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A Better Way v Vertis

How Better Mortgage, a Mortgage Processing and Services Company, Turned to an Innovative AI Solution to Fuel its Rapid, Distributed Growth

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1. Summary

Launched in 2016, Better Mortgage is a company that allows U.S. consumers to take advantage of modern, disintermediated processes and an improved supply chain when procuring a mortgage. It competes on higher-quality, technology-enabled services that support reduced prices, and has expanded considerably in an industry where most competitors are locked into established and comparatively inefficient practices, processes, and technology platforms. Better Holdco, Inc. (“Better”) is Better Mortgage’s parent company and employs more than 7,000 employees globally. It has a real estate portfolio of office sites in the U.S. and India.

2. Case Study

Challenge

Better was growing rapidly even before the pandemic, experiencing a dramatically increased need for new employees across all roles, due to expanding market opportunities. The company wanted to hire from beyond its existing locations to gain access to a wider pool of talent and to improve alignment of its workforce with an increasingly diverse customer base.

At the same time, Better was considering how to form its new hires into teams across different disciplines, and how that would affect the office locations in which they worked. Complicating matters was the migration of existing and potential employees out of cities in the wake of the pandemic. The company wanted to ensure that corporate decisions would not impose undue costs on employees faced with a dynamic housing market.

Beyond hiring and relocation, Better understood that its efforts to improve hiring could also inform customer-related insights and enhance services.

The problem: The sources of information Better had for supporting this planning were brittle, falling short in terms of both accuracy and timeliness.

Solution

Better had already investigated relevant services from consulting companies and brokerage providers, but found that these were static and insufficiently transparent. The option of establishing an in-house team of specialists to build software and perform data analysis was considered but deemed too risky and expensive compared to other options.

The company found Vertis, an artificial intelligence company that promises “better decisions based on data,” via a referral from an existing customer facing similar challenges. After a demo and trial of the product, Better not only realized the value of the data Vertis includes in the platform, but was also able to import internal employee data to drive additional insights. Some examples of external data sourced and analyzed by the Vertis solution include:

  • Talent pool analysis with information about employment levels and wages in specific occupations
  • Population and migration metrics, including demographics and diversity
  • Commercial real estate data on office costs across markets
  • Economic data and housing trends

The Vertis platform uses data from a range of sources, both public and private, including government databases and alternative sources such as web crawlers. The company’s proprietary data-ingestion pipelines capture raw data from all these sources, then consolidate and feed it into a machine-learning model.

One key aspect of the Vertis platform is a market recommendation engine. The underlying ML model is trained with relevant data to calculate a score for each market based on customizable filters and importance weighting. The output is a scored and ranked list of markets based on the user’s custom settings. The model is further dynamically trained to continuously provide real-time customizable results.

Result

The Vertis solution helps Better analyze information in real time, at times providing answers to questions the team never even thought to ask. This kind of serendipitous discovery has proven rewarding, even as the solution’s versatility enables ad hoc exploration. For instance, the team has applied segmentation to compare different datasets according to employee types or city location types (using data from city authorities). It also helps with deeper data analysis into labor movements across demographics.

The result has been a change in the decision-making framework at Better, where discussions today are driven by empirical data and analysis, rather than hunches and opinions. Decisions are being made ahead of the curve, because they are no longer bogged down by spurious or aging assumptions.

That clarity has enabled Better to be more decisive and confident in executing decisions. In fact, the company adopted an agile approach specifically to maximize the leverage it was getting from new data sources and analyses.

“The better informed we can be as a company, the more competitive advantage we have in the market,” says Richard Duff, Director of Real Estate and Workplace Services at Better. “And while you might not win solely on the basis of a labor-related strategy, you could definitely lose if you got it wrong. Trying to launch in a market where there just isn’t enough talent to support your goals or headcount targets is not likely to succeed.”

There have been indirect benefits as well. For example, a broader geographic workforce distribution means staff are more likely to be aligned and in touch with their diverse potential customers. This in turn should facilitate more wide-ranging considerations in the company’s decision-making. It should also improve business resiliency by helping counter local environmental risks and other threats, such as attacks or other disruptions.

Lessons Learned

The data visualization provided by the Vertis solution has helped Better directly share results with decision makers. The leadership team has more time to discuss trends within the labor market and workforce, and those discussions are informed by more current and insightful information than would otherwise be available.

Deploying the Vertis solution has increased collaboration between business units. And this is certainly advantageous, especially in an “open” culture where people are receptive to having their assumptions questioned and increasing their level of understanding.

In order to maximize the advantages of the information made available by Vertis, companies may have to increase their ability to act quickly upon improved insights.

“Without a platform like Vertis, the datasets you’re getting typically update annually or quarterly, and then you’re doing an analysis to understand them, which also takes time,” Duff says. “As any analysis that you’re doing might be quarterly, you’re probably at least three to four months out of date at any given moment.”

Since teaming with Vertis (www.vertis.ai/), Better has consistently reduced that feedback loop via the integrated data streams it receives from the platform.

3. About Anand Joshi

Anand Joshi

Anand Joshi is a semiconductor industry executive with more than 25 years of experience. He is a recognized artificial intelligence expert and analyst. His reports on computer vision, artificial intelligence, infrastructure, and chipsets have been used by top semiconductor and OEMs for strategic planning purposes, and he has also worked with several prominent AI chip companies, including NanoSemi, Wave Computing, and Redpine Signals. Anand has built state-of-the-art AI chipsets and vision-based software analytics products, and worked with Tier One customers in consumer, automotive, and enterprise markets to understand and implement AI products per their needs.

4. About GigaOm

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5. Copyright

© Knowingly, Inc. 2021 "A Better Way" is a trademark of Knowingly, Inc. For permission to reproduce this report, please contact sales@gigaom.com.