Enterprise Decision Management - a Weblog

October Rules Fest 2009

-- Posted by Carole-Ann

My abstract has been accepted at October Rules Fest!  I will be presenting as well as my fellow Chief Architect Carlos Serrano Morales.

I will be talking about the feedback loop and business performance monitoring.  Carlos will be focusing on the popular subject of Cloud Computing.

As a reminder, the show is in Dallas the last week of October 2009.

If you have not yet registered for the event, feel free to do so on their website at http://www.octoberrulesfest.org/

There is also a LinkedIn event you can sign up for and let everyone know you will be there: http://events.linkedin.com/October-Rules-Fest/pub/79911

Business Rules or Spaghetti?

-- Posted by Carole-Ann

In the early days, we use to think about Business Rules as a great way to extract logic from the code.  The vision of several nested if-then-else statements evoked the type of spaghetti code we all wanted to get away from, and we did.

Now that Business Rules Management Systems (BRMS) have made it to the typical application blueprint, the fear and pain of maintaining spaghetti code is well behind us...  But should it?

Don't take me wrong, I would never even dream of saying "let's go back to those days".  I have a passion for Decisioning Technologies and really appreciate the benefit it brings to the table.

But what if we created a new type of problem?  Now that complex, really complex business rules can be created with ease, is it possible that we are toying with new limits?

I have seen some very large systems with tens of thousands of business rules.  Granted you don't have to worry about the inter-dependencies.  But you still have to figure out what rule you need to update, what context it refers to.  With tens or hundreds of rules, not a problem.  With thousands it become more challenging.  If you have even more business rules, it may become a hard problem.

A customer I worked with a little while ago showed me how they navigated a world-wide repository of business rules.  I was amazed by the time they spent clicking around to find where some piece of logic were located (country- or region-level for example), and make sure that they applied the right rating table for the right population of end customers.  Navigating, selecting, browsing, validating, updating...  What could have been a simple update, in the end, relied on many error-prone user-maintained naming conventions and a lot of time wasted navigating what could have resembled Business Rules Spaghetti!  No blame on the customer, they did what they were supposed to but the nature of business rules, regardless of the technology you use, opens the door for those issues.

If you allow me analogy here, it is like your file system.  It is not bad at all (I don't know how we could do without one actually) but when you manage a 500Mb or 1Tb disk with tens of thousands of files, you are bound to click around to find the picture you archived a while ago.  This is why Google desktop and other search techniques are so useful.

Back to the Business Rules world, this is what happens with maturity.  You end up with large volumes and eventually complex dependencies that may be contextual (when editing rules related to product ABC you want to pick one of the Pricing tables for Product ABC, other pricing tables are irrelevant).

We have a formidable opportunity now with new approaches and technologies to better handle content.  Instead of thinking "the old storage way" about structuring a rules repository, why not adapt like Google, and think in terms of tags, dynamic structures, dynamic context and dynamic filtering.  This is elegant and flexible.

I am impressed by the potential of such technologies applied to BRMS.  The customer I talked about is able to boost the productivity of the business analyst or business users in charge of the maintenance with very little changes to their rules.  Actually only the structure of the repository and a few data providers changed.  Dynamic filtering and linking turn an old Rules Maintenance Application with growing pains into a slick and empowering tool.

Live from InterAct - preshow tutorials

-- Posted by Carole-Ann

We flew into NY on Monday.  After what seemed a long day of internal meetings and presentation rehearsals, we started the show in the afternoon with our tutorial.  I was part of the "Operationalizing Analytics" track.

Scott Horwitz talked about the how Insurance companies can benefit from Business Rules, Decision Simulation, Predictive Analytics and Decision Optimization.  If you have been reading this blog, these should not be new concepts to say the least.  It was good though to engage the crowd on their current practices.

I was responsible for the Decision Simulator part and demo.  It was refreshing to see heads nodding when I talked about existing customers' experiences.

Horia finally showed a demo on Decision Optimization.  Customers had lots of questions on regulatory compliance.  I anticipate that we will get more and more compliance questions over time, especially as the Obama Administration defines new rules for the Insurance business.

Before the Welcome reception, managment briefed the whole staff about the name change.  We are now FICO, rather than Fair Isaac.  The official marketing count of attendees for the show is over 500.  Not so bad given the economy.

Now, let's get ready for tomorrow's big day.  I have 2 presentations.  I must say that I am pretty excited about my NFL presentation.  A French woman discussing football in New York.  It has to be a first!  If you happen to be in town, don't miss it.

