(Un)Calculated Risk | by Peter Orr of Intuitive Analytics

Refunding Adjusted Yield (RAY) Shines Light on Issuer Financing Cost

Posted by Peter Orr on Jan 23, 2015

It’s 2015. Watson vanquished humans in Jeopardy 4 years ago and is now rapidly moving towards replacing as many oncologists as possible. Google is just one company running driverless cars and trucks around everywhere. Facebook is trying to monetize every eye twitch you make looking at a web page. Let’s check in on innovation in public finance:

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Financial Software: Top 10 Reasons Why a Database Kicks a Spreadsheet’s Butt

Posted by Peter Orr on Jul 16, 2010

I’ve always believed there are actually three certainties in life (in contrast to the far less archetypal two): death, taxes, and finance people’ love of spreadsheets.  Spreadsheets are excellent for doing certain types of work given their flexibility. Though frankly, these “electronic chalkboards” as their inventors called them are simply not the right medium for others. For instance, heavy duty simulation based number crunching and optimization shouldn’t be done on a chalkboard, electronic or otherwise. The memory management and numerics simply aren’t suitably industrial strength for big jobs like that. As a data store the spreadsheet also has drawbacks.  Sure it’s flexible and easy to add new bits, but that same flexibility is a problem when it comes to compatibility and consistency, virtues in and of themselves.

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Financial Software: The answer to “Build or Buy?”

Posted by Peter Orr on Jun 07, 2010

"Programming today is a race between software engineers stirring to build bigger and better idiot-proof programs, and the universe trying to produce bigger and better idiots. So far, the universe is winning."            - Unknown

Many public finance businesses are grappling with the "build vs buy" question as it relates to their analytic tools.  I've commented here on the challenges of building good financial software and frankly, most firms that aren't specifically in software development are poorly equipped to do so.  And this is a tangentially related and important question.

Of course, build vs buy is not a new question generally but it may be new to some in financial services. The most succinct variant of the common wisdom on this is in this infoworld article . Here's the bottom line from the article:

"Decades of trial, error, and egghead analysis have yielded a consensus conclusion: Buy when you need to automate commodity business processes; build when you're dealing with the core processes that differentiate your company."

There's an interesting dynamic about the technology "backbone" behind a public finance business (providing accurate/current debt profiling, refund screens, historic prices and reset histories from EMMA, bond and option valuation functionality, etc).  Although these may be commodity business processes that every banking/advisory/investment firm must do in one form or another, that data backbone serves as the foundation for proprietary analytic tools and reports that can differentiate one from the rest. 

At IA, we do both automation and innovation so that the workflow public finance analytics need to support are fully addressed. This allows us to be far more efficient and effective in designing each.    

Other good "build vs buy" articles here:


MIT Free Software: Build or Buy Dilemma 

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Financial Software: The Good, the Bad, the Ineffective

Posted by Peter Orr on Dec 31, 2008

"The dividend of the computer revolution to us did not come in the flooding of self-perpetuating email messages and access to chat rooms; it was in the sudden availability of fast processors capable of generating a million sample paths per minute."

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