Emerging Technologies (DISA ISA 3.0)

Module 6 ISA DISA 3.0

1. 1 Digital Accounting and Assurance Board The Institute of Chartered Accountants of India (Set up by an Act of Parliament) ISA 3.0 Emerging Technologies Module - 6

2. 2 Learning Objective Understand concepts of the following Emerging Technologies and the evolving landscape Understand the Impact on the Profession Understand the Risks in Emerging Technologies Evaluate the approach of Governance and Controls in these Technologies Understand the inter-relationship with these emerging technologies. Understand Role of Professionals

3. General Structure Meaning Examples in Finance Use Cases Impact on Audit Risks and Challenges Governance and Controls Professional Opportunities

4. Chapter 1 Artificial Intelligence

5. Artificial intelligence (AI) is an advanced computer system that can simulate human capabilities, , based on predetermined set of rules. Some of the activities computers with artificial intelligence are designed for include: Speech recognition Learning Planning Problem solving

6. Machine Learning: It refers to the use of computing resources that have the ability to learn, acquire and apply knowledge and skills. These cognitive systems have the potential to learn from business related interactions and deliver evidence-based responses to transform how organizations think, act and operate.

7. Machine learning A neural network Deep learning Cognitive computing Computer vision Natural language processing (NLP) Common Terminologies used in AI

8. Why AI is important? AI automates repetitive learning and discovery through data AI adds intelligence to existing products. E.g. Siri in new generation Apple products AI adapts through progressive learning algorithms to let the data do the programming. AI analyzes more and deeper data using neural networks that have many hidden layers. AI achieves incredible accuracy through deep neural networks - which was previously impossible. AI gets the most out of data. When algorithms are self-learning, the data itself can become intellectual property.

9. Types of AI Based on Capabilities Weak AI or Narrow AI General AI Super AI Based on functionality Reactive Machines Most basic type of AI. Limited Memory Theory of Mind Self-Awareness

10. AI Platforms IBM – Watson Analytics Google – Deep Mind – Tensor Flow Microsoft – Cognitive Services Amazon – AWS AI Services Facebook – FB Learner Flow

11. AI and Speech Recognition Speech recognition is technology that can recognize spoken words, which can then be converted to text. A subset of speech recognition is voice recognition, which is the technology for identifying a person based on their voice. The technology to support voice-powered interfaces is growing powerful by the day. With the advancements in artificial intelligence and ample amount of speech data that can be easily mined for machine learning purposes, it would not be surprising if it becomes the next dominant user interface

12. Advantages and Disadvantages of AI Disadvantages High Cost No Replicating Humans No Improvement with Experience No Original Creativity Unemployment Advantage Error Reduction Difficult Exploration Daily Application Digital Assistants Repetitive Jobs No Breaks

13. Pattern Recognition in Banking A number of variables have to be considered in order to establish whether a transaction or set of transactions is suspicious E.g. customer’s salary account in a bank Multiple credits in account other than salary credit Sizeable increase in Cash to Non-Cash Transaction Ratio - large cash deposits and cash withdrawals Many transactions with a few related accounts Burst in Deposits - Number of Transactions, Amount Burst in Withdrawals - Number of Transactions, Amount Unusual applications for Demand Drafts against cash. Transactions that are too high or low in value in relation to customer’s profile Computers will learn the past behavioural pattern of the customer based on historical transactions and may identify unusual activities

14. Use Cases AI in finance JPMorgan Chase Wells Fargo Plantation

15. Impact on Audit AI in its risk assessment. Providing advice and insight, contributing to successful implementation. Assurance on management of risks related to the reliability of the underlying algorithms Effectiveness of risk management, control and governance process. Fraud Investigator

16. Scenarios wherein Artificial intelligence techniques can be used for fraud management: Data mining Expert system Machine learning and pattern recognition Neural network

17. Risks of AI AI is Unsustainable Lesser Jobs A threat to Humanity

18. Challenges for AI Computing is not that Advanced Fewer people support Creating Trust One Track Minds Probability Data Privacy and security Algorithm bias Data Scarcity

19. Governance and Controls Structure, process and procedures. Formality and structure AI governance establishes accountability and oversight Ethical, social, legal responsibilities

20. Professional Opportunities Opportunity to automate and de-skill time-consuming and repetitive work Minimize the burdens and maximize the benefits to organizations. CAs possess the domain knowledge and experience to create the relevant learning algorithms CAs should work closely with AI programmers. Learn patterns of behavior and send out real time alerts CFO of the future will need to know as much about technology.

