“Playing Chicken” with the Data Freight Train
The “mastery” of data is not about how much you capture, how large your data warehouses or lakes become, or the native cloud provisioning solutions you deploy—it is about creating, sustaining, and utilizing a data supply chain already being deployed by non-traditional lenders. To think otherwise is akin to “playing chicken” with a freight train—hoping somehow it will veer from its tracks and spare you.
By Mark P. Dangelo
The complete article and graphics can be found at –>Mark P. Dangelo: Playing Chicken with the Data Freight Train – MBA Newslink
In 2022 when interest rates touched 7% right before the MBA Annual Conference, optimism among the participants was high that these rates were an aberration—not the norm for the industry’s future. Yet in 2023, inflation continued to grow, the Federal Reserve maintained its promise to raise rates, and the consumer paid greater percentages of their income for home ownership. A year later, affordability dominates buyer’s decisions with mortgage lenders experiencing shrinking margins and declining volumes.
Additionally, it was during the 2022 Annual conference that I released “Adapt or Die: The Reimaging of the Mortgage Industry” at the request of the MBA. It was a comprehensive future look at the impact that digitalization was going to have on growing digital products and services, which under the microscope of tradition, lacked volumes and were uniquely distinct from commodity driven profit margins.
To put a finer focus on events and discussions a year later, interest rates are now the highest since 2001, volumes projected for 2024 will contract to levels not seen since 2011, and a recession is likely in 1H 2024 (see Business Insider / Fannie Mae, September 23, 2023). So, what is next? What strategy, operational improvements, or competitive differentiation should bankers and lenders (BL) embrace to survive 2024-2025 market conditions? What needs to change especially when it comes to innovation, data, and systems?
The key to survival for many leaders will be a fundamental shift from BL process ideation and implementations (e.g., LOS, AVM, consumer) to data-discovery, ingestion, and reuse to fuel efficient ML and AI across-process solutions. Indeed, the industry is being reimaged.
What’s in Your Data?
Across financial and lending groups, the growth of cloud capabilities since the Great Recession exploded—growing over 50% per annum. It was in part fueled by extensive demands to deal with regulations, complexity of operations, customer requirements, and the exponential growth of FinTech solutions all underpinned by housing demand and a pandemic. Today, the provisioning of off-premises computing and storage capacity is straightforward—thanks to the rise of AWS, Snowflake, and Azure.
Yet the ability to reuse data, to ensure linkages back to the auditable systems-of-record (SOR) was discounted as the tools and methods to replicate, manipulate, and iterate data all without capital budgets or complex utilities become ubiquitous. With data capture and storage doubling every 18-24 months, designers ignored the requirement for auditable SOR’s. That is, paths of data lineage which cannot be traced back to their original sources.