Join us for an easy-to-use playbook with detailed steps to help you get your AI project funded. Intelligent applications to deal with fraud and money laundering are essential for modern risk management in financial services, banking and retail. However, AI projects dealing with fraud often miss out on funding because stakeholders span many organizations and need very different levels and types of information; from technical to financial evaluation, nuanced details can accelerate or stall a projects depending on how they are presented.

2. Intro
Why we need to build a business case, especially for these
solutions
How we can build a business case
Conclusion & Q/A

4. In any high-tech project
In any graph project
In any graph-enhanced fraud solution...

5. NO
STRONG
CASE

6. People are not buying into graph-enhanced fraud solutions
because
these solutions are DIVERGENTtechnologies

7. Convergent:
• Something you have bought
before
• You understand your
requirements
• You understand your
evaluation criteria
• You know what to expect
Divergent
• Something new, that you
have never bought before
• You may not understand
fully
• You may not know how to
evaluate / compare
• You may not know what to
expect

8. High-tech business interpretation of fundamental, Nobel
prize-winning behavioral scientific work by Kahneman & Tversky:
Prospect theory: how humans make
decisions under uncertainty

9. What would you choose?
1. a 95% chance to win
$10000
2. a 100% chance to win
$9499
What would you choose?
1. a 95% chance to loose
$10000
2. a 100% chance to loose
$9499
In times of uncertainty, people will
choose lower / undervalue uncertain rewards
choose higher / overvalue uncertain losses

10. Divergent Tech = Uncertain tech
3 main decision factors at play:
• p(V): the perception of Value (rewards)
• p(R): the perception of Risk (losses)
• C: the Cost (losses)
People will compare p(V) to p(R)+C

11. For any human being to make a decision on Divergent Technology
p(V) >> p(R)+C
NEEDS to hold true. Otherwise
NO DECISION

12. The p-factor: we are talking perception
We can influence perception
How we influence perception, depends on the specific question at
hand
In the case of business decisions, we need to take the uncertainty /
perception OUT OF the equation, by adding more quantitative,
objective, not-subject-to-interpretation data points

13. Influencing p(V):
• response times,
• speed,
• # servers,
• # cores,
• realtime vs batch,
• # people,
• # mandays,
• etc...
Influencing p(R)
• Be there for the customer,
• manage expectations,
• technical excellence,
• show how it's done,
• we've done this before,
• here's a reference,
• ...
This is what we call a BUSINESS CASE

15. Answers!