Technology Design and Artificial Intelligence in Asset Management Presentation by:

1. Technology Design and Artificial Intelligence in Asset Management Presentation by: Stephen Mutinda, UX/Information Systems Director- Afrique Hub Uphold public interest www.afriquehub.com

2. Define & Explore Challenges in Asset Management • - Asset Lifecycle Management Needs – Current & Centralized –Mobile, Status (Warranties etc), Reporting • How to use data collected by our systems, ERP,EAM • Asset info ain’t valuable unless some one uses the information to make good decisions that positively impact an assets performance. • Organization Alignment Challenge- Sync maintenance management and production management goals and targets Plan & Scheduling • Explore 3 Technologies that would effectively meet the needs in Asset Management. – Best Practices strategy for implementation • Practical – Fixed Asset Management System PRESENTATION OBJECTIVES

3. Asset management applies to dealing with people’s, organizations’ or companies’ assets and investments. Assets include either intangible or intangible assets. Intangible assets are things we cannot touch such as intellectual property, goodwill, financial assets, or human capital.  Tangible assets, on the other hand, are things we can touch and include buildings, land, computers, or office equipment. ASSET MANAGEMENT

4. It’s a systematic approach to the governance and realization of value from the things that a group or entity is responsible for, over their whole life cycles.   In its broader definition, asset management is an organized method of introducing, operating, preserving/maintenance, improving and disposing of various assets in a cost-effective way. We care because optimally managing asset effectiveness is the key to: Achieving production targets, Controlling costs, and Meeting corporate and organizational goals. ASSET MANAGEMENT

5. This role is carried out by an Asset Manager, could also be a firm or a person and their main aim, above all, is to make gains, value of use or profit as possible for their client, balancing costs and capitalizing on opportunities. Asset management firms have expert portfolio managers, and access to internal, detailed equity research portfolios and are better positioned to handle above tasks. ASSET MANAGEMENT

6. Physical/fixed asset management: the practice of managing the entire life cycle (Introducing/design/construction/ commissioning, operating, maintaining/repairing, improving/modifying, replacing and decommissioning/ disposal) of physical and infrastructure assets -production and service plants, facilities, transport systems, buildings and other physical assets. Aspects of Asset Management

7. Infrastructure asset management - is the combination of financial, economic, engineering, and other practices applied to physical assets with the objective of providing the best value level of service for the costs involved. Financial asset management Refers to investment management, the sector of the financial services industry that manages investment funds and segregated client accounts which employs experts who manage money and handle the investments of clients Aspects of Asset Management

8. Digital asset management: a form of electronic media content management that includes digital assets Intellectual and non-physical asset management This incorporates the constraints upon such licenses for ownership eg. a time period. Rights such as usage updates, support and maintenance Aspects of Asset Management

9. ENTERPRISE/CORPORATE ASSET MANAGEMENT These are asset information systems that support the management of an organization's assets. An EAM includes an asset registry (inventory of assets and their attributes, GIS Based) combined with a computerized maintenance management system (CMMS) and other modules (such as inventory or materials management), soft assets such as permits, licenses, brands, patents, right-of-ways and other entitlements or valued items. ASSET MANAGEMENT FOCUS POINT

10. SUMMARY OF ASPECTS OF ASSET MGT

11. Asset managers need to make informed decisions in order to fulfill their organizational goals, this requires good asset info, clarity of strategic priorities, inter-departmental collaboration and communications, workforce and supply chain engagement, risk, performance monitoring and continual improvement. Needs in Asset Management include: -Up-to date Asset/product portfolios (type, quantities, condition assessment, growth prospects of brand,profit margins, income contribution of products, market share, operational risks, -Streamlining of operations and offering digital-inspired experiences Whether we are talking about asset management, or the broader category of managed financial services, wealth management, the technology concepts we will discuss generally apply to both. GOALS IN EAM