Now introducing Decision Simulation

-- Posted by Carole-Ann

Et voila!

We are now delivering Decision Simulation to the BRMS world.  What an exciting day!

Let me give you some insight as to what that means in reality.  Up to now, the industry has been focusing on what we call "validation" capabilities.  Validation is about running your business rules against test cases, sometimes historical data, and assess how it compares to expected values.  You end up with a listing of pass versus fail transactions.  Typically you just care about the discrepancies (what failed).

Decision Simulation is a key component of the Decision Improvement loop I always talk about because it offers a real alternative to Business Users.  Why do they need an alternative?  Because validation tells them IF the new business rules (I often call it a strategy) are what you expected them to be, it does not tell you HOW they will perform, in business terms of course.

In the world we live in now, we cannot afford to make sub-standard decisions out there.  If you fail to price new applicants properly, you will lose business.  If you grant too much credit to risky applicants, they will not be able to repay and you will lose money.  If you process fraudulent claims, you will lose money. If you lose money, you may not be able to stay in business.  We see examples every day that lead to bailout plans, mergers and acquisitions, or worse.

Being able to assess the value of your decisions before they hit production is valuable.  It may be the most valuable thing to the business owner: boosting his confidence that he is making the right decision.  How do you define right versus wrong?  It is really up to you: it could be measured in terms of revenue, profitability, risk, etc.  With a good set of Key Performance Indicators (KPIs), business users can chart the business impact of their strategy changes.  It assumes of course that your recent historical data is a good enough predictor of what is yet to come.

The tool that we are releasing now provides the kind of insight to the business users that Fair Isaac has provided to its leading customers, mostly in Account Management via TRIAD or our custom Strategy Science engagements that leverage Decision Optimizer.  Decades of expertise embodied into a set of out-of-the-box reports.  It is really exciting to finally make it available to all of our customers!

If you are an existing Blaze Advisor customer, I will be glad to host you on our Introductory webinar tomorrow (Wed 12/17 noon EST / 9pm PST).  If you are not, we will have a session in January that does not assume knowledge of our leading BRMS.

Will Data Drive Decision Improvement?

-- Posted by Carole-Ann

In the past few weeks I have been briefing our internal teams, external customers and industry analysts on our Decision Improvement capabilities.  One of the topics that was the most foreign to the BRMS addicts was Data Management, although it is one critical piece of Decision Improvement.

Let me set the stage here.  Decision Management covers obviously Decision Automation, with a particular emphasis on Business Rules, Predictive Analytics and Transactional Optimization.  The idea is to combine a set of decisioning technologies to make decisions in your Production systems.  Decision Improvement is the discipline of analyzing those decisions that are made day in and day out, and explore if and how those decisions could become more profitable, efficient, safe, etc.

Very soon you will hear a lot more along those lines with Decision Simulation capabilities that will complement other techniques such as Decision Modeling and Decision Optimization that have been applied very successfully in Financial Services (sub-prime crisis notwithstanding).

Although we have been worshiping Data in our predictive analytics or decision optimization activities, those were taboo most of the time in the BRMS world.  Why is that you may ask?  Very simply because Business Rules technologies have been extremely careful to integrate with data.  Data always belonged to the application.  Having proprietary data models or data storage was bad.  We all focused on making it easy to get access to database records, XML documents, Java objects, .NET assemblies, COBOL copybooks, etc.  Since we do not own the representation, it would be counter-intuitive to own the storage, wouldn't it?

Well things are changing now with the need in the industry to improve (objectively) those decision services.  With data, a brand new world of opportunities opens up.  With potential, comes new architectural challenges of course.

When you simulate a decision service, the PKIs that you drive from each run are only as good as the data that you use.  This refers to the general Garbage In / Garbage Out principle.  While business users become more savvy in those kinds of techniques and technologies, I anticipate that data warehousing technologies will find increased steam.  Although this is not at all new, actually pretty classic, I expect the Decision Management ecosystems to include more often than not datamart technology.

This goes beyond the traditional database component in the traditional software architecture as the historical data will need to be collected religiously, scrubbed and eventually massaged for future usage in the Decision Simulation applications.  This will stress more of the ETL capabilities, and to some extend continuous intelligence or real-time OLAP may become a medium for filtering out relevant data to be collected -- this is something I may discuss at greater length in another post.  Data preparation is a discipline that we do not often find in BRMS projects today.  The art of slicing and dicing data will allow to better target various segmented customer populations, but also empower the business users in the sense that they may potentially get greater coverage with less data via sampling and weighting.

