A Nexus of Complexities Facing Mortgage Leaders

The politics of innovation and technology are dramatically altering discussions and selection processes.  Creating optimal strategies and deploying efficient, learning solutions requires identifying new demands, requirements, and data differentiators compared to traditional BAU.

In a year of presidential politics, the sound bites never seem to end—or become more pointed.  Prior cycles, while sharp and cutting based on ideology, have now enveloped rapidly emerging innovation and technological advancements.  From Tik Tok to artificial intelligence (AI) to privacy to cybersecurity, innovative advancements have pushed the boundaries and the potential impacts on workers, skills, software, products, services, and rights. 

State and Federal (executive) orders and legislation surrounding ethically sourced data, its manipulation, and its sharing has led to a patchwork quilt of compliance demands directing challenges to First Amendment rights and business model efficacy.  Moreover, will the challenges to traditional modes of operation improve the estimated $2 trillion in home originations for 2024 (e.g., per loan margins or yield greater unit sales)? 

Currently, when it comes to AI it is both an angel for efficiency projected to add trillions in USD to economic growth and insight, and a data-driven demon that is opaque, eliminates jobs, and threatens living standards.  When examining the impact to mortgage per loan margins, the reduction of a single person hour spent during the origination cycle can yield $110 to $140 per loan, embryonic solutions of ML, AI, and neural network innovation hold both great promise and fear .  For mortgage firms struggling with a four-decade low in housing affordability, availability, and volume, every margin improvement is critical to survivability. 

Therefore, what approaches could be utilized to “depoliticalize” critical, future solution sets (e.g., AI, DaaP, multimodal architectures)?  There is not a “one-size fits all” solution as it is dependent on demographics served, infrastructure deployed, and skill sets available.  To understand and assess organizational options for innovations and technologies that will continue to be politicalized, organizational leaders must change their approaches to how innovation is adopted, adapted and improved.  Unlike the system ideations based on process automation of paper-based systems, these next-generation of data-driven solutions must:

  1. Recognize the critical challenges facing traditional processes and implementations (see Table 1),
  2. Map the challenges against business model shifts that will be forthcoming regardless of politician and media “facts” (see Table 2),
  3. Break out the impacts across three macro mortgage processes—origination, servicing, and securitization (see Tables 3, 4 and 5 respectfully) as part of prototyping, piloting, and scaling for production, and
  4. Develop iterative roadmaps of action and implementation using short bursts of activity (e.g., Agile) to incrementally deliver the necessary outcomes and desired results.

The methodology used for the above is (AI)2 (Adjust, Innovate, Action, Iterate) surrounding distinctive use cases as it represents a next-gen approach to adopting data-driven solutions that have robust impacts (i.e., AI).  The design and deployment of (AI)2 delivers the industry data differentiations which will be downfall for many enterprises as they rush to move siloed innovative pilots into scaled production systems impacting crosslinked critical controls within legal, auditing, and regulatory compliance.

For the complete article including the referenced tables, please see –> https://newslink.mba.org/mba-newslinks/2024/may/mba-newslink-wednesday-may-29-2024/a-nexus-of-complexities-facing-mortgage-leaders-mark-dangelo/?utm_campaign=MBA%20NewsLink%20Wednesday%20May%2029%202024&utm_medium=email&utm_source=Eloqua