By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data-driven white label SEO
    Does Data Mining Really Help with White Label SEO?
    7 Min Read
    marketing analytics for hardware vendors
    IT Hardware Startups Turn to Data Analytics for Market Research
    9 Min Read
    big data and digital signage
    The Power of Big Data and Analytics in Digital Signage
    5 Min Read
    data analytics investing
    Data Analytics Boosts ROI of Investment Trusts
    9 Min Read
    football data collection and analytics
    Unleashing Victory: How Data Collection Is Revolutionizing Football Performance Analysis!
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: First Look: FICO Decision Optimizer
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > First Look: FICO Decision Optimizer
AnalyticsBest PracticesBusiness IntelligenceCRMData ManagementDecision ManagementInside CompaniesMarket ResearchMarketingPredictive AnalyticsSoftware

First Look: FICO Decision Optimizer

JamesTaylor
Last updated: 2013/05/22 at 8:06 AM
JamesTaylor
6 Min Read
decision management tool
SHARE

decision management toolDecision Optimizer is one of FICO’s Decision Management Tools and is designed to address some specific challenges in customer decisioning, particularly that there are often competing objectives and very large numbers of customers (and thus customer decisions) involved.

decision management toolDecision Optimizer is one of FICO’s Decision Management Tools and is designed to address some specific challenges in customer decisioning, particularly that there are often competing objectives and very large numbers of customers (and thus customer decisions) involved. Combine this with the many possible action combinations, uncertainty about what customers might do, as well as uncertainty about the actual business impact of each decision and coming up with the best approach is complex. Once you have an approach or strategy to address these issues it must still be implemented to be useful and that means handling deployment as well as convincing business users of the value of the approach.

FICO Decision Optimizer uses decision models to encapsulate the business impact of customer decisions. These models incorporate KPIs, business constraints and goals. They map possible actions to risks and opportunities and manage all the links between these elements. Once you have a model developed, Decision Optimizer runs data, all your customer records or a subset, through the model to determine the optimal actions to these customers – optimizing to maximize or minimize the targets you identified while meeting your constraints. Uses include champion/challenger comparison, what-if analysis, stress testing, exploring the efficient frontier and tuning already deployed rules for customer treatment. Decision Optimizer can be used in Basel Stress testing, early stage collections, credit line management, origination and more.

The process for Decision Optimizer involves going from data to developing a model, optimizing the model to drive scenario selection and then generating a decision strategy. Predictive analytics from FICO Model Builder or from SAS/SPSS/R etc can be fed into the models. Results can be as a set of actions or as a decision tree. Decision tree results can be driven out to set of business rules in FICO Blaze Advisor or exported using the well defined PMML model for Decision Trees. This allows the output to be integrated to various FICO solutions like FICO Origination Manager or FICO TRIAD Customer Manager as well as with the rest of the Decision Management Platform products like FICO Blaze Advisor.

More Read

benefits of ai in customer service

Problems Solved with AI And Machine Learning in Customer Service

The Growing Importance Of Data Collection For Customer Service
Big Data Leads To An Impressive Array of Chatbots In Customer Service
Predictive Analytics Reveals Secrets To Boosting Customer Loyalty
Is Big Data Important In Your Social Media Customer Service Strategy?

Decision Optimizer is a web-launched client talking to a remote server for the compute power that supports multiple users on the same model. The initial interface includes a number of key elements. For scenario design you can manage:

  • Data items including input data items, some of which are also potential decision keys, output metrics and reporting metrics
  • The treatments or available actions to be selected from
  • Facts true across all customers
  • Constraints on the metrics that must or should be met
  • Calculations of various types that convert defined input into outputs:
    • Lookup tables/charts (values mapped to probabilities)
    • Equations
    • PMML models
    • SAS regression models
    • Java code

Many scenarios can be defined using these elements and these scenarios can be grouped. The core of a scenario is a model of the components and how they interact. This connects the calculations, input data, metrics and treatments/actions. Each calculation has inputs and outputs that are connected by the equation or look up table. At one end of the model are the fixed facts and the account inputs and at the other are the metrics you want to optimize for and the constraints that must be met. One or more layers of calculations link these and the available treatments/actions into a network model: What you know, what you can do and what you care about.

Once scenarios have been executed and the results gather the overall results for different scenarios can be viewed in a grid for the scenarios in the group. All the various output metrics are shown so they can e compared.

For each scenario you can specify that the results must be created as a decision tree (that can be deployed) or as a set of optimal actions for each customer (for a batch process like a mailing campaign). Decision Optimizer can automatically simplify the generated decision trees to make them easy to read and deploy. One particularly nice feature allows the specification of business palatability constraints to make sure the tree will be acceptable e.g. specifying that, all other things being equal, higher credit scores should be more likely to be accepted than not, no matter what seems “optimal.” In addition tree templates can be defined that limit the attributes and bins that can be used also easing deployment and business believability.

Decision Optimizer allows portfolio level optimization of individual customer decisions and allows the results of this optimization to be deployed into a Decision Management System by generating a deployable decision tree that makes near-optimal assignments. This means that individual customer decisions can then be made that are very close to the optimal without the need to do optimization at run time.

Copyright © 2013 http://jtonedm.com James Taylor

(image: decision management tool / shutterstock)

TAGGED: customer service
JamesTaylor May 22, 2013 May 22, 2013
Share This Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

big data and IP laws
Big Data & AI In Collision Course With IP Laws – A Complete Guide
Big Data
ai in marketing
4 Ways AI Can Enhance Your Marketing Strategies
Marketing
sobm for ai-driven cybersecurity
Software Bill of Materials is Crucial for AI-Driven Cybersecurity
Security
IT budgeting for data-driven companies
IT Budgeting Practices for Data-Driven Companies
IT

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

benefits of ai in customer service
Machine Learning

Problems Solved with AI And Machine Learning in Customer Service

11 Min Read
data collection for customer experience
Big DataData CollectionExclusive

The Growing Importance Of Data Collection For Customer Service

5 Min Read
chatbots in customer service
Artificial IntelligenceExclusive

Big Data Leads To An Impressive Array of Chatbots In Customer Service

7 Min Read
secrets to boosting customer loyalty
AnalyticsExclusivePredictive Analytics

Predictive Analytics Reveals Secrets To Boosting Customer Loyalty

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?