Historical Data is king of course, either proprietary or pooled.  That being said, you can benefit from Decision Simulation even if you do not have physical data.  If you know enough about your business and the expected customer data distribution, you can fabricate data and make it available for simulation.  This allows simulation capabilities to be deployed on day 1, and then enhanced by historical data as it becomes available.

Not started yet?

If you are not yet thinking about Decision Improvement, but you have already started deploying Decision Automation projects, I highly recommend that you start thinking about data collection.  Science or Art, it takes practice to identify the appropriate data elements, calculations and decisioning artifacts that will be useful in the future.  So get started!

More food for thought...

Offline Decision Improvement is only half of the story.  Financial institutions have used Champion / Challenger strategies in Production for years.  The data we apply strategies to in that case is the real-time Production data, not previously processed Production data aka historical data.

If you are not familiar with Champion / Challenger methodology, here is a simple definition: the idea is to route some percentage of the transactions to the Challenger and the rest to the Champion, in a statistically relevant manner.  That allows to try out a new Challenger strategy without shifting the entire portfolio in the traditional big bang approach and therefore reducing risk.  Portfolio performance can be charted and analyzed to decide which strategy performs better according to the business objectives.

An attempt at demystifying CEP, BPM and BRMS

-- Posted by Carole-Ann

The more I read on Complex Event processing (CEP), the more I believe that people are confused or people are trying to confuse end users.  It reminds me of the Business Process Management (BPM) / Business Rules Management Systems (BRMS) market a few years ago: BPM vendors said that the rules could be modeled in the process flow and BRMS vendors said that processes could be implemented as ruleflows...  It took a few years to realize that each technology had a sweet spot and a real purpose.  They were complementary.

Now looking at the CEP Blog from Tim Bass, comments posted here (look at the comments) and there on the blogosphere, it is obvious that the role of CEP is unclear.  I am not disputing the value of the technology but merely begging the industry to keep things simple and straight-forward.

I will provide a simplistic prospective here.  You may argue that it is too simplistic but the more we discuss it, the stronger I feel about it.

Simple CEP / BPM / BRMS model

In our BPM / BRMS world, we came to the conclusion that we needed two types of technology: BRMS tools are used to make business decisions that are owned by the business users, BPM tools are used to carry out a process, executing on the decisions made by the BRMS tool.  Can you make a decision as part of a flow?  Yes.  Is it good practice to maintain them there?  No.  Can you automate a flow in a rules service?  Yes.  Is it good practice to do so?  No.  I assume we are all in agreement so far.

When CEP comes into the picture, we feel compelled to question this model.  Is CEP the right technology for processes?  Is it the right technology for decisions?  Some go as far as questioning whether CEP should replace Business Intelligence (BI) and/or Business Activity Monitoring (BAM).

At that point in time, being a product manager by trade, I get back to the problem definition.  what are we trying to accomplish?  Complex Event Processing...  This is all about processing events.  When is it valuable?  When you receive a flurry of events that cannot be handled efficiently using other traditional methods.  This is actually what happens most of the time in the real world: lots of things happen all the time.  Having a module that processes these events real-time would have tremendous value.  It would help dictate what kind of processes need to be executed and what types of decisions need to be made. 

Do we have to worry about an event overload during the execution of a process?  Typically no.  A single "document" is being treated by the process.  It may access more data when needed but it would not typically get flooded by other external events.  Do we have to worry about an event overload during the execution of a decision step (business rules)? Typically no.  Business rules apply to a set of business objects.  Additional data may be accessed as needed of course.  I qualified my answers with "typically" because there may be times when many events could happens and influence the processing of a flow or a decision.  Would all those "exceptional paths" belong to the process or business rules.  If limited they may but if we are talking about tons of events we may have to deal with, it is more likely we would want to use a module for processing those events, correlating and filtering them.  Isn't that the forte of CEP?

The CEP / BPM / BRMS world seems fairly simple after all:

• CEP module receives or intercepts a flurry of events and processes them with the objective of figuring out what those events are relevant for; it triggers the appropriate business processes or decision services
• BPM module receives the request for a given process to be applied to a higher level entity (an application, a document...); it automates the steps defined in the business process
• BRMS module is invoked with a given context to apply business rules; it makes a business decision 

Carlos Serrano-Morales wrote a great post on that subject.

