Finnovating!

“We’re really excited to have DeMyst Data demoing their innovative new solution at FinovateFall. We think the audience will find their new solution for helping lenders with segmentation and offer customization via alternative data sources very interesting.” ~Eric Mattson, CEO of Finovate

For those of you unfamiliar with Finovate, it is “the conference” for showcasing innovations in the fields of banking and financial technology. On stage, we’ll publicly launch the tool and demo some of our initial results with real client data.  Our focus will be on exposing lenders to the rich segmentation we are able to create with minimal customer inputs and illustrating how the outputs can be used to customize offers for thin file consumers.

We’ll be in NY (and traveling around the US) for a few weeks leading up to the conference and look forward to re-connecting with many of you and meeting others for the first time.   Drop us a note, we’d love to share some results and discuss how the product can help you grow!

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We can predict anything!

What?

We’re opening some private beta trials to the DeMyst API, a tool that leverages rich public data sources; think digital footprint, telecommunications usage, and much more, to predict risk or conversion when there is minimal consumer information available.  Initially targeted at lenders, a few client meetings quickly revealed that our tool had broad applications to anyone working with ‘thin file’ customers.  So, like any good group of bootstrapping engineers, we iterated a bit, and hence, the latest version of the DeMyst API, a tool capable of predicting anything, was born.

How does it work? 

The tool excels at predicting a ‘target’ with minimal inputs/identifiers. Of course, the more identifiers the better, but the reality is, there is a bunch of rich data out there in the public domain that with a bit of aggregation, some pretty geeky analytics, and kickass technology, allows us to produce either a standalone prediction or complementary attributes for your own scorecards.    The UX is painless; just upload a decent sized sample containing whatever identifiers are available (e.g. it even works with just email!), we’ll append nifty third party data, exert our ‘muscle’, and within minutes, produce an API with a custom prediction. Yes, minutes.

Sounds cool, prove it: 

From a proud founder’s perspective, we’ve been pretty blown away by how much lift is being created by the toolkit.   We can boast a  >90% hit rate and significant growth improvements.  To prove it, we’re offering a few private beta spots so you can test for yourself.

What’s the catch? 

There are two:

• You must be brutally honest and willing to provide us with feedback to help us refine the product.

• You must have a genuine interest in commercially using the product if you like it (at a preferred rate of course).

To show our appreciation, we promise to provide attentive support and assistance, some free consulting help, and a certain level of exclusivity as a lighthouse customer.  This of course all comes free with your early access to a slick new tool that could massively increase your distribution without impacting your current risk level.

Early Adopter?

To reserve your spot, click here .

Google What?

A few weeks ago, Google made its foray into financial services with Google Advisor.  The site, in essence a price comparison engine, bills itself as one-stop shop for financial services designed to help users easily find relevant products from multiple providers, compare them side by side, and apply online.  Available only in the US, Advisor allows users to create customized searches for products including mortgages, credit cards, CD’s, checking, and savings accounts.  The site then, typically within 2 seconds, produces a list of offers that match the user’s criteria along with lender contact info and rates.  Finally, Google is only paid when users contact lenders for mortgages.  In all other products, Google’s listings are sorted exclusively by APY.

This new domain, which within its first few weeks has solidified top placement in search and garnered 75k YouTube views of it’s “how too” video has left many people scratching their heads asking, “Why?”  A couple of thoughts on that:

1-     According to their blog, Google had already constructed and begun testing a mortgage comparison tool in 2009 and therefore, adding other financial offers to this product was relatively easy.

2-     5 days after the launch of Advisor, Google announced the acquisition of Sparkbuy, a consumer comparison site, and that Sparkbuy’s 3 person team was joining Google as employees working on the Advisor product, e.g. the perfect operating team.

But rather than ponder “why”, because frankly, I think the answer is, “because they can,” I found myself navigating the site trying to determine “who”, in today’s economy, finds a site like this useful?  Practically speaking, the only measure of creditworthiness on the site is self entered, the rates are variable and for comparison only, and the end result of your “customized search” is still an application away from an offer of credit.  So, for those of us with a 780 FICO score and the entire spectrum of credit products to choose from, I guess yes, Advisor could be considered a good source of information.  But what about for the other 80% of the US population?  Think for a second about an average US consumer who is searching for a loan.  Their intent is unambiguous- cash or access to credit as quickly as possible at the lowest available interest rate.  Through this lens, Advisor’s process of choose the loan that’s “right for you,” browse offers, contact the advertiser, apply, and then get accepted or rejected seems to me to miss the mark.

Now of course, a workflow that facilitates actual lending is much more complex than a comparison tool, which in fairness, Advisor only claims to be.  But if anyone, Google has the brand and resources to meet user objectives.  Surely, they know enough about each of us to head down the necessary path of individualized customized product offerings, yet, have chosen to shy away.  I’ll go out on a limb and predict that Advisor’s intent is not to send free, non-biased referrals to lenders forever, and that in all likelihood, what we are seeing today is only a first iteration.  Thoughts?