During a panel at Fair Isaac’s Interact conference last week, a banker from Abbey National in the UK suggested that part of the credit crunch was due to the use of the FICO score. Unlike other panelists, who were former Fair Isaac employees, this gentleman was formerly of Experian! So there was perhaps some friendly rivalry, but his point was a good one. He cited an earlier presentation by the founder of Strategic Analytics that touched on the divergence between FICO scores and the probability of default. The panelist’s key point was that some part of the mortgage crisis could be blamed on credit scores, a point that was first raised in the media last fall.
The FICO score is not a probability.
Fair Isaac people describe the FICO score as a ranking of creditworthiness. And banks rely on the FICO score for pricing and qualification for mortgages. The ratio of the loan to value is also critical, but for any two applicants seeking a loan with the same LTV, the one with the better FICO score is more likely to qualify and receive the better price.
Ideally, a bank’s pricing and qualification criteria would accurately reflect the likelihood of default. The mortgage crisis demonstrates that their assessment, expressed with the FICO score, was wrong. Their probabilities were off. (more…)
Externalizing enterprise decision management using service-oriented architecture orchestrated by business process management makes increases agility and allows continuous performance improvement, but…
How do you implement the rules of EDM in an SOA decision service? (more…)
I was prompted to post this by request from Mark Proctor and Peter Lin and in response to recent comments on CEP and backward chaining on Paul Vincent’s blog (with an interesting perspective here).
I hope those interested in artificial intelligence enjoy the following paper . I wrote it while Chief Scientist of Inference Corporation. It was published in the International Joint Conference on Artificial Intelligence over twenty years ago.
The bottom line remains:
- intelligence requires logical inference and, more specifically, deduction
- deduction is not practical without a means of subgoaling and backward chaining
- subgoaling using additional rules to assert goals or other explicit approaches is impractical
- backward chaining using a data-driven rules engine requires automatic generation of declarative goals
We implemented this in Inference Corporation’s Automated Reasoning Tool (ART) in 1984. And we implemented it again at Haley a long time ago in a rules langauge we called “Eclipse” years before Java.
Regretably, to the best of my knowledge, ART is no longer available from Inference spin-off Brightware or its further spin-off, Mindbox. To the best of my knowledge, no other business rules engine or Rete Algorithm automatically subgoals, including CLIPS, JESS, TIBCO Business Events (see above), Fair Isaac’s Blaze Advisor, and Ilog Rules/JRules. After reading the paper, you may understand that the resulting lack of robust logical reasoning capabilities is one of the reasons that business rules has not matured to a robust knowledge management capability, as discussed elsewhere in this blog. (more…)
TIBCO is the CEP vendor most focused on the market for business rules, as reflected in Paul Vincent’s post here. Although I agree with Paul that rule vendors are not currently offering enough in terms of support for long-running processes, the conclusions that he draws in favor of considering a CEP alternative to a BRMS are not compelling yet.
Paul said that rules don’t address the following that are addressed by CEP:
- BAM (business activity monitoring) and the other BPM (business performance management)
- Complex-rule processing
- Customer-centric (portfolio-based) decisions / policies
I am sure Paul was just being flippant, but you may notice that there is a bit of a war going on between CEP, BPM and rules right now. (more…)
Don’t miss the great post about his and Ilog’s take on rule and decision management methodologies by James Taylor today (available here).
Here’s the bottom line:
- Focus on what the system does or decides.
- Focus on the actions taken during a business process and the decisions that govern them and the deductions that they rely on.
- In priority order, focus on actions, then decisions, then deductions.
- Don’t expect to automate every nuance of an evolving business process on day one – iterate.
- Iteratively elaborate and refine the conditions and exceptions under which
- actions show be taken,
- decisions are appropriate, and
- deductions hold true
Another way of summing this up is:
Try not to use the word “then” in your rules!
Do check out the Ilog methodology as well as the one I developed for Haley that is available here. The key thing (more…)
A manager of an enterprise architecture group recently asked me how to train business analysts to elicit or harvest rules effectively. We talked for a bit about the similarities in skills between rules and requirements and agreed that analysts will fail to understand rules as they fail to understand requirements.
For example, just substitute rules in the historical distribution of requirements failures:
- 34% Incorrect requirements
- 24% Inadequate requirements
- 22% Ambiguous requirements
- 9% Inconsistent requirements
- 4% Poor scoping of requirements
- 4% Transcription errors in requirements
- 3% New or changing requirements
A client recently asked me for guidance in establishing a center of excellence concerning business rules within their organization. Their objectives included:
- Accumulate requisite skills for productive success.
- Establish methodologies for productive, reliable and repeatable success.
- Accumulate and reuse content (e.g., definitions, requirements, regulations, and policies) across implementations, departments or divisions.
- Establish multiple tutorial and reusable reference implementations, including application development, tooling, and integration aspects.
- Establish centralized or transferable infrastructure, including architectural aspects, tools and repositories that reflect and support established methodologies, reusable content, and reference implementations.
- Establish criteria, best practices and rationale for various administrative matters, especially change management concerning the life cycles of content (e.g., regulations or policies) and applications (e.g., releases and patches).
I was quickly surprised to find myself struggling to write down recommendations for the skill set required to seed the core staff. My recommendations were less technical than the client may have expected. After further consideration, it became clear than any discrepancy in expectations arose from differences in our unvoiced strategic assumptions. Objectives, such as those listed above, are no substitute for a clearly articulated mission and strategy.