Predictive modeling becomes affordable for mid-market customers
Clever predictive models and analytics are used mainly by the large Fortune 3000 companies. They are often complex, require highly trained users, and are prohibitively expensive to deploy and manage. In the same way as BI vendors promise “bringing BI to the masses”, eBureau promises “predictive scoring for the masses”. The strategy is similar: make the solution quicker and easier to deploy, reduce the up-front costs, and improve the speed of response and overall performance.
So what is predictive scoring? When you apply for a loan, the loan provider refers your application to a credit bureau like Experian or Equifax. They add up your outstanding loans and credit cards debts, review how well you have performed (e.g. did you make all your repayments on time?) and “score” the credit risk for the inquiring lender, predicting the probability of repayment default for the loan provider. There are however other uses for predictive scoring.
eBureau is a VC-funded start-up that claims to offer a ‘next generation scoring and information bureau’. eBureau offers marketing and lead generation (to score customer attractiveness), customer retention and promotions (to score customer response), payments and e-commerce (to score fraud and credit risk), and accounts receivable management (to score the likelihood of debt recovery) applications. These are proving particularly attractive for mid-market and direct marketing companies—typically companies preferring to rent outsourced services rather than buy a more expensive in-house technology solution.
eBureau builds a scoring model for every customer, and offers each custom score as a hosted service. This means eBureau charges its customers a fraction of a dollar for each transaction or score. This sounds a bit like the Google Adwords model—which is no bad thing—you only pay for what you receive.
The method for delivering this service is eBureau’s secure, US-based hosting center that contains over 150 Terabytes of data. Much of this data is the c. 100 billion data records it integrates from 3rd party providers. eBureau claims to add an additional 3 billion new records every month. These include household demographics files, directories, purchase and payment histories, bankruptcy and other government filings, and 1000s of other databases. By mashing together the data sets of a client with its own, eBureau is able to deliver higher quality results than had the client executed this process in-house. This is tangible value-add.
eBureau claims that model development normally takes only a few days, and has no elaborate consulting requirement as it is a template-driven, heavily automated process. Although this sounds impressive, eBureau still has a David and Goliath battle on its hands against the two heavyweights of predictive scoring and analytics market, Fair Isaac ($800m revenues) and SAS ($1.9Bn revenues). Whether these suppliers seriously wish to engage the relatively unserved mid-market with custom scoring models is open to question, which might just enable eBureau to seize the “1st mover advantage”. Well, it worked for David.