Mortgage data vendor uses Qlik to build analytics platform

Mortgage data vendor uses Qlik to build analytics platform

Wanting a solution to get pertinent records within the fingers of decision-makers all over the loan trade, Polygon Analysis used embedded analytics features from Qlik to construct a chain of SaaS packages.

Based in 2015 and founded in Washington, D.C., Polygon Analysis is an impartial tool supplier that develops records merchandise for the loan industry. The seller collects records disclosed by means of lenders and regulatory businesses, integrates and prepares it prior to plugging it into records science fashions, and develops analytics gear together with experiences and dashboards that purchasers use to tell choices.

Qlik, in the meantime, is a full-featured analytics supplier whose gear can be utilized all over the analytics pipeline, from records integration thru research and perception, and are geared toward leading to data-informed movements. Maximum lately, the seller introduced Qlik Cloud Information Integration, a cloud-based records integration platform as a carrier.

The issue

The loan trade depends upon records to force key choices.

Every mortgage applicant carries inherent possibility of default, so lenders use records to scrupulously read about whether or not a given applicant is most likely sufficient to pay their mortgage to make it definitely worth the possibility of lending cash to that applicant. As well as, each the secondary loan marketplace, the place mortgage servicing rights are purchased and bought, and the mortgage securitization procedure, the place loans are packaged and traded as securities, rely closely on records.

Loan records, alternatively, is voluminous and remoted in spread-out records assets, with mortgage originations in the USA totaling $2.7 trillion in 2021, consistent with the Federal Nationwide Loan Affiliation — regularly referred to as Fannie Mae — and greater than 4,500 lenders national that do not proportion records with one any other.

Information comprises key details about laws, debtors, actual property agents and businesses, and houses.

Mortgage data vendor uses Qlik to build analytics platform
Polygon Analysis CTO Greg Oliven speaks all through a webinar hosted by means of Qlik.

“The loan trade is relatively massive, and there is numerous worth at stake,” mentioned Greg Oliven, CTO at Polygon Analysis, on Nov. 30 all through a webinar hosted by means of Qlik. “The trade’s records is huge and unwieldy, which we name the last-mile drawback, which is how finish customers unencumber the price contained in [the industry’s] records units.”

So, in 2018, Polygon Analysis got down to construct a collection of packages that unencumber the price contained within the loan trade’s huge records units and make mortgage-related decision-making extra instructed.

Lenders, servicers and traders had their very own historic knowledge to tell choices, but when they sought after broader context, they needed to comb thru exterior records themselves and broaden records merchandise on their very own.

Some higher organizations would possibly have had the assets to take action, however that wasn’t the case for all mortgage-related enterprises. Or even for people that did have the assets — together with records scientists and monetary capital — accumulating records from disparate assets, modeling the information and growing analytics gear from the information is a time-consuming procedure.

We now have got down to remedy the issue of unlocking the price contained in trade records units.
Greg OlivenCTO, Polygon Analysis

Polygon Analysis, due to this fact, aimed to take away the burdens of information control and knowledge preparation from particular person loan enterprises and supply them with records merchandise that result in insights.

“We now have got down to remedy the issue of unlocking the price contained in trade records units,” Oliven mentioned.

The solution

To handle the desires of loan lenders and traders, Polygon Analysis used Qlik’s analytics platform to construct the Polygon Analysis Platform, which is composed of a chain of packages replete with embedded records that consumers can subscribe to as a carrier and use to tell choices.

To begin with, Polygon Analysis selected to make use of gear from a supplier as opposed to Qlik, although Oliven declined to call the analytics supplier. Qlik has a large number of competition, together with embedded analytics consultants like Logi and Sisense, records integration distributors together with Informatica and Talend, and full-featured analytics distributors comparable to MicroStrategy, SAS and Tableau.

In keeping with Oliven, the platform that Polygon Analysis to begin with selected could not scale to fulfill the seller’s wishes. So Polygon Analysis as a substitute grew to become to Qlik. And the use of Qlik, the seller constructed the Polygon Analysis Platform.

“We switched horses and not seemed again,” Oliven mentioned. “We went with Qlik on account of the scripting inside Qlik Sense, and the scalability and cloud tale.”

Qlik gear that Polygon Analysis used to broaden its mortgage-specific analytics platform come with the next:

  • the Qlik Associative Engine as the bottom for construction packages with more than one use circumstances comparable to gross sales, compliance and automatic device studying;
  • Qlik’s in-memory type to permit velocity regardless of the massive quantity of information contained in every utility;
  • Qlik Cloud to construct a scalable platform that may deal with much more records because it is available in from present assets and new ones that would possibly get up;
  • Qlik’s automation engine to create scheduled experiences and replace records units with new knowledge; and
  • low-code/no-code features to permit simple construction by means of Polygon’s builders and finish customers to simply discover the information in every utility.

“[Qlik] has an impressive interface that we in reality like,” Oliven mentioned. “It is a ‘write as soon as and leverage many’ more or less atmosphere.”

He added that Polygon consumers don’t have to be Qlik consumers to devour the guidelines within the Polygon Analysis Platform. But when they’re joint consumers of each Polygon and Qlik, it complements their revel in.

“We’re ready to empower our purchasers throughout the interface with out them desiring to be a Qlik shopper, however it is all the time nice if they’re [a Qlik client] as a result of they may be able to leverage their figuring out and funding within the atmosphere,” Oliven mentioned.


In the end, Polygon Analysis used analytics features from Qlik to construct 9 interactive dashboards — every embedded with a large number of records units that routinely replace — making up the Polygon Analysis Platform.

Consumers can subscribe to as few as probably the most 9 dashboards, some aggregate of them or they all. Pricing for Polygon’s quite a lot of dashboards levels from $1,499 yearly for CensusVision and FHAVision to $7,299 consistent with yr for SPCP (Particular Function Credit score Program) Analytics-in-a-Field.

The 9 dashboards Polygon Analysis evolved are designed to provide consumers what the seller calls an built-in framework instructed by means of records.

They come with records units that permit customers to compete with friends on the native degree, together with the advance of a gross sales technique; determine new markets and segments inside markets to spur enlargement; put into effect variety and inclusion targets in each hiring and buyer acquisition; and observe each inner KPIs and exterior marketplace efficiency.

Inside of every dashboard, consumers can discover the information units with no need to jot down code.

“They may be able to engage with microdata, in reality drill down and have a look at a specific marketplace or a mortgage product,” Oliven mentioned all through an indication of HMDAVision, which prices $4,000 yearly and permits customers to have a look at particular geographic markets. “It really works at an excessively granular degree. And you are able to pack numerous knowledge into one interface.”

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