Compared to the Human Body

My background is in life sciences, a source of inspiration.  Please indulge me here while I digress in a biological comparison.

I picture CEP as being the sensors.  The skin for example receives tons of inputs (events) on temperature, moisture level, etc.  It is not responsible for making a business decision although it happens that it makes "some level" of decision.  Typically raised hair and goosebumps may result from the sensors detecting cold weather.

BPM would be the nerves carrying the information to the brain and executing on its orders.

As you probably guessed, BRMS would be represented here by the brain, capable of making a higher level decision based on the contextual information correlated by the CEP module (it is cold) but also based on business strategies (use a blanket at night or turn up the heater if that's not enough; get a sweater during the day). 

Assuming that we decide here to use a blanket, the BPM system will be responsible for carrying out this order, get the complete system to get up, walk to the linen closet and grab the most appropriate blanket.

CEP may intervene any time to provide input that may alter the process or the decision making.  If the skin feels cold *and* the eye sees that an ice cube was dropped on the skin, the information would be provided again using the appropriate process / decision service.

I want to emphasize that, although CEP was making some level of decision, it is not built or informed to make the business decision.  There is a clear separation of role.

What makes this so complicated?

I think we are all guilty within the industry.  We are used to use our hammer on any kind of nail or screw in order to feel as ubiquitous as possible.  We hate to see technology used for a specific problem, by fear that it loses appeal.  I actually think that success comes from the acknowledgment that a tool has a purpose, and learning how to use it appropriately.  If we were still trying to convince the world that BRMS is a credible alternative to BPM (and vice versa), we may still be involved in half baked projects (product management recommended book: Angel Customers and Demon Customers).  We would not have been able to grow into a recognized component of the agile architecture.  CEP needs to follow this lead.

I am afraid that we are also getting confused by our own algorithms.  Some Business Rules Engines (BRE) are toying with the usage of Rete to CEP problems.  This should be irrelevant to the role of CEP.  If in the end we use Rete, Parallel Rete or any other algorithm to implement CEP, it should not matter to the role of CEP in the first place.  We must admit that our own Charles Forgy has presented his findings at the latest October Rules Fest. The intention was not to create confusion at the usage level - mea culpa if we did.  We believe that it would be a different Decision Automation module, part of Decision Management of course but not necessarily part of BRMS.

Complication comes from other sources as well.  Because CEP deals with events in time, we sometimes associate it with Business Intelligence (BI), thinking that because it can process events real-time, it should be able to process time-aware query (how many A events happened after a B event).  When combining both aspects (real-time and BI), you could build a Business Activity Monitoring (BAM) system but this does not mean that CEP is BAM either...

Well, as passionate as everyone is on that subject, I am expecting a few heated comments here...  This is healthy as it will help the whole industry as well as the end users to come to a conclusion on what CEP is and what it is good for.  Go ahead!

The evolution of BRMS (part 2)

-- Posted by Carole-Ann

Thank you for attending the Evolution of BRMS session at Business Rules Forum.  It was great meeting some of you there in person.

For those of you that could not make it, I wanted to give you the gist of what I presented.  A previous presentation covered the evolution of the business rules technology focusing first on the drivers that forced the market to shift its focus from Business Rules Engines (BRE) to Business Rules Management Systems (BRMS).  In this second presentation, I explore the evolution that is taking place as we speak, going from BRMS to Decision Management (DM). 

In a nutshell, the main ideas are summarized below. 

Increase Confidence in Strategy Performance

• Once business rules are verified and validated, they are typically promoted to Production at the right time -- How do you check today that those business rules will allow you to achieve your business goals?  How long does it take to realize whether or not the rate of automatic decisions is acceptable?  
• The next step in decision improvement is to better compare champion / challenger strategies -- How do you accurately predict the relative business value of each strategy?  How would external elements such as interest rate change or cost of resources influence the ability to repay or likelihood to accept an offer?
• The last step (in this scenario; another methodology is to start actually here) would be to generate an optimized strategy out of this decision model and historical data -- How does your current strategy map compared to an optimal assignment?  Can you infer an optimal strategy that can be applied consistently to your incoming transactions?

Address more Sophisticated Decisions

• Business Rules come typically from experts, regulations and/or legacy code -- Are they as precise / efficient as those of your competitors?  Would statistics on your historical data help you better identify the good versus bad risk applicants?  What if you could predict which customers are likely to accept which offers?  How competitive would you be if you could accurately price each transaction according to your estimated related expenses?
• Some decisions may appear sub-optimal and could be improved -- Do you offer your customers the best possible deal given your product constraints and your business objectives?  How efficient is your usage of resources given your delivery schedules?