21. Chapter 2 Blockchain

22. History In the year 2008, an individual or group writing under the name of Satoshi Nakamoto published a paper entitled “Bitcoin: A Peer-To-Peer Electronic Cash System A few months later, an open source program implementing the new protocol was released that began with the Genesis block of 50 coins.  Anyone  can install this open source program and become part of the bitcoin peer-to-peer network .

23. Technologies that make Blockchain  possible Peer -to-peer network (distributed ledger ) Public key infrastructure (blockchain addresses ) Hash function (miner)

24. Advantage of Blockchain Improved  accuracy by removing human involvement in verification Cost reductions by eliminating third-party verification Decentralization makes it harder to tamper with Transactions are secure and efficient Transparent technology

25. Disadvantages of Blockchain Significant  technology cost associated with mining bitcoin Low transactions per second History of use in illicit activities Susceptibility to being hacked.

26. Principles of Blockchain Distributed Database Peer to peer transmission Transparency Irreversibility of records Computational logic

27. Examples in Finance Payments  and  reconciliations Issuance, ownership and transfer of financial  information Clearing and settlement latency

28. Use Cases Barclays  placed themselves at the forefront of adoption by  implementing  the security and transparency aspects of  block chain  technology into their transaction processes . There are a few notable projects that use blockchain  technology  for supply chain management transparency, such as  Ambrosus , which targets the safety and origins of food  products , and  Vechain , a  blockchain based platform  that allows both consumers and retailers to confirm the authenticity and quality of purchased products. DHL, a global logistics leader, is working together with  Accenture , a global management and professional services  company , to integrate blockchain technology with the  pharmaceutical  industry to improve serialization accuracy

29. Impact on Audit Opportunity  to streamline financial reporting and audit processes . The auditor can have near real-time data access  Test internal controls over the data integrity  Auditing Smart Contracts and Oracles

30. Risks and Challenges Vendor risks Credential Security Legal and Compliance Data security and confidentiality Scalability issues  Interoperability between block chains Processing power and time Storage will be a hurdle

31. Governance and Controls Governance  Framework Management Oversight  Regulatory Risk Business Continuity Vendor Management Secure key distribution and management policies Secure APIs and Integrations

32. Professional Opportunities Assist  in evaluating the functional design Evaluation of Proof of Concept Assessment of Risks in Implementation Impact on Audit Audit of Smart Contracts and Oracle

33. Chapter 3 Cloud Computing

34. Characteristic of Cloud Computing Resource   pooling   O n -demand  self   service   Rapid elasticity  Measured  services B road network access

35. Advantages of Cloud Computing Cost  Efficiency Reduce spending on technology infrastructure Unlimited Storage Backup & Recovery Automatic Software Integration Easy Access to Information and Globalize the workforce Reduce Capital costs Quick Deployment Less Personnel training and minimize maintenance and licensing software Improved Flexibility and effective monitoring of projects

36. Disadvantages of Cloud Computing Internet  Connectivity Technical Issues Security in the Cloud Prone to Attack Availability Interoperability

37. Cloud computing development models

38. Private Clouds Resides within the boundaries Built primarily by IT departments within enterprises Optimize utilization of infrastructure resources can either be

39. Characteristics of Private Cloud Secure Central Control Weak Service Level Agreements (SLAs ) Advantages Improve average server utilization Reduces costs Higher Security & Privacy of User Higher automations possible Limitations Invest in buying, building and managing the clouds independently

40. Public Cloud Can be used by the general public Administrated by third parties or vendors over the Internet The services are offered on pay-per-use basis Business models like SaaS (Software-as-a-Service) and other service models are also provided

41. Characteristics of Public Cloud Highly Scalable Affordable Less Secure Highly Available Stringent SLAs Advantages widely used at affordable costs deliver highly scalable and reliable applications no need for establishing infrastructure for setting up and maintaining the cloud. Strict SLAs are followed. There is no limit for the number of users Limitations : Security, Organizational autonomy are not possible.