12. DEFINITIONS • Technology Design are the practices of creating new technology products, services and environments. • It involves innovation and development of products and services that users view as valuable based on their needs, preferences & perceptions. TECHNOLOGY DESIGN Technology is the application of scientific knowledge for practical purpose

13. In Relation to Asset Management, we consider this as a set of business practices to provide solutions that combines financial, inventory and contractual functions to optimize spending and support lifecycle management to strategic decision-making - Are you still tracking assets on a spreadsheet? Asset Tracking and Log, not just keep count • Done well, it helps organizations make better decisions, improve cost controls, demonstrate regulatory compliance, build stakeholder trust and manage risk. • KEYWORDS • Product Design – Visual Design - User Experience – Information Design – Software Architecture – Software Design - Engineering SUBSETS OF TECHNOLOGY DESIGN

14. Use technology that incorporates your unique processes, philosophy, and data. • Integrate your proprietary data, models, and intuitive visualizations to tell a meaningful story. • Leverages portfolio design and collaboration at scale. • Security - Insecure assets can result in the leak of sensitive data. • Challenge • - High technology costs( hardware and software life-cycle costs) for asset management - Asset managers and service desk managers do not know where to start. • Solution Focus • -Develop an IT Asset Management Standard Operating Procedure. • -Draft a list of technical requirements , model and acquire solution • -Improve other processes by leveraging asset data. GUIDE TO CHOICE OF TECHNOLOGY IN AM

15. Blockchain is a shared ledger technology. Ledgers are simply places where we record business transactions like orders, payments, activities and maintenance, repairs and replacements. In distributed relationships, participants have his or her own ledger enabling: • Open collaboration • Transparency- Data is immutable- Transaction carried out cannot be modified with other nodes permission • Real time Consistency – Agreed upon rules verified by all nodes (Smart Contracts) BLOCK CHAIN IN A.M

16. STEPS: • InspirationGet inspired about blockchain is to visit and interact with active think tanks and laboratories • Calaston Tech Co. last year reported that BCT proved capable of processing transactions equivalent to a full day’s trades sourced from across its client base, which spans more than 1,400 fund distribution and asset manager clients in 35 countries. https://www.youtube.com/watch?v=Vw57hxLnWwk • Education – Gain Knowledge • Ideation – Engage team and out of box thinking • Collaboration – With industry frontiers and developers • Prototyping – Gather requirements from stakeholders and team and model your project processes • Implementation – Validation and verification as well as mitigating risk and security concerns involved. Guide to implementing blockchain. Position your firm for the future by advancing asset management technology.

17. Outlines best practices for ITAM in an organization. It provides organizations a way to prove that they're performing that satisfy corporate governance requirements and management activities. • This enables organizations to uniquely identify software that's deployed on a given device. • A data standard for detailing the entitlements and rights associated with a piece of software, and the method for measuring license or entitlement consumption. • A measurement standard that allows for standardized reporting of resource utilization. This standard is especially important when managing complex data center licenses and for managing cloud-based software and hardware. STANDARD FRAMEWORK IN AM

18. DEFINITION OF AI • This is the creation of technology that is able to perform tasks that would normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. • - It can either be done by a computer or a computer controlled robot, machine learning. ARTIFICIAL INTELLIGENCE

19. This is the process of systems learning from data, identifying patterns and making decisions with minimal human intervention SUBSETS OF AI • Email Spam Detection • Mortgage & Loans Eligibility • My voice is my password • https://www.safaricom.co.ke/personal/get-more/information-services/jitambulishe • Robotics involves engineering and design of robots to perform tasks that are difficult for human being to perform or perform consistently e.g Sophia Robot

20. Few years ago A.I was limited to discussion in Academic circles, now making Intelligent systems has caused an Noisy ecosystem of enthusiasts, vendors and service providers on what AI can & Cant. • AMAZON- Without ML, Amazon.com couldn’t grow its business, improve its customer experience and selection, and optimize its logistic speed and quality • Learning Problem Solving, Conversational Agents &Voice & Pattern Recognition IS A.I Real or A Bubble

