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Using Rapid Analytics to Find and Keep Customers

Using Rapid Analytics to Find and Keep Customers

Mortgage lenders today face daunting challenges. Despite a recent rate-driven surge in refinance activity, overall origination volume is sluggish and costs remain high. While falling rates and easy access to refinance pushed Q2 2019 retention rates up significantly, overall customer retention remains relatively anemic, particularly among cash-out refinances. Together, these challenges are contributing to lenders’ declining profit margins, making it more critical than ever to find creative, cost-effective ways to gain and retain customers.

With a tight housing supply and the majority of mortgage holders having coupons lower than today’s prevailing rates, finding first-lien mortgage and refinance candidates – let alone qualified ones – is difficult to say the least. How can mortgage institutions hold on to the customers they have and acquire new ones?

data over city

A Universe of Data

We live in a world inundated with data, and the mortgage industry is certainly no exception. An abundance of valuable, relevant data is available to help improve lenders’ growth and retention strategies. Origination and servicing data, MLS information and public records can all be combined to yield significant, actionable intelligence about customers and prospects. Likewise, housing market data – home prices, equity positions, market activity, etc. – can provide insight into areas of both risk and opportunity, and do so at a granular level.

The challenge is organizing incredibly vast data sets in a way that makes them available for modeling and other advanced analytics. Even under the best of circumstances, this has proven to be a very complex, costly and time-consuming process.

At Black Knight, our data scientists faced these challenges on a daily basis. In fact, we scoured the marketplace to find a tool that would help us wrangle the terabytes of mortgage and housing data we work with into useful information. Such a tool simply did not exist, but that didn’t change our needs – so we built one instead.

The result is our Rapid Analytics Platform (RAP) – a “virtual lab” for organizations working with big data and complex analytics specifically around housing-related assets – and which we now offer to clients. RAP provides a lender’s data scientists and analysts a powerful, seamless workspace to source data, execute queries, create advanced analytics, and train machine-learning models.

As a cloud-based tool, RAP provides massive computational power, significantly reducing the time, effort and cost required to analyze large data sets and apply advanced analytics. It transforms the way lenders can leverage information by allowing decisions to be made based on the entire universe of available data, rather than sample sets. RAP’s real-time, high-speed processing delivers instant results ­– even for the most complex uses – transforming the way mortgage industry professionals work with big data.

No Wrangling Required

Data in RAP is production-ready; all of Black Knight’s diverse and comprehensive data sets are loaded and ready to go. These include public property records covering 99.9% of the U.S. population, MLS listings, our industry-leading, loan-level mortgage performance data, Black Knight’s Home Price Index (HPI), and AVMs. RAP also provides access to our advanced predictive analytics and pre-built models, which are indispensable in developing effective growth and retention strategies. As all of these datasets exist “under one roof,” they can be intermingled at the property level in a way that today’s siloed datasets makes all but impossible.

With RAP, users can also upload and merge their company’s proprietary data, as well as external data, then apply analytics to the combined set with Black Knight data. In addition, since RAP supports multiple programming languages – including SQL, R, Python and Scala – any model currently used by a firm can be deployed within the RAP environment – maximizing existing investments.

The speed with which analysts and data scientists can explore multiple scenarios, see results, change parameters and then re-run whole scenarios in RAP is unparalleled. It not only helps teams of data scientists work faster and more efficiently, it also provides an affordable way for mid-sized and smaller companies in the industry to access big data and complex analytics. This virtually “plug and play” platform eliminates the need to build out massive infrastructure, so users can deploy it immediately.

Using RAP for Growth and Retention

RAP provides numerous ways for a bank to develop more effective growth and retention strategies. For example, a bank could run its portfolio of retail, non-mortgage customers against the Black Knight Propensity to Transact Model within RAP. The model merges the bank’s data with public record information, MLS data and AVMs to identify candidates for a refinance or home equity loan.

Since not all leads are equal, the model goes even a step further. To find the best possible prospects, users can input additional data sources as they choose. For example, they can use the extensive household-level demographic data we offer, as well as our HPI, to take into account factors such as changes in household status and local market conditions. This helps pinpoint potential “move-up” or “move-down” buyers in growing markets, enabling a lender to focus its resources on targeting the consumers most likely to transact.

On the servicing side of the house, a client can apply the Propensity to Transact Model to its mortgage portfolio for quickly identifying cash-out refinance or home equity prospects. The user is able to rank these candidates leveraging Black Knight Mortgage Scores, which uses such factors as borrower behavior patterns, economic conditions and equity position to identify customers most at risk for attrition.

Armed with this type of information, banks are able to foster the customer relationship well in advance and work to capture that customer for a refinance, new mortgage or equity loan before the competition does. Outputs can feed downstream actions such as client call lists and outreach programs.

Using RAP, lenders can also easily leverage Black Knight’s advanced run-off analytics to mitigate attrition. These analytics tell lenders why, how and to whom they are losing their loans, from both their origination pipeline and their servicing portfolio. Some of the most relevant data returned includes pay-off type, new loan type, interest rate and lender.

Given this data, a lender can create a profile of likely runoff candidates and develop strategies to prevent future run-off. The user could also slice and dice the data by geography and financial institution, then segment the data and identify the competitive product offerings that are causing their customers to leave. The lender could use this intelligence to provide products that prevent these companies from further poaching its portfolio.

Endless Possibilities

Using RAP, clients have a unique tool that arms them with the information needed to develop timely content and relevant offers, better focus their resources, and use sales and marketing funds more effectively. In addition to improving growth and retention results, mortgage professionals can also leverage RAP for many other purposes. From risk management and portfolio research – to economic modeling, benchmarking, and investor reporting, RAP supports an unlimited number of use cases.

RAP enables faster, more agile decisions for mortgage professionals to keep up with changing market conditions and trends. By delivering computational power an order of magnitude greater than what most firms have in-house, RAP is also democratizing access to big data and analytics – allowing mid-sized and smaller lenders to get in the game. The fact that RAP does all this without requiring millions of dollars of infrastructure and development costs makes it a game-changer for the mortgage industry.

To learn more about Black Knight’s Rapid Analytics Platform (RAP), watch this video.

Media Contacts

Michelle Kersch 904.854.5043