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Rapid Analytics and the Capital Markets

Rapid Analytics and the Capital Markets

Buy, sell, hold. Three concepts that seem simple and straightforward enough. But – as anyone who makes their living in the high stakes world of capital and secondary markets is well aware – the decision to buy, sell or hold is anything but simple. An incredible amount of information gathering and assessing goes into making an investment decision. Dealing with pools or portfolios of real estate or mortgage-related assets requires even more information. Or at least it should.

The fact of the matter is that many of the in-house analysts and data scientists tasked with informing these decisions are trying to do so with one arm effectively tied behind their backs. The tools they’ve historically used – spreadsheets, data dumps, models fueled by lagged information – are simply unequipped to perform at the level today’s big data-driven markets demand.

Firms hire teams of analysts to pore through and hopefully mesh those spreadsheets and data dumps together to produce a coherent outcome that helps them make the right buy or sell decision. The stakes are high, and missing critical elements can be very expensive. Today, advances in cloud-based computational power mean that you can – and should – make decisions with the largest and best universe of data available.

Of course, that requires the tools to operate in this new reality.

Information is the Foundation

Decisions are ultimately only as good as the information that drives them. If one piece of information related to a trade is wrong, it can mean the difference between a profit and a good profit; or worse, between profit and loss. That means you must start with best-in-class data sources. Capital markets investors in the housing and mortgage space have a very particular need for very particular information, and Black Knight is by far the superior source for that data.

From nationwide MLS listings to our industry-leading McDash loan-level mortgage performance data, to public property records covering 99.9% of the U.S. population, Black Knight’s datasets are indispensable for those working with housing assets. Our Home Price Index (HPI) covers more than 20,000 ZIP codes nationwide, with a granularity unmatched by even our closest competitor. Likewise, the analytics and models we produce – based upon deep industry expertise – can be indispensable in making informed portfolio and trading decisions.

But raw information isn’t enough. Or rather, it’s often too much. When you’re dealing with massive data sets (McDash alone provides over a hundred data fields on more than 170 million current and historical mortgages – let alone the gargantuan size of Black Knight’s public records database), the sheer volume of information can be both invaluable and incapacitating without the right tools.

At Black Knight, our data scientists faced this reality on a daily basis. We needed a tool to wrangle the terabytes of data – the very specific mortgage and housing data that we deal with every day. Despite scouring the marketplace, we could not find an existing tool that fit the bill.

So we built it.

A Unique Virtual Analytics Lab

The result is our Rapid Analytics Platform (RAP), a virtual lab for those working – in capital and secondary markets and elsewhere – with big data and complex analytics around housing-related assets. For those tasked with making or informing buy, sell and hold decisions around these assets, RAP is nothing less than a game-changer.

RAP gives data scientists and analysts access to all of Black Knight’s extensive data sets, as well as our automated valuation models (AVMs), advanced analytics and behavioral models, all from within a unified, powerful workspace. This single, seamless environment also lets users upload and merge their own proprietary data and other external data sources and apply analytics to the combined set. Whether the use case is modeling or benchmarking, RAP provides the ability to run scenarios and make assessments based upon all of these varied data sources – in one spot – efficiently and less expensively. There is no need to build out a massive infrastructure, because it’s already been built.

RAP is reflective of a world where there’s no longer a need to use sample data and extrapolation to produce an analysis. Rather, the entire universe of relevant information can be brought to bear on creating or recalibrating models, gaining actionable intelligence to help identify and capitalize on opportunity, and mitigating portfolio and trading risk.

In practice, those on the buy side with a limited time window to make a decision can use RAP to examine all of the available data, and distill the necessary information to decide whether it makes sense to bid or pass. Conversely, sellers are able to create pools for market with information that could become transparent to potential investors and hopefully make for a more robust auction or sales process.

Agnostic Power and Flexibility

RAP is code agnostic, allowing a firm to use any models already being used, as is, within the RAP environment. SQL, Python, R – whatever codebase a team of data scientists has been working with can be imported and used in conjunction with all of the easy accessible data sets the platform includes, maximizing any existing investment as well as the reach and scope of the models themselves.

Since both the data and the code execution are live – and powered by the massive computational power afforded by cloud computing – data can be pulled, models run, results reviewed, then tweaked to change parameters and run again, in real time. The ability to consider multiple scenarios on the fly adds a degree of informed expediency to buy, sell or hold decisions that has simply never been available in this market.

The flexibility RAP affords also insures that whatever specific approach to the secondary markets a given analyst or team employs stays valid, functional and independent. Independence is critical for secondary markets analysts to develop a unique approach – not only to gain a competitive edge against competitors, but to differentiate internally as well. RAP allows them to maintain that independence and develop unique strategies for each unit within the firm, as well as against their competitors.

Something for Everyone

That’s what makes RAP so useful across the enterprise. It is of obvious use to the modeling group, but also to someone at the trading desk, or someone enabling and insuring the originations markets. Each of these users will have different purposes and goals in analyzing large amounts of data, but RAP brings all of these use cases and groups under one umbrella. RAP enables better performance across the board: from research, to trading, to due diligence, to quality assurance and portfolio valuation.

All of the many decisions made on a day-to-day basis for those involved in the capital and secondary markets present opportunity and risk. RAP provides the tools and information to discern one from the other and make the best moves determined by the best data at the optimum moment, and puts them in the hands of those who know what to do with that insight. The fact that RAP does so without requiring millions of dollars of infrastructure and development costs is by design. As is ensuring that your experts are informed and forearmed, not shoehorned into a ‘one-size-fits-all’ approach to data and analytics.

Media Contacts

Michelle Kersch 904.854.5043
Mitch Cohen 704.890.8158