21. Deep Lens- Swami Siva Subramanian – Detecting and alerting bears in action. AI shapes every aspect of Amazon’s business, from its warehouses full of products to your Bluetooth smart speaker. The ability to save a second or two for millions of orders, delivery time predictions makes a HUGE BOTTOM-LINE DIFFRENCE AI and machine learning powers three popular Amazon products: Alexa , Amazon Go Store – Enter store grab item and customer account debited. Amazon Recommendation Engine – detecting those who bought x bought y so show y earlier in shopping season Dance of robots - https://www.youtube.com/watch?v=eUsGRrIbips Amazon’s 855,000-square-foot fulfillment center in Kent, Washington, 18 miles south of Seattle, they spring in to action when Odhis orders for an iphone from Kondele, manourver other robot shelves and deliver to a worker who will place it in a conveyor belt to the person who will box it up for dispatch CASE VIEW

22. Amazon, Apple, DeepMind, Google, IBM and Microsoft have joined together to create Partnership on AI to Benefit People and Society to develop and share best practices, advance public understanding, provide an open platform for discussion and to identify aspirational effort in AI for socially beneficial purposes. Those working with AI today make it a priority to define the field for the problems it will solve and the benefits the technology can have for society. Big Data analytics for the purposes of mining and making important decisions FUTURE OF AI

23. AI’s tech specific capabilities can be adapted to suit your particular industry strategic realistic objectives, and the significant technical challenges presented by AI adoption can be easier to navigate. AI is a subset of machine learning that deploys algorithms to large sets of data, enabling computers to mimic human intelligence. AI is central to the predictive modeling used by e-commerce companies such as ASOS, or video streaming companies like Netflix. Anyone who has received targeted web ads will have encountered AI technology. Using AI-powered software, companies can better understand the needs of their customers. Automated communications such as email programs and chatbots can be tailored to suit individuals, rather than groups. AI ADOPTION IN ASSET MGT

24. AI Adoption in Big Data acquisition and analytics will involve collating digital content into one location, tagging files with keywords, and making it searchable, anyone in an organization can access and compare assets with ease. Batch uploading of metadata allows keywords to be assigned to groups of images. This speeds up data processing and quickly enables you to make images searchable Simplified file sharing reduces the amount of network storage used by file downloads AI ADOPTION IN ASSET MGT

25. Applying metadata to assets, this makes them searchable state • Image Similarity search feature saves time and offers enhanced user experience with no extra administrative effort. • The feature uses data from the image recognition service Amazon Rekognition in order to calculate the probability of images featuring similar content. This enables establishing assets with common features, styles, [patterns and compositions • convert the image recognition data into valuable search terms AI FEATUTURES IN AM

26. Asset management firms are looking at various ways to consolidate the voluminous data shared across the globe to make informed decisions. • Artificial Intelligence (AI) and machine learning technologies such as supervised and unsupervised learning frameworks can help them analyze various sources of data, recognize patterns within the large volumes of data including images, text, and voice. The different methodologies that are commonly used are predictive and social media analytics, Big Data analytics, news and events sentiment analysis, text mining, and Natural Language Processing (NLP). APPLICATION OF AI IN AM

27. Financial institutions are seeking novel ways to use voluminous data from across the globe to make important investment decisions. While existing business intelligence is mostly built on structured historical and present data available within firms, enterprises also want to use the growing unstructured data. • Predictive analytics, artificial intelligence, and machine learning can be used to detect patterns hidden in structured and unstructured data to produce actionable insights, which can increase the accuracy of key investment decisions. APPLICATION OF AI IN AM

