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Managed analytics saves you money

5.0
2 reviews

We are experts in creating real value for clients through the use of data analytics and help clients assess data needs and opportunities. 

Business Data Miners takes the worry out of analyzing and understanding your data. We manage the process of data preparation and analysis, data modeling, and integration into your ongoing operations. Our dashboards and web reports provide timely insights that allow your company to more easily communicate and collaborate both internally and externally. Our solutions and services have saved our clients hundreds of millions. They include:

  • Credit risk management: Statistical models for mortgages, car loans, bad debt, credit scoring, account churn, and risk charts to aid decision making
  • Data Analytics: Analyze client data to identity underlying hidden patterns to increase competitive advantage, e.g., customer loyalty analyses, product cross-sell modeling, and sales forecasting.
  • Fraud prevention: Automated decision models to assist identity checking, credit/debit card transaction fraud, cards breached, check deposit fraud, claims fraud, internal fraud
  • Social media analytics: Statistical analysis to support marketing and customer service activities
READ MORE...
 
$5,000+
 
$200 - $300 / hr
 
2 - 9
 Founded
2009
Show all +
Weston, MA
headquarters

Portfolio

Key clients: 
  • Sprint Nextel
  • Citizens bank
  • Fortune global 100 bank
  • Fortune global 500 entertainment company
  • Top 3 healthcare insurance company
  • Cincinnati Bell Wireless
  • Border City Media

Reviews

5.0
2 reviews
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Customer Predictive Modeling for Telecommunications Corporation

"They have a great ability to pick a very technical topic and learn the modeling techniques quickly."

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5.0

Quality: 
5.0
Schedule: 
4.0
Cost: 
5.0
Willing to refer: 
5.0
The Project
 
$50,000 to $199,999
Project summary: 

Business Data Miners built a custom predictive model of customer credit for a large telecommunications provider. The team also evaluated perspective customer financing risks.

The Reviewer
 
1001-10,000 Employees
 
Chicago Metro Area
Director, Fraud, Credit and Collections, Leading Telecommunications Firm
 
Verified
The Review
Feedback summary: 

The team built a highly functional model that was used as a long-term tool. Business Data Miners has an intelligent and innovative team that learns and applies new techniques quickly. They do not always pitch their ideas well, but they follow through and know the data and technology. 

BACKGROUND

Please provide a brief description of your firm.

We are one of the largest telecom carriers in the U.S., behind Verizon.

What is your role and responsibilities? 

I was the director of the Credit Risks department at the time. I was responsible for bad debts, and setting credit rules for our company.

OPPORTUNITY / CHALLENGE

What was your business goal for the project with Business Data Miners?

Our company was using off-the-shelf modeling software to evaluate consumers. As we grew, we realized we needed to build a custom model and we talked with a few vendors. We gave them a common set of data, and ask them to build a predictive model for whether consumers would be a good credit risks for wireless service. Their team built the best model from that competition, so we chose them to evaluate perspective customer financing risk.

SOLUTION

Can you talk more about the model?

It was designed to give the most accurate evaluation based on a credit bureau score and basic demographic information. The model gave the likelihood of a customer being able to pay, and our management decided which scores were acceptable for credit. Sometimes, we decided to maximize sales, and sometimes we decided to minimize bad debt. Business Data Miners did their job by coming up with the pay score accurately.

When was that project completed?

In 2001, I think.

Can you give us a sense of the size of the initiative in dollar terms?

I don’t recall the exact figures, but it had a pretty significant revenue impact. Every transaction they worked on involved a few cents add-on per transaction, and there were more than one million a month being conducted. That adds up to a pretty significant number.

RESULTS & FEEDBACK

Do you have stats or metrics to track improvement?

The model worked, and I believe it was used for three to four years. That longevity alone shows how accurate and predictive the model was. Most models will be updated before four years.

What is unique or special about Business Data Miners compared to other vendors?

They are classic data geeks, in a good way. They have very smart Ph.D.s working for them for years. They have a great ability to pick a very technical topic and learn the modeling techniques quickly. They also use innovative, new trends to help the work. The model must provide results that are useful to help a business make decisions. They get the job done without any frills or fuss.

Looking back on the project, is there anything that you think Business Data Miners can improve upon, or something you would do differently?

I don’t think Larry [Bookman] is a real slick presenter. Larry and his team are good people to have in the room during client meetings, but probably not the right guy to lead the presentation when you’re pitching the material to the client. However, they really know data and understand the technology. This is the most important thing. They help us make correct business decisions.

5.0
Overall Score Our experience is positive.
  • 4.0 Scheduling
    ON TIME / DEADLINES
    They finish everything on time but sometimes things get sidetracked.
  • 5.0 Cost
    Value / within estimates
    We were very pleased with the value for what we spent.
  • 5.0 Quality
    Service & deliverables
    It’s very good.
  • 5.0 NPS
    Willing to refer
    Very likely.