Connect Decisions

• Decisions made in silos may lead to contradictions, overlaps, inefficiencies -- Do you proactively market to customers that have a history of Fraud or Delinquency?  How valuable are the customers you try to retain?

The slide deck is available from the Business Rules Forum website if you are an attendee.  Our marketing guys will also post it on our community site for your convenience.

Business Rules Forum

-- Posted by Carole-Ann

 

After Dallas, travel brought me to Florida where I attended Business Rules Forum.

On Tuesday, John Rymer invited me to sit in a vendor panel (the only woman).  We discussed topics such as market consolidation and evolution towards Decision Management.  As you would expect all the vendors were unanimous that they would still be in business despite the Platform play of the IBM, Oracle etc. ;-)

I was not surprised to see that BRMS vendors are trying to confuse the audience regarding Decision Management.  As an early pioneer, I am of course a great proponent of Decision Management.  I contributed to shape its vision.  Therefore it is sometimes frustrating to hear people say it is the same as BRMS.  I love BRMS too but I see a clear distinction between the two: one is a superset of the other.  BRMS focuses on business rules, in other words: "how do we empower business users?".  Decision Management looks at the bigger picture in terms of including a larger set of technologies to solve more than business rules problems: "how do we predict the ability to repay?  how do we optimize resource allocation?"  Decision Management takes a serious look at how we improve decision too: it's about providing tools and services for business users to assess how profitably new strategies will perform in various economic conditions.  This goes well beyond business rules validation as provided by the BRMS today.

Frustration can turn in great satisfaction.  Although vendors faked they did not get it (or maybe they really did not), some bloggers did not get it either, I was extremely pleased to see that the audience was getting it.  I heard several people talk about "automating and improving decisions".  They are (getting) ready for this new discipline.  I definitely perceived from the side discussions I had after the panel and my talk that enterprises are now ready to investigate or embrace Decision Management.  I did not get that feeling in the previous years so I am sensing some market maturity there.

The panel touched also on Standards.  I was probably not popular stating that we are not ready for standards.  Not that they are unimportant of course, they can definitely change the adoption of technology.  But I still feel like we are at the stage where vendors want to define standards for the sake of having standards.  I have not seen any real end-user contribute to OMG or W3C on that subject.  I do not expect them to determine what the standard should be (duh!) but I expect them to dictate what is important to focus on.  Is it all about being able to swap one engine versus another, like a rule language extension of JSR94?  Or is it about swapping BRMS and therefore focusing on HOW the rules are represented (templates, metaphors, etc.) and lifecycle management processes?  Or was JSR94 the only thing end customers really cared about?  I am pretty sure JSR94 is not the solution of course.  But I think we will run into a wall if we try to define a standard for the wrong thing.  Not knowing the objective I could define more than one perfectly engineered wrong design.  After all, this is the core reason we have product managers in the software industry: to link the solution to the root business problem.  If we miss the business problem, the solution will likely miss the point too.  Vendors tend to disagree.  Fine.  The illusion that BRMS can be swapped with no effort is pure marketing today.  What is being discussed in terms of Standard will not allow to make it real though.  No offense to the vendors involved, it is all about business.  With pragmatic people like Changhai being involved in OMG PRR effort, I feel that we have a chance to get real results *if* we focus on what the end-users really need.  This is an open call to real end-users with real business problems to speak up.

On Wednesday morning, I presented my perspective on the market evolution to Decision Management.  This was the part 2 of the pre-show webinar I blogged there.

The talk was much better attended than most of the sessions I went to.  If you were in the audience, thank you for coming.  My objective was to educate the crowd on Decision Automation technologies such as Predictive Analytics and Optimization as well as Decision Improvement concepts.  It feels like it was the right approach as the BRF attendees are not yet fluent with those concepts.  I'll provide more details on the talk in another blog entry.

One of the highlights of the show was our Customer Dinner.  We had a private reception at the Fulton's crab house.  Great food.  I also got the opportunity to spend one on one time with a few customers that I had not met before.

Overall, the show was a good Business Rules Practitioner Reunion as always but it was a disappointment to see it had not grown much.  It is understandable that the attendance is down with the crisis but it is unfortunate that quite a few sessions had to be canceled.

