Gaming the Odds and Gaining Competitive Advantage with Automated Onboarding

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Transcript of Gaming the Odds and Gaining Competitive Advantage with Automated Onboarding

Gaming the Odds and Gaining Competitive Advantage with

Automated OnboardingPresented by Recombo CEO, Mike Gardner

on Wednesday, March 11th 2015 at:

So you probably think that I’m going to tell you how much faster you could underwrite, and how much money you could save, if you automated your underwriting?

Well I could…

But, my guess it that you

already know that’s something

you should be doing.

What you will learn today:

1. How your risk department can use basic statistics concepts to unlock revenue

2. How a risk score is developed and how it is often determined improperly

3. What you need to do get started for your organization

Las Vegas is the best city in the world to teach us that there is MONEY tucked inside of RISK.

There’s a lot that needs to be done to unlock the value of merchants…

Pass/fail reviews only provide “buckets” for sorting merchants

A histogram of your merchants can provide a a view of your merchant profile.

So if this a chart (histogram) of all the merchants that submit applications to your firm, can you see the money you’re leaving behind?

How about now?

Too Risky to do Business With

OK, how about now?

Too Risky to do Business With

Do Your Own Math

Assume the following:• Average monthly value of a merchant $2500

• Average merchant applications per month 100

• 80% of merchants get approved

The cost of false positives in your risk model:

5%: $30,000/annum

15%: $90,000/annum

25%: $150,000/annum

Consider the following:

How much time, if any, is your organization spending reviewing the merchants you declined, rather than looking for new merchants?

Hang on though, Mike! I don’t want to be taking on more risk for my organization!

Risk isn’t a point – it’s a range.

High Risk

Low Risk

Your Threshold of Risk

0 100Your Risk Score

What you score, is as important as how you score

Rep

uta

tio

n

45

pts

Del

iver

y M

eth

od

68

pts

Val

ue

20

PtsId

enti

ty 7

5p

ts

1. Identity 2. Validity3. Legitimacy4. Financial Acceptability5. Risk Level

High Risk

Low Risk

Your Threshold of Risk

0 100Your Risk Score

Remember that underwriting is like a court room; your merchants are presumed innocent, and your underwriting team is a prosecuting attorney

As the case stacks against merchants, the less desirable they become as clients

Rep

uta

tio

n

45

pts

Del

iver

y M

eth

od

68

pts

Val

ue

20

Pts

Reputation 45pts

Delivery Method 68 pts

Value

20 Pts

Iden

tity

75

ptsSorry,

too risky

High Risk

Low Risk

Your Threshold of Risk

0 100Your Risk Score

But when we use lots and lots of data sources in our underwriting, we increase the probability that our data potentially “overlaps.”

This is a “specification error” and I can almost guarantee that if you’re scoring, you’re over specifying.

Imagine our fictitious merchant is the big yellow circle below, and we want to use just three variables to describe his risk:

• Reputation

• Chargebacks

• BBB rating

Rep

Chargebacks

BBB

All these little areas of overlap are the

problem

If we COULD calculate that overlap area (which we can’t), and we took out that double counting, we’d find our merchant is actually within our threshold of risk – but we turned him down!

Reputation 45pts

Delivery Method 68 pts

Value

20 Pts

Hey, I’m not risky; I’m a false positive.

So now, when you look at your merchants, you know the money is sitting right on the edge – it’s the “good” people you’ve said no too

Since our risk models are likely “over specified,” our first, and possibly most valuable place to look for opportunity, is with the people you’ve turned away.

Rep

Chargebacks

BBB

So what do I you want you to do?

Score everyone – At minimum, you should be automating your underwriting process so that you’ve got good data.

What else do I want you to do?

• Keep every score you’ve calculated. You need this data to understand the distribution of your applicants

• Regularly review the “marginal no applicants”. These are opportunity

And finally…

Monitor your data sources to make sure they aren’t “getting smarter” at your expense. As your data providers widen the number of variables they are considering, they are increasing your probability of “overlap.” You need to keep adjusting your risk models and weightings accordingly.

The ETA recommends that companies maintain an “agile approach to underwriting…constantly reflecting improvement”.

Remember this: Constantly reflecting improvement means it is TURNING DOWN AS FEW merchants as possible, NOT checking every imaginable item to reduce your risk to zero.

To learn more about Rapid Customer Onboarding, and how it impacts and shapes underwriting in the payments market, come visit us at www.recombo.com, here at MAC, or upcoming at Transact15 in San Francisco.