insurer can diversify the risks associated with re insurance by insuring many buildings in several different locations. Examples of nondiversi able risks include in ation, unemployment, and natural disasters such as hurricanes. Nondiversi able risks are correlated. For example, interest rates can increase for all rms at the same time. Systemic risks are generally nondiversi able. For example, if excess leverage by nancial institutions causes systemic risk resulting in an event that disrupts the nancial system, this risk will have an effect on the entire economy and, therefore, all organizations. Because of the global interconnections in nance and industry, many risks that were once viewed as nonsystemic (affecting only one organization) are now viewed as systemic. 28 fi fi fi fi fi fi fi fi fi fi fi fl fi fi k fi fi fi
Topic 3. Risk Management Process and Classi cations of Risk 3.i. Quadrants of Risk: Hazard, Operational, Financial, and Strategi Although no consensus exists about how an organization should categorize its risks, one approach involves using risk quadrants: (1) Hazard risks arise from property, liability, or personnel loss exposures and are generally the subject of insurance. (2) Operational risks fall outside the hazard risk category and arise from people or a failure in processes, systems, or controls, including those involving information technology. (3) Financial risks arise from the effect of market forces on nancial assets or liabilities and include market risk, credit risk, liquidity risk, and price risk. (4) Strategic risks arise from trends in the economy and society, including changes in the economic, political, and competitive environments, as well as from demographic shifts. Hazard and operational risks are classi ed as pure risks, and nancial and strategic risks are classi ed as speculative risks. The focus of the risk quadrants is different from the risk classi cations previously discussed. Risk classi cations focus on some aspect of the risk itself, while the four quadrants of risk focus on the risk source and who traditionally manages it. 29 fi c fi fi fi fi fi fi
Section 2. Creating a Stronger RM Foundation 3.1. Question: Classi cations and Categories of Risk 1. A pure risk is a chance of loss or no loss, but no chance of gain. 2. Hazard risks are type of risks that can result in losses but not in any gains. 3. Risk can be classi ed as subjective or objective. Subjective risk can exist even where objective risk does not. 4. The focus of risk quadrants is different from the focus of risk classi cations in general. While the classi cations of risk focus on some aspect of the risk itself, the four quadrants of risk focus on The source of risk and who has traditionally managed it. 5. A new computer chip that could position a company for explosive growth is an example of Strategic risk. 6. Fluctuations in the value of stocks or bonds due to interest rate changes is an example of Financial risk. 7. One enterprise risk management (ERM) approach to categorizing risks involves dividing risks into four risk quadrants. The risks categorized as hazard risks are Traditionally managed by risk management professionals. 8. Carol has worked as a payroll clerk for a small organization for 20 years. Over the years she received only two small salary increases and began to embezzle funds from the company since she felt she was not adequately compensated for her job efforts. In terms of the quadrants of risk, Carol's theft risk can be classi ed as Both a hazard risk and an operational risk. 9. Company G is a manufacturer of high pro le golf equipment. The risk management professional for Company G is concerned about loss of business related to product design. Failing to respond to changing customer demand and preferences in the design of golf clubs could cost Company G signi cant market share. Categorized according to the quadrants of risk, this exposure to loss is classi ed as A strategic risk. 10. George has received an inheritance and is deciding what to do with the money. He has limited his options to four choices: donate all the money to his favorite charity, use the entire inheritance to buy a yacht, invest the inheritance in a small rental property, or use the entire amount to purchase T- bills. In this case, The rental property presents both pure and speculative risk; property values may increase, and the building could burn down. 11. Jean is the Risk Manager for a Fortune 1000 company. Her CFO has tasked her to analyze vulnerabilities in the rm's supply chain. The adequacy of suppliers to meet an organization's needs would be an example of Operational risk. 30 fi fi fi fi fi fi fi fi fi