42. Hybrid Cloud Combination of public, private and community cloud. Normally a vendor has a private cloud and forms a partnership with public cloud provider or vice versa

43. Characteristics of Hybrid Cloud Scalable Partially Secure Stringent SLAs Complex Cloud Management Advantages highly scalable and gives the power of both private and public clouds. Provides better security than the public cloud. Limitations security features are not as good as the private cloud and complex to manage

44. Community Cloud Exclusive use by a specific community of consumers from organizations that have shared concerns Owned, managed, and operated by one or more of the organizations in the community, a third party or some combination of them May exist on or off premises Suitable for organizations that cannot afford a private cloud and cannot rely on the public cloud either

45. Characteristics of Community Cloud Collaborative and Distributive Maintenance Partially Secure Cost Effective Advantages Establishing a low-cost private cloud. Collaborative work on the cloud. Sharing of responsibilities among the organizations. better security than the public cloud. Limitation Autonomy of the organization is lost some of the security features are not as good as the private cloud Not suitable in the cases where there is no collaboration

46. Service Models of Cloud Computing Platform as a service Infrastructure as a service Software as a service

47. Impact on Audit and Auditors Does the organization’s strategy for the cloud link to the overall business strategy? Are the audit teams knowledgeable about the differences in cloud computing services and do they apply the right approach to deliver effective audit coverage? Is there a clear understanding of the difference between the organization and the cloud, and where the technology boundary starts and stops? What is the IT General Controls on the Cloud enforced by the organization? Have there been any independent audits / review of the Cloud environment?

48. Risk and Challenges Greater dependency on third parties Increased complexity of compliance with laws and regulations Reliance on the Internet as the primary conduit to the organization’s data Unclear responsibilities and accountabilities Compromised system security Invalid transactions or transactions processed incorrectly Failure to respond to relationship issues with optimal and approved decisions

49. Governance and Control Governance of Cloud Computing Services Enterprise Risk Management IT Risk Management Third-party Management Legal Compliance Right to Audit Certifications Service Transition Planning

50. Professional Opportunities Assessment with respect to costs and benefits on migration to cloud versus in-house tools Cloud based solution Implementation for clients Assessment on the model of cloud to be deployed and the variants for the same. Consulting with respect to the migration from traditional facilities to cloud based infrastructure. Training to the user staff as regards the operating of these facilities; IT audit of these facilities

51. Chapter 4 Data Analytics

52. Data Analytics is defined as the science of examining raw and unprocessed data with the intention of drawing conclusions from the information thus derived. It involves a series of processes and techniques designed to take the initial data sanitizing the data, removing any irregular or distorting elements and transforming it into a form appropriate for analysis so as to facilitate decision-making.

53. Common Terminologies Data Warehouse Data Marts Business Intelligence Database Data Lake Data Science

54. Types of Data Analytics Descriptive analytics Diagnostic analytics Predictive Analytics Prescriptive analytics Cognitive Analytics

55. Data Analytics Functions Column Statistics Benford Law Back-Dated Entries Identify Duplicates & Gaps Authentication Check Beneish M-Score Same-Same Different Pivot Table / MIS Identify Outliers by Masks Pareto Outliers Sampling ABC Analysis Aging Analysis Splitting Vouchers Quadrant / Pattern Analysis Trendlines Rounding off Relative Size Factor (RSF) 3-Way Matching Weekend Payments Max Variance Factor (MVF) Analytical Review Vouchers with Blank Reference and Narrations

56. Steps involved in applying Analytics on Data Curate / Cleansing the Data Profile the Data Analyse the Data Investigate Document

57. Some Data Analytics software and Testing tools MS Excel General Audit Software General Audit Software Application Software Specialized Audit Software

58. Advanced Tools for analytics Hadoop R programming Python programming Matlab Julia

59. Examples in Finance BFSI Compliance and Regulation

60. Use Cases Uber is a popular smartphone application that allows you to book a cab. Uber makes extensive use of big data. Uber has to maintain a large database of drivers, customers, and several other records. Uber makes the best use of data science to calculate its surge pricing. When there are less drivers available to more riders, the price of the ride goes up and if the demand for Uber rides is less, then Uber charges a lower rate. This dynamic pricing is rooted in Big Data and makes excellent usage of data science to calculate the fares based on the parameters.