28. Some areas where the asset management industry uses AI and machine learning technologies are: Portfolio management and optimization: This involves optimization of investment and risk strategies, and predictive forecasting of long term price movements are some use cases suitable for the effective use of AI and machine learning. Social media usage and analysis: Social media analytics is primarily used for market sentiment, research analyst opinion, influencer, and demography analyses. The other emerging trend is crowd sourcing ideas to bring analysts, investment managers, and asset managers together to share opinions and monitor trends. INDUSTRY USE CASES

29. Event monitoring and timeline analysis: Technologies to consolidate unstructured data and provide actionable insights by collating data from various portfolios data visualization tools. Customer interaction and services: Banks are using virtual private assistants to provide various services. These services include statements of accounts and funds transfer in core banking, portfolio selection, risk return analysis, and customer portfolio dashboard in the asset and wealth management space. Banks are increasingly using messaging apps that use smartbots and chatbots to interact with customers INDUSTRY USE CASES

30. These technologies can help provide real-time actionable insights, and facilitate portfolio management decisions. Let's look at the framework for some of the use cases. Social media analytics: The firm's portfolio holdings, social media data from Twitter, Facebook and other micro blogging sites, are consolidated to provide sentiment analysis, pattern charts, and so on for a given portfolio (see Figure 1). This is also useful in studying client demographics and preferences, and suggesting relevant products to customers. FRAMEWORK USE CASES

31. FRAMEWORK USE CASES

32. - Data from social media and blogs is fed through an engine with social analytics tools to provide sentiment analysis, insights, trends, patterns and alerts. It should be customizable to the needs of the asset management firms. • User interface frameworks to facilitate interactive and customized data visualization. solution should also include a recommendation framework that combines structured and unstructured data to provide contextual information summary, along with investment recommendations. • Facilitate classification and clustering of structured and unstructured data; filtering of stock recommendation reports for suitability; and unstructured data processing including real time events capture, NLP, and sentiment analysis FRAMEWORK USE CASES

33. FRAMEWORK USE CASES

34. Recommendation framework that combines structured and unstructured data to provide contextual information summary, along with investment recommendations. The framework should facilitate classification and clustering of structured and unstructured data; filtering of stock recommendation reports for suitability; and unstructured data processing including real time events capture, NLP, and sentiment analysis. The framework should include a customizable dashboard to enable the portfolio manager to make smart decisions. The dashboard should allow configuration of some of the preferences like sectors, demographics, and so on. FRAMEWORK USE CASES

35. News and event analytics: The solution framework should gather all relevant news and events from various sources like analyst websites, blogs, and research firms, and perform analytics on them. Some of the news and event analytics that should be performed are: Event categorization: Classify news into opinions, press release, blogs, analyst views, credit rating, and provide a timeline summary of published items.Event relevance: Provide features like entity tagging (people, company, government bodies, and others); stock, sector, and geography relevance for wealth manager portfolios; novelty rating (as the first instance of news creates greater impact); news volumes (list of sources offering similar news and opinions); and events alert calendar. Event impact: Facilitate impact-mapping based on the type of risk, and corresponding impact such as high-risk (bankruptcy, CEO-related, and others) and high-impact (mergers and acquisitions, regulatory actions, divestments). FRAMEWORK USE CASES

36. Historical event analytics: Perform historical analysis of events against stock performance for the past and present timelines. Appropriate visualization tools need to developed to present interactive graphs, charts for stock performance with regard to holdings, external news, and events so that they are easily interpreted by portfolio managers. Firms also need to implement NLP-based search and query facilities. FRAMEWORK USE CASES

37. With Changes in demographics and customer expectations, tighter regulations, disruptive digital technologies, and rising competition from fintech companies firms will need to customize their solution as per their asset management and investment strategies. Firms must also consider their data and supervised learning requirements, and model accuracy while choosing the solution. Embracing newer technologies such as AI and machine learning will help them unlock the value of data to drive informed decision making, which is imperative to business growth. CONCLUSION

38. END…. DEMO PRACTICAL