My Check Fraud Detection Model Reduces Fraud by 60%

A project manager from a bank just told me that the model developed by me has resulted in 60% reduction in fraud loss. He said "everyone was surprised at how effective it was." It was a model that I developed two years ago for a top 15 bank.(Of course, I was not surprised at all since the model was tested on holdout data sets and showed similar performance).

The model was built and deployed on Oracle databases. The main reason for the success of the model was that I spent huge amount of effort building model variables that captures the fraud patterns. Luckily, I used Oracle analytic functions to build those variables easily. (Please see my posts "How to build predictive models that win competitions" and "Recency, Frequency, Monetary (RFM) Analysis: Part 1"

Another important advantage of using an uniform platform, i.e., Oracle databases, is that the deployment is easy. I simply deployed the model as a set of SQL query. See my posts "Build Predictive Models Using PL/SQL" and "Logistic Regression Model Implemented in SQL"

From Oracle SQL Developer to Data Miner

As mentioned in an earlier post How easy is it for a SQL developer/analyst to become a data miner?, if we consider data mining as just more sophisticated SQL queries, data mining is simply a natural extension of SQL programmer/analyst's daily job, i.e., querying the database. For example, a SQL programmer can write a query to answer a business question: finding people living in Boston, MA with annual income at least $50K and credit score 750 or higher. One simply puts the three conditions in the "where clause" as the following:

select person_id, person_first_name, person_last_name
from tbl_data_about_people
where
home_city='Boston' and home_state='MA' and
annual_income>50000 and
credit_score >=750;

Similarly, we can put a predictive function in the "where clause" to answer a more useful question: finding people living in Boston, MA who are 25% more likely to purchase a new car with 2 months as the following:
select person_id, person_first_name, person_last_name
from tbl_data_about_people
where
home_city='Boston' and home_state='MA' and
prediction_probability(model_likely_to_buy, 1 using *)>=0.25;

We can see how easy and powerful to use predictive models in SQL. A traditional Oracle SQL developer can greatly enhance his/her value by picking up those data mining functions. There are a number of good documents and sample codes available at Oracle's site, e.g,
The Data Mining Sample Programs
Oracle® Data Mining Concepts