61. Impact on Audit Completeness Accuracy Validity Authorization Segregation of duties Compliance Cut off

62. Risks and Challenges Data privacy and confidentiality Completeness and integrity of the extracted client data may not be guaranteed Compatibility issues with client systems Audit staff may not be competent to understand the exact nature of the data and output Insufficient or inappropriate evidence retained on file due As large volumes will be required firms may need to invest in hardware to support such storage An expectation gap among stakeholders

63. Professional Opportunities Analytics Business Consultant Analytics Architect / Engineer Business Intelligence and Analytics Consultant Metrics and Analytics Specialist Preparation of MIS and Dashboards including Visualization Solutions Monitor tracking of Key Performance Indicators (KPIs) and Key Result Areas (KRAs).

64. Chapter 5 Internet of Things

65. The Internet of Things , or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

66. Benefits of IOT Monitor their overall business processes Improve the customer experience Save time and money Enhance employee productivity Integrate and adapt business models Make better business decisions and Generate more revenue

67. Advantages of IoT Improved business insight and customer experience Efficiency and productivity gains Asset tracking and waste reduction Cost and downtime reductions Newer business models

68. Examples in Finance Inventory Tracking and Management Fraud prevention Optimized capacity management

69. Use Cases DeTect Technologies an IoT startup, focuses on asset integrity management, especially in the conventional oil and gas industry, and has built a unique, patented technology for pipeline condition monitoring in real-time using a long-range ultrasonic sensor for temperatures of up to 350 degrees Celsius. TagBox uses IoT automation and analytics as the foundation of its cold chain supply business. It helps clients create reliable and sustainable cold chains through comprehensive solutions that use IoT , advanced analytics, as well as automation and control, which gives real-time visibility of the entire cold chain (cold storage, cold transit and retail refrigeration).

70. IoT and Smart Cities Ever since the concept of a smart city was introduced, IoT (Internet of Things) has been considered the key infrastructure. A smart city can be described in a wide sense as the convergence of ICT, the ecological environment, energy technologies, and support facilities within urban and residential environments.

71. Benefits of IoT in creating Smart Cities Better Management of traffic and reduced congestion on roads Improved crime detection and surveillance Reduction in pollution Savings in Power and electricity Improvised safety for citizens Increased efficiency in parking Better waste and sewage management

72. Impact on Audit Automatically receive all associated data through a digital system Inventory and Assets Reducing time lapse Drone can help gathering evidences presence of personnel is detected Sample test not required

73. Risks Software updates and patches Hardware lifespan Security and privacy issues

74. Challenges Insecure web interface Insufficient authentication/authorization Insecure network services Lack of transport encryption Privacy concerns Insecure cloud interface Insecure mobile interface Insufficient security configurability Insecure software/firmware Poor physical security

75. Governance and Controls IoT solution governance can be viewed as the application of business governance, IT governance, and enterprise architecture (EA) governance. IT organizations must: Develop a comprehensive technical strategy to address the complexity Develop a reference architecture for their IoT solution Develop required skills to design, develop, and deploy the solution Define your IoT governance processes and policies

76. Professional Opportunities   IoT will bring CAs new opportunities for client service in the areas of business process design and data analysis. Clients will need CAs to help set up accounting and recording systems, such as dashboards that aggregate data received from the IoT . CAs may also be hired to provide opinions on the security of the IoT .

77. Chapter 6 Robotics Process Automation 82

78. Robotics Process Automation 83

79. 84 Key Objectives for RPA Implementation Improve accuracy Reduction of monotonous work Higher efficiency Manage controls Skill upgradation of personnel Cost saving Improve customer experience

80. 85 Examples in Finance Credit Card Application E-Commerce Websites and Logistic Companies KYC Authentication

81. 86 Use Cases ICICI Bank, one of India’s major financial institutions, started its automation journey in 2016. It was one of the first private lenders to adopt software robotics on such a large scale. Using robotic process automation (RPA), the bank’s operations department deployed 200 robotics software programs. The development helped the ICICI Bank to process around 10 lakh transactions per day. Today, the RPA is helping to process more than 2 million transactions daily.

