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Sell Once: POS and Modeling

According to Fair Issac:

The Hartford Insurance Group is gradually moving all of its decision logic onto Blaze Advisor, the world's leading business rules management solution.  Blaze Advisor enables The Hartford to combine its own predicitve models with rules and other dcisioning elements - all without programming - and rapidly deploy the automated decisioning processes to multple frontline interfaces, including third party agency management applications (with automatic transpormation from/to XML) and a cusotmer self-serve website.  Currently, new BRM-based processes are being used for real-time POS quotations and new business; soon they'll be extended to renewals as well.

Computer grids speed Predictive Modeling Results

Computer grids speed Predictive Modeling Results - Nationwide Insurance, with the assistance of 5-year old company, DataSynapse has developed a grid computing scheme to dramatically reduce time for problem solving.  A typical predictive modeling solution would take the Nationwide Actuarial department about 83 days to compute on one of its processors was now reduced to 81 minutes using a 50-computer grid.

"One source of competitive advantage is how well we analyze that data and what you can do with it.  We did expect it to succeed as well as it has.  It challenges your fundamental notions..."

Amica Mutual Develops Models for Marketing Dollars

Amica Mutual Develops Models for Marketing Dollars - After procuring senior management buy-in, Amica Mutual was able to develop an Inquiry Model that identified 12 predictive variables which were most likely to predict an inquiry into purchasing life insurance.  By segmetation and scoring, it was discovered that a vital few concepts exists in life insurance purchases.  Amica exceeded its inquiry goals by 110%, reduced marketing costs by 25% and increased revenues.

Data Mining Resources

Data mining resources can be found at Dorian Pyles website: Model & Mine.  Of particular interest is the breakdown of basics of mining and modeling. As discussed in his book, Business Modeling and Data Mining, Pyle explains just what models are and how they can be used to reveal hidden assumptions and needs, determine problems and discover data and costs.

Additionally, the site compiles a review of data mining and business modeling software such as Clementine, JMP, Brainmaker, @Risk, CrystalBall and many more.  It is a terrific thumbnail sketch of strengths of each program.

Be sure to Bookmark this page!

MAT: A new Tool for Life Insurance Underwriting

In this paper presented by BioSignia, Inc., a study is reported that demonstrates yielding a higher quality of preferred class risks when utilizing Internet-based marekting.

The evolution of the life insurance industry is requiring a robust risk assessment tool that not only could streamline the underwriting process and reduce the processing cost, but also improve the risk assessment quality. The Mortality Assessment Technology (MAT) introduced in this paper was developed for that purpose. MAT is based on multiple evidence-based disease prediction models and a conversion to predicated mortality ratio (PMR). By applying MAT into a national longitudinal cohort dataset, it was shown that MAT accurately predicted mortality and yielded better mortality risk discrimination power then the conventional method. More specifically, the preferred class defined by MAT had significantly lower mortality outcomes than the preferred class defined by conventionally used criteria. It is believed that MAT could play significant roles in the evolution of underwriting from a paper driven process into an automatic, computerized, intelligent decision process.

Need $550,000 ???

Put your mind to work and develop a new algorithm to help identify terrorist chat rooms.  RPI is looking for proposals to develop this technology as they believe as many other sources do, that the terrorists who planned September 11th used the basic email and chat rooms for their work.  In fact, this author heard of a Tampa librarian who, inadvertently believes she set up an email account for Atta.  Remember, public libraries continue to provide access to the internet for free.

Apparently, those who do plotting of any kind, and use the internet, deviate from customary practices by sending flurries of messages to only one person, for example.  It is through this type of "sorting" and mining that RPI hopes to identify these patterns and activities.  The US govt has for years relied on a 30 year old software called, Echelon to review massive amounts of phone data.

Maybe George Orwell's time is upon us!

Please, don't check my driving record!