Predictive Risk Scorecard for Auto loan Financing

"[The finished scorecard] gave us some real competitive advantage[s], and indirectly saved us a lot of money."

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5.0

Quality: 
5.0
Schedule: 
5.0
Cost: 
5.0
Willing to refer: 
5.0
The Project
 
$50,000 to $199,999
Project summary: 

Business Data Miners created a custom scorecard to track subprime auto loans. The team worked with historical data in over 20,000 files to create an accurate prediction model for new applicants. 

The Reviewer
 
Large enterprise
Chief Risk Officer, Auto Financing Firm
 
Verified
The Review
Feedback summary: 

The team provided professional service and dialogue during the project. Business Data Miners created a functional product that worked perfectly. They went above and beyond in helping to clean up the data used for analytics, sometimes identifying systematic issues. 

BACKGROUND

Can you describe your company in brief detail?

The company that Business Data Miners did the work for is an indirect auto finance company.

What was your role?

My role was the chief risk officer.

OPPORTUNITY / CHALLENGE

What business challenge were you trying to address with Blue Fountain Media?

We wanted to have a custom scorecard built to track subprime auto loans. In order to do a custom scorecard, their team had to take historical data on more than 20,000 files, and then analyze that data and come up with predictive analytics that would allow us to use that historical data to predict the performance of new applications.

That company was a finance company just financing cars. We offered our services to automobile dealers and those dealers who had non-prime customers would submit applications to us. We would use predictive analytics that [Dr.] Larry [Bookman, co-founder and president of Business Data Miners] built for us to score a credit bureau, and tell us whether that bureau was a risk that was worth taking or not. If we didn’t want to take the risk, then his model also helped us decide how we should price that risk. The model calculated the rate to charge that customer based on their risk profile in order for us to meet our economic targets.

SOLUTION

What technologies or platforms were used for that data work?

In our own environment, it’s an electronic bureau from Acrofax, TransUnion, or another provider. That bureau would be transmitted to us electronically. It would automatically get fed into this algorithm that they built based on the analytics. That algorithm would spit out a credit score, and that score told us what we needed to know about the risk of that particular applicant.

What was your process for selecting Business Data Miners to work with?

They were referred to us by a company that we were already doing some business with. In fact, Larry was providing a contract role. I don’t know what the exact arrangement was. This was a Canadian company based in Toronto, Ontario, Canada. When we said we wanted to have a custom scorecard built, they put us in touch with Business Data Miners.

I looked at about 20 or 30 different cuts to optimize the data. I think we gave him around 300 different data points. He had to sort through all that. Scorecards typically only have about 10 to 15 different data elements to them. You’re sorting through mounds of data in order to come up with the 10 or 15 elements within that data that actually have a bearing on risk and predicting risk and predicting performance. It’s not an easy process, but the scorecard that he built for us was highly effective. It gave us some real competitive advantage, and indirectly saved us a lot of money by not taking on as many bad loans.

Can you give us a sense of the initiative in a dollar figure?

It was in the low six figures.

RESULTS & FEEDBACK

How did Business Data Miners perform throughout the project?

In terms of the service level and useful dialogue we had with Business Data Miners, it was very professional. The end product did exactly what it was supposed to do and performed very well. That particular score card was only in use for about four years. Then the business was sold to a bank. The bank had its own analytics team. The bank used its own team to build the next evolution of the scorecard. Even with four more years of data, they didn’t really build something that was more predictive.

I think what Business Data Miners built was as predictive as it could be based on where the business was in its current state of development. By the time they built the next evolution, they tripled the size of the business. I think they got a 10 or 15 percent lift in terms of the predictability of the latest scorecard.

What is unique or special about Business Data Miners?

That wasn’t a tendered scenario. I’m missing some comparativeness. Typically, when you have a scorecard company do some work for you, they want clean data. The data they get from companies is typically not that clean. Their team not only worked with us to help, but clean up the data. Most companies would just reject anything that didn’t look like clean data. In this case, they identified a number of different things that seemed to be systemic. We were able to do a very material cleanup of our data rather than just throwing it out. He took the extra step to do that, which makes Business Data Miners stand out.

Documentation is very important in these projects. I know that four years later when the bank and their own people reviewed all that work, they commented that his documentation was outstanding

Is there anything that you think Business Data Miners could improve upon or something you might do differently?

No.

5.0
Overall Score It was a very well-run project. I’m very happy.
  • 5.0 Scheduling
    ON TIME / DEADLINES
    We had some really tight deadlines and gave them basically a month to do two months of work, and they did it. I think they dropped everything else to hit our deadline.
  • 5.0 Cost
    Value / within estimates
    I’d say it was all fair at the end of the day. I can’t remember having any difficulty with what we had to pay.
  • 5.0 Quality
    Service & deliverables
    They did the scorecard, and we didn’t have to go back to them for anything.
  • 5.0 NPS
    Willing to refer
    We’re going to use them again here shortly. We were always impressed with their work.