82. 87 Impact on Audit Need to understand technology Opportunity to influence control design Potential to increase audit efficiency Free up capacity to focus on higher priorities Enhance ability to add valuable insight Need to develop new testing approaches Consider for changes to internal audit staffing model

83. 88 Risks RPA strategy risks Tool selection risks Launch/project risks Operational/execution risks

84. 89 Challenges Shortage of skilled resources Lack of proper team structure Unable to automate end-to-end cases Vaguely defined business continuity plans

85. 90 Governance and Control Ownership Deployment framework Operational risk/ data security Enterprise management RPA Vision/roadmap

86. 91 Professional Opportunties The McKinsey Global Institute estimated in its December 2017 reports that by 2030, automation will drive between 75 and 375 million people to reskill themselves and switch occupations. Robotic Process Automation (RPA) is not replacing accountants but evolving their role and augmenting their effectiveness through automation. It is a progressive, positive, and necessary shift that is creating the digital workspace for accounting and finance professionals to focus on the greatest value they can provide to their organisation.

87. 92 Practice Questions

88. 93 Q. 1.What does P2P technology stand for? Password to Password Peer to Peer Product to Product Private Key to Public Key Correct answer is B P2P stands for Peer to Peer Technology where every participant acts as an individual peer in the network

89. Q.2. What is a Blockchain ? A distributed ledger on a peer to peer network A type of cryptocurrency An exchange A centralized ledger Correct answer is A A distributed ledger on a peer to peer network . Blockchain is a distributed ledger on a peer to peer network

90. Q.3. Which of the following is not a step involved in RPA? Preparation of project Development of business cases Implementation of RPA Data Cleaning Correct answer is D Data Cleaning is not an activity within RPA. Preparation of project, Development of business cases and Implementation of RPA are steps within the RPA project

91. Q.4. Which of the following statement about RPA is false? It is walking talking robot It is a computer coded software These are programs that replace human repetitive tasks These perform in cross functional platforms Correct answer is A RPA is not a walking talking robot. It is instead a computer coded software, that replace human repetitive tasks which can perform in cross functional platforms

92. Q.5. Which of the following is a system of inter-connected and inter-related computing devices which have ability to transfer the data over network? Blockchain Internet of Things Robotic Process Automation Artificial Intelligence Correct answer is B The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

93. Q.6. Which one is simplest form of analytics? Predictive Descriptive All of the mentioned Prescriptive Correct answer is B Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis

94. Q.7. The method by which companies analyze customer data or other types of information in an effort to identify patterns and discover relationships between different data elements is often referred to as: Customer data management Data mining Data digging None of the above Correct answer is B Data mining refers to a method where companies analyze customer data or other types of information in an effort to identify patterns and discover relationships between different data elements.

95. Q.8. Which of the following is a central storage for all kinds of structured, semi structured or unstructured raw data collected from multiple sources even outside of company’s operational systems? Data Warehouse Data Lake Database Data marts Correct answer is B Data Lake is a central storage for all kinds of structured, semi structured or unstructured raw data collected from multiple sources even outside of company’s operational systems.

96. Q.9. Which of the following tools best describe Predictive Analytics? Simulation Statistical Analysis Machine Learning Graphical reports Correct answer is A Predictive Analytics analyses the past behaviour and makes predictions about the future to identify the new trends. Simulation is one such technique used in predictive analytics. Graphical reports and statistical analysis are more commonly associated with historical / descriptive analytics. Machine Leaning is used in Cognitive analytics.

97. Q.10. Which of the following is not a cloud deployment model? Private Public IaaS Hybrid Correct answer is C Private, Public and Hybrid are cloud deployment models. IaaS is a Cloud Service Model as per NIST categorisation.

98. Q.11. Which of the following is not a stream of AI? Machine Learning Big Data Speech Recognition Natural language processing (NLP) Correct answer is B Big Data refers to huge and voluminous data characterised by volume, variety and velocity. Machine Leaning, Speech recognition and NLP are streams in AI.

99. Q.12. Which of the following is not an example for AI Platform? Watson Tensor Flow AWS AI Microsoft Power BI Correct answer is D Microsoft Power BI is a predominantly a Data Analytics Platform. Watson, Tensor Flow and AWS AI are AI Platforms.

100. 105 ? Questions

101. Thank You 106