Utilizing Advanced Technology in Asset Management By Katherine Baunach We seem to have found ourselves at an “era crossroad,” and no, I am not referring to Taylor Swift’s tour and the struggle to find tickets. There appears to be a consensus that we are exiting the Information Age, once defined as the ability to generate, access, and control information, which occurred after shifting away from more traditional industries and practices established during the Industrial Revolution. With this change, the Age of Artificial Intelligence, Machine Learning, and Data Creation is very much present in our daily lives. However, we are at the very infancy of these technological advancements. This then begs the question: how can we implement and weave this new technology within the asset management lifecycle and our subsequent decisioning practices to drive efficiency and execution? Evolution of Technology The evolution of technology is well documented within the asset sector. The use of proprietary and third-party property management and disposition platforms have been a best practice for 25+ years. As we migrated to cloud-hosted, web-based applications, we saw developments to stimulate operational efficiency via the implementation of integration capabilities between systems via methods like APIs (application programing interface). Additionally, stronger rules engines were introduced to assist in automated workflow through a series of “if, then” scenarios to further staff capacity and support portfolio scalability. As these operational concepts were well past their implementation phase, the next advancement focal point surrounding third-party data integration was to strengthen analytics. The ability to interface with or aggregate market and multiple listing service (MLS) data, home price forecasting data, and various key municipal data came to the forefront. Subsequently, this led to normalizing these data points and presenting them in a way to help make the decisioning process more streamlined when determining optimal performance on executing an investment or management strategy across a portfolio or at an asset-level. What’s Next? Tying back to the original proposition, where and how can we layer in newer forms of technology — specifically, machine learning and artificial intelligence — and who will create this standard? Embedded within Guardian Asset Management’s ecosystem is a successful marriage of its various service pillars, including asset disposition, property management, renovation, maintenance, preservation, evaluation, and title services. The two former pillars – asset disposition and property management – have tremendously benefited from Guardian forging deep partnerships with leading machine learning and artificial intelligence firms to not only support several operational initiatives, but to layer various proprietary developments into its technology infrastructure designed to support strategic decisioning. Many assets under management face simple strategic questions, such as, “Is this part of a long-term strategy via a rent and hold management path, or is this part of short-term strategy by leveraging a strategic disposition management path?” While this decision is often made during due diligence, circumstances can often subsequently change due to various factors such as the aggregation of additional data. Layered under the broad management path decision are complex methodologies and critical data points that will help asset managers arrive at what drives optimal execution. For example, the decision to liquidate might be easy to determine based on the asset’s characteristics or due to the lack of additional velocity in a given market. Should the decision be made to liquidate, critical data must be obtained and analyzed to determine how to best execute the plan since various disposition options are available. There are a few avenues that one can evaluate as the conveyance strategy once liquidation is the determined route. These options include As-Is, Repaired, Auction, Deed-Away, Donation, and Occupied Sale. Historically, the determination of which path to choose required a seasoned asset manager with access to several data points. Today, the use of modern technological concepts layered upon years of experience and data analytics, will drive asset owners to make faster, logical, and more optimal decisions. The following are several key developments Guardian has made in the asset management sector: AI-Driven Apps // As we have progressed through developments in technology, Guardian has been able to better aggregate data on assets. A constant variable has always been a property’s true condition as that is often subjectively interpreted. Guardian, through proprietary developments, has application technology that helps close this data gap, turning photographs of a subject into data points, which is then layered by artificial intelligence. This allows us to better identify risks, flaws, and opportunities associated with a property that can be addressed through renovation or repair practices, while also directly tying costs and timeline projections to the analysis. Asset managers are now provided with more data in real-time and with less resources to make critical decisions instantaneously. Integrated rule engines within management platforms can then drive subsequent tasks and directives, creating more capacity for each asset manager. Decisioning Tools // Complementing the above, Guardian has critical-decisioning tools layered within its operations to better assist its clients and investors on generating optimal results. Properties are analyzed either from a risk perspective or opportunity perspective. However, the data and analytics reviewed are often the same for each perspective. By integrating decisioning points from various sectors of our industry, ranging from approaches utilized by private lenders, mortgage servicers, and investors, we’ve been able to better apply this advanced technology to help identify the best execution plan faster and with higher confidence. As asset owners, sensitivity to time is critical, which is a driving initiative behind these applications. Strategic Integration // The heartbeat of our ecosystem that ties our diverse services together is technology and the ability to integrate our various applications and platforms. Through strategic dashboards and interfacing, we’ve studied the critical data that drive asset decisioning and present our analytics to the decisionmakers, be they internal associates or external clients, effectively offering streamlined transparency without overstimulation. Guardian continues to not only embrace technology but is a leader in its application as we head into a new era. By helping support technology’s development and implementation, we are able to drive continued advancement within the