Topic 3. Risk Management Process and Classi cations of Risk 12. During the past year, International Toys has undertaken four capital projects. The company has renovated and refurbished one of its aging warehouse buildings. It has purchased the most recent version of its current order processing computer software. It has added two trucks to its eet of delivery vehicles. Lastly, it has purchased a new production machine that will allow it to launch a new product line. In this case, The new production machine is the most speculative risk in the company projects. 13. George works for a large company and part of his job is to monitor assets according to their liquidity. George is particularly concerned that the company eet cars are affecting its liquidity and rising fuel prices are having an adverse effect during tight economic markets. If George's concerns were categorized as causes of loss according to the quadrants of risk, his concern most directly relates to Financial risks. 31 fl fi fl
Section 2. Creating a Stronger RM Foundation Topic 4. Risk Management Objectives, Bene ts, and Basic Measure Reference: CPCU 500 Online 1st edition, Assignment 2. Module 3, 4.a. Risk Management Objective 1. Tolerable (1) Reduce Downside Risk (2) Earnings Stability (3) Uncertainty Anticipate and Recognize Emerging Risks (4) Business Continuity 2. Pro tability (1) Intelligent, strategic risk taking (2) Identi cation and Growth and management of cross-enterprise risks (3) Improved capital allocation 3. Reduced Cost (1) Costs of accidental losses not reimbursed by of Risk insurance or other outside sources (2) Insurance premiums and expenses incurred for noninsurance indemnity (3) Costs of risk control techniques to prevent or mitigate accidental losses (4) Costs of administering risk management activities 4. Legal and Such legal obligations are typically based on these Regulatory items: (1) Standard of care that is owed to others (2) Compliance Contracts entered into by the organization (3) Federal, state, provincial, territorial, and local laws and regulations 5. Social Businesses must ful ll their social obligations and Responsibility behave morally for the community and society as a whole. 32 fi fi s s fi 4 fi
Topic 4. Risk Management Objectives, Bene ts, and Basic Measures 4.b. Tolerable Uncertainty De ning and maintaining tolerable uncertainty, which means aligning risks with the organization’s risk appetite, is essential to every holistic risk management strategy. This connects to risk management’s fundamental purpose for organizations. To meet this objective, risk management programs should use measurements that align with the organization’s overall objectives and take into account senior management’s risk appetite. For example, value- at-risk (VaR) can be used to analyze various nancial portfolios with different assets and risk factors. VaR can be calculated quickly and easily to determine risk-factor returns on a portfolio. (1) Reduce Downside Risk: Downside risks, including losses and failures, are an inevitable aspect of any type of business or speculative risk. To reduce downside risks, organizations can use threshold limits, which can be applied to many types of risks. By monitoring risks with preset limits based on established risk criteria, triggers are established to alert management when the threshold has been breached. When these thresholds are breached, management can review the situation and discuss changes before the losses become more signi cant and more dif cult to manage. The risk management strategy an organization uses must be well thought out so that the strategy itself does not increase risk. (2) Earnings Stability: Maintaining earnings stability requires precise forecasting of uctuations in asset values, liability values, and risk management costs (such as costs for insurance). (3) Anticipate and Recognize Emerging Risks: Analyzing the past will always be one of the most effective ways to predict the future—after all, past is prologue. However, the risks that offer the richest potential upside and the most calamitous downside are often those that either can't be anticipated at all or are deemed so improbable that the organization doesn’t even consider them. An organization’s risk radar should scan both the organization and the external environment for emerging risks. This radar should also be sensitive to the convergence of emerging internal and external risks. (4) Business Continuity: Continuity of operations is a key goal for many private organizations and an essential goal for all public entities. Although survival requires only that no risk occurrence (no matter how severe) permanently shut down an organization, the goal of continuity of operations is more demanding. To be resilient, an organization cannot interrupt its operations for any appreciable time. When an organization’s senior management sets business continuity as a goal, its risk management professionals must have a clear, detailed understanding of the speci c operations for which continuity is essential and the maximum tolerable interruption interval for each operation. 33 fi fl fi fi fi fi fi