October Rules Fest

-- Posted by Carole-Ann

The very first occurrence of October Rules Fest happened in Dallas a couple of weeks ago. The objective was to get all kinds of business rules techies in one room and cover all kinds of topics from rule algorithm details and innovation to enterprise deployment considerations to decision management.  James Owen and team assembled a fantastic panel of presenters if I may say so myself.

Despite the slowdown in the economy the attendance was pretty good -- around a 100 or so senior architects and CIOs from large enterprises from all around the world.  Given that they did not do any marketing, this illustrates the power of blogs!

Everyone was very engaged in the sessions.  Lots of great conversations during and after the sessions.  It was friendly, competition was respectful and most of us stayed at the technical level (no sales pitch).

Being one of the early Decision Management pioneers, I decided to provide education on Predictive Analytics.  I changed the title to "Demystifying Predictive Analytics" by the way.  From the feedback I received it seems that it stroke a cord with the audience.  Too often, modelers and IT do not talk (that is if they know each other at all!) and do not value each other's contribution.  My talk intended to provide enough background on what models are, how they are being constructed and what they can be used for.  It took us years at Fair Isaac to get mutual respects.  Sharing our scars will help the industry at large "grow up" faster.

Carlos Serrano-Morales and myself had the opportunity to present again on Thursday afternoon.  We focused this time on Enterprise Deployment.  We admit this is boring stuff to some extent but this is also what business rules evangelists need to understand to really exploit the whole value of business rules, and avoid architecture pitfalls.

Charles Forgy presented also the latest and greatest innovation on parallel Rete.  I can tell that all the vendors were taking notes!  Aren't we lucky to have him working for us?  Priceless.

Again, based on James Owen blog, it seems those three sessions were quite well appreciated by the audience.  I encourage you to read his blog report on the sessions.  The slide decks will be available soon I believe.  They also taped the talks.  I am waiting for the videos any day now.

I loved the show.  I hope that James and Rolando will do it again next year.  It was a great place to discuss the "technical" stuff without the marketing.  It felt like a high school reunion, just missing a couple of the "usual suspects" (Paul Haley and Ernest Friedman-Hill).

Feedback from our customers was also very positive.  So this is not just my opinion...

I also want to thank Andreas for the picture of me presenting.  If you are interested in what I am showing on the screen, it is a pretty cool data discovery report from Model Builder.  I am explaining the weight of evidence sparklines.

The Role of Predictive Analytics in the Sub-Prime Crisis

-- Posted by Carole-Ann

Being part of Fair Isaac, I have never really doubted the critical role predictive analytics could play in business.  I see real-life examples day in and day out but when I read the New-York Times article http://www.nytimes.com/2008/10/05/business/05fannie.html?partner=permalink&exprod=permalink, I found one that was painfully telling…

Let me point your attention to a few points that CHARLES DUHIGG makes in this investigation.  I will not comment though on the politics involved.

Fannie Mae has been playing a crucial role for the lending industry as we all know.  Their early success relied on their ability to predict which borrowers would be able to repay, assessing the premium required to compensate for the risk they took.  With an effective model, you can pinpoint good risk versus bad risk and therefore make safe decisions that ensure the business will prosper.  This is pretty much the essence of predictive analytics: once you know the probability to repay for people with a given set of characteristics, you can extrapolate and estimate how much reserves you need to build in order to beat the odds that you will not get you money back for each population segment.  This is how premium are calculated.

Unfortunately with new types of mortgage product and the lack of associated data, Fannie has not been able to produce a robust predictive model.  Not being able to tell how borrowers would behave in the long run, there was no way to estimate how much risk they were exposing themselves to.  When you combine that with the absence of a CRO (Chief Risk Officer), which is like driving with your eyes closed, no wonder we got where we are.

This is fairly atypical black and white example but it drives the point: with a robust model, you thrive / without a model, you’ll hit a wall… eventually.  I am not saying that predictive models are the only way to make good decisions but they definitely help manage the uncertainty.

One might wonder how they could have built a robust model in absence of data.  This is a fair question.  Well, how about better integrating a feedback loop into the system to detect the early signs of the meltdown?  This is what we call Decision Improvement.  Another potentially complementary approach might have been to take a less aggressive stand: knowing that we don’t know for sure, premiums could have been calculated with more room for caution.  This is where business rules and predictive models work hand in hand.

Again, this is not taking into consideration other facts that influenced the situation such as the mandates from Capitol Hill or the laxity of credit agents.