What if liability premiums were based not on demographics and DMV records but on actual driving habits? That's the idea behind Norwich Union's newest business. In a pilot program launched last year, the British insurer began to track 5,000 customers by placing GPS receivers in the trunks of their cars. Data from the devices will be used to adjust drivers' premiums from month to month. "We calculate everything from speed and acceleration to whether they're braking too early or too late at intersections," says project manager Robert Ledger. So far Norwich Union has collected data on about 1 million journeys, and its statisticians are using the information to recalculate its insurance tables. Next year it will make the technology available to the rest of its 3.5 million auto customers, hoping that the feedback will lead to fewer accidents -- and thus higher profits. "Over time," Ledger says, "we think we can change people's behavior and make them safer drivers."

Or check out the actual features at Norwich Union:

Features of the Pay As You Drive’™ For Young Drivers product include:

• a tariff per mile, with the rate personalised to each customer and dependent on the time of day the car is driven
• the first 100 off peak miles each month are free
• young drivers could see a saving of up to 30% a year off the cost of their premiums
• premiums are billed monthly – premiums will vary monthly if customers vary their driving
• there is a one-off fee of £199 for the telematic device – this is expected to cost less than the savings to be made in premiums.
• the box has a built in car locator – enabling customers to have their car located if there’s been an accident, breakdown or if it has been stolen

Now, could this data collected be indicators of future success in say, bill payments, return-to-work predictors, or fradulent actions?

More Incoming Data Streams

More incoming data streams...this time from eylion.  It has amassed a database of 23 million people and 1.5 million companies.  All of the data is for sale at $6.50 per name.  Check the accuracy of your name....you'll be surprised.

The data interpretation is based upon three different technologies.  They are: Natural Language Extraction (the ability to read an English sentence and know what it means), Artificial Intelligence Algorithms (providing the ability to interpret information from various websites) and finally, Information Integration Logic (an organizer and validator of the data found).

Perhaps this information could be utilized in claims management, or life and disability underwriting.  It seems like a good start, but much more data will need to be collected.  How can we get into the social security disability system or state unemployment data?  That could really provide insight into the vailidity of claims or the worthiness of a life underwriting process.

Algorithms on the rise in 2005

Algorithms on the rise in 2005!  Wall Street is still chasing the elusive formula for beating the market.  In 2004,  algorithmic trading accounted for 9 % of all trade...it is "predicted" that in 2005 close to 21% will be done using these techniques ! 

Certainly, the employment outlook for anyone involved in any facet of data mining is on the rise.  But then if the algorithm works, who would need to work?  I guess it is more than buying low and selling hi!

There's Gold in them thar hills!

Gold, not fools gold, but real, honest to goodness riches. As if locked in a vault, insurance carriers, banks, investment firms, or any business for that matter, has a treasure of data to mine in a way to better understand the patterns and behaviors of how and why their customers tick.

As highlighted in Data Mining for Golden Opportunities, there are boundless methods to identify these nuggets.

In the past, mining for gold consisted of choosing a site and then sifting through endless amounts of dirt. Sometimes the prospector only found a few valuable nuggets, sometimes he hit upon an entire vein, but most of the time, he found nothing at all and decided to either move on to another promising spot or give up mining altogether and stop wasting his time. Today, with scientific methods and specialized tools, mineral mining is much more accurate and productive. Mining for data has evolved in much the same way. Older methods executed by business mathematicians and statisticians took a long time to yield constructive information. Now, current software and techniques help make data mining a lucrative, more accessible process for most businesses.

Kudos to the banking industry for attempting to sort through the marketing relationship between savings accounts, insurance purchases, CD and other investments.  Will the insurance industry be able to transition from a focus on underwriting modeling to marketing modeling.  Could there be another gold vein in the mine beyond the underwriting models.  Would strategic relationships between carriers (a PC carrier uniting with a Life carrier to sell each others products) enable its distribution force to be more efficient and focused?  Would profitability come easier with this approach?  After all, isn't it easier to sell an existing customer !