Section 2. Creating a Stronger RM Foundation 4.c. Pro tability and Growth Holistic risk management isn’t just about staving off disaster or ensuring organizational survival. Ideally, risk management is integrated into every facet of an organization’s strategy for pro tability and growth. (1) Intelligent, strategic risk taking: Successful organizations usually take risks to grow and increase pro t. This type of risk can create a positive or a negative outcome. Decisions about new opportunities should be based on the organization’s risk appetite. An important bene t of risk management is that it provides organizations with a framework to analyze and manage the risks associated with an opportunity. For example, when an organization considers whether to expand into a new product line, risk management can help it decide whether the potential rewards are greater than the downside risks. (2) Identi cation and management of cross-enterprise risks: For example, supply chain risks have traditionally been viewed as operational risks. However, a supply chain interruption could also become a nancial risk if it affects product sales and a reputational risk if it affects customer service. Holistic risk management provides an opportunity to recognize these cross- enterprise risks when making strategic supply chain decisions. (3) Improved capital allocation: A holistic risk management strategy empowers organizations to improve their capital allocation in two ways. The rst is by reducing the cost of risk, freeing up capital for other purposes. The second way is by improving risk analysis for various strategic options so that capital is allocated where it is likely to produce the best reward for the risk. 4.d. Reduced Deterrent Effects of Hazard Risk Risk management reduces the deterrent effects of uncertainty about potential future accidental losses by making these losses less frequent, less severe, or more foreseeable. The resulting reduction in uncertainty offers organizations these bene ts: (1) Alleviates or reduces management’s fears about potential losses, thereby increasing the feasibility of ventures that once appeared too risky (2) Increases pro t potential by greater participation in investment or production activities (3) Makes the organization a safer investment and therefore more attractive to suppliers of investment capital through which the organization can expand. The security sought by these sources of new capital rests at least partly on con dence that the organization will prosper despite the accidental losses that might befall it. Consequently, an organization’s ability to attract willing investors depends to a signi cant degree on the effectiveness of its risk management program to protect investors’ capital against the cost of accidental losses. 34 fi fi fi fi fi fi fi fi fi fi s fi
Topic 4. Risk Management Objectives, Bene ts, and Basic Measures 4.e. Basic Risk Measures Risk professionals should use these measures to evaluate an organization’s risk pro le. Highly correlated risks with a high likelihood, major consequences, high volatility, and signi cant exposure over a long time horizon should be a key focus of risk management. 1. Exposure In these examples, the exposure can be quanti ed based on the number and amount of mortgages or the number of policies and policy limits. Other exposures, such as the risk of a data breach or loss of reputation, are not as easily quanti ed. 2. Volatility The CBOE Volatility Index, or VIX, created by the Chicago Board Options Exchange, provides a measure of stock market volatility. The volatility of energy prices, as another example, is a major risk for many organizations. Utilities, airlines, trucking companies, and other types of organizations that are highly dependent on fuel use strategies such as hedging to manage the risk associated with volatility in the price of oil and other fuels. 3. Likelihood For example, a bank can probably quantify the likelihood of a loan default based on a prospective borrower's credit score and other characteristics. However, it would be more dif cult for the bank to determine the likelihood of a cyberattack in which customer data is taken, resulting in liability. 4. Risks with high likelihood and minor consequences Consequences should usually be managed through an organization’s routine business procedures. Risks with potentially major consequences should be managed even if the likelihood of their occurrence is low. For instance, the risk of a re at a bank, although unlikely, must be managed. 5. Time For example, diversi cation in nancial investments can horizon help manage the risks associated with the time horizon of those investments. An insurer that matches the durations of its assets (investments) and liabilities (loss reserves) neutralizes the risks associated with time horizon. When real estate prices are highly volatile, an organization may defer an expansion strategy that involves a long time horizon, such as purchasing or building new facilities. 6. Correlation The correlation coef cient is a measure that determines the degree to which two variables' movements are associated. The range of values for the correlation coef cient is -1.0 to 1.0. For example, if hazard risk A and nancial risk B are positively correlated (correlation increase), then the overall risk of the organization is increased and, if it is negatively correlated (or uncorrelated), the overall risk is reduced. 35 fi fi fi fi fi fi fi fi fi fi fi fi
You can also read