Servicers: It’s time to improve decision-making using predictive modeling

HousingWire recently spoke with Yvette Gilmore, senior vice president of Servicing Product Strategy at ServiceLink, about the challenges of portfolio management in the current environment and how machine learning can help servicers streamline the asset-decisioning process.

HousingWire: What are the current challenges of portfolio management for servicers?

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Yvette Gilmore: While servicers are always concerned with mitigating risk, streamlining operations, minimizing losses, reducing costs and elevating the borrower experience, today’s extraordinarily active marketplace is truly putting them to the test in each of these areas. Those whose portfolios are growing in number and/or the variety of properties face the added challenge of managing this new influx without slowdowns or errors.

From a risk management standpoint, servicers want a rules-based approach in every aspect of their operation. They are seeking to not only facilitate their decision-making processes and comply with evolving regulations, but also ensure a level of consistency and certainty for the customer. Customers rely on servicers for fast, transparent, well-informed decisions, and for consistent answers and results regardless of the company representative they may speak with. 

HW: How does EXOS One Marketplace help servicers streamline the asset decisioning process?

YG: Technology and transparency come together in ServiceLink’s EXOS One Marketplace to support servicers and investors in makingfaster, better-informed asset decisions. From their desktops, they can see their entire portfolios at a glance, monitor and manage properties throughout their lifecycles, compare disposition options, and adjust their strategies as new information becomes available. 

Behind the curtain, machine learning and artificial intelligence replace traditionally complex manual processes to identify optimal disposition paths. Given servicers often consult as many as seven different systems and have conversations with up to five different peers in the process of decisioning a single asset, EXOS One Marketplace can offer dramatic reductions in time, cost and effort.

I should point out that EXOS One Marketplace eschews the one-size-fits-all approach of many technology platforms available to servicers today. We can tailor this decisioning tool to integrate with each client’s unique business rules. Our goal is to help servicers and investors manage timelines, reduce losses and lower costs as effectively as possible, and determine the best disposition paths for mitigating risk and maximizing returns.

HW: What are the benefits of applying machine learning and analytics to servicing technology?

YG: Machine learning and analytics open the door to more rapid and confident decision-making. In the past, servicers needed to base their decisions on their own historical information and best practices. Today they can rely on machine learning that essentially takes in and processes massive amounts of data from a variety of sources to produce a new level of intelligence. Machine learning can streamline the evaluation process by identifying patterns that enable it to predict outcomes under various sets of circumstances.

Thanks to machine learning and analysis, EXOS One Marketplace can, for example, predict how a specific property might fare at auction or in the CWCOT second-chance program, or what level and cost of repairs a particular property might require if held for a certain period of time. The system continues to learn from each of ServiceLink’s clients so that it can continually improve the quality and precision of predicted outcomes. It also collects historical operational data from our field services and title companies to improve the claim and decision-making processes.

HW: How does EXOS One Marketplace maximize visibility of assets throughout the entire default lifecycle?

YG: Being able to see all portfolio assets, as well as their various disposition paths, at once can be a tremendous advantage for servicers and investors. EXOS One Marketplace pulls the disparate data required for decision-making onto one customizable desktop view that enables the user to personalize their dashboard with graphs and other helpful elements.

Predictive modeling enables users to tap into deeper visibility, as it shows them the potential effects of various decisions. By simulating an outcome on an asset based on a decision they could make today, the servicer can evaluate whether that decision would improve the outcome or lead to losses. Said another way, users can literally see the impact of today’s decisions on tomorrow’s outcomes.

This is game-changing, because servicing on its face is simple: There’s an asset, and it needs to be managed. But there are a host of incremental decisions that could make consequential impacts on the ultimate outcome. EXOS One Marketplace enables the user to see those potential impacts today.

The EXOS One Marketplace platform also improves the level of transparency to senior leadership, offering visibility into losses within the portfolio as a whole or at the individual asset or aggregated zip code level.

Through EXOS One Marketplace, ServiceLink strives to provide servicers and investors with technology and services that make managing their assets easier. Our technology informs their decisions, streamlines their processes and provides them with the foundation for a consistent, exceptional client experience.

The post Servicers: It’s time to improve decision-making using predictive modeling appeared first on HousingWire.

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