Fintech startups are taking business away from traditional institutions like banks, exchanges, and brokerages. One of the reasons that these startups are able to compete with $30B+ behemoths like Credit Suisse and Goldman Sachs is their advanced decision making capabilities. By leveraging new data sources and better predictive analytics, companies like Ferratum Bank can make more accurate decisions in a fraction of the time. This talk will cover: Types of decisions you can automate Challenges in building predictive, financial apps First-hand, real-world examples Greg Lamp is the co-Founder and CTO of Yhat. In this role, Greg leads development of Yhat's core products and infrastructure and is the principal architect of the company's cloud and on-premise enterprise software applications. Greg was previously a product manager at OnDeck, a fintech startup in New York and before that an analyst at comScore. Greg is a graduate of the University of Virginia.

1. Microdecision Making
in Finance Services
Greg Lamp

2. Me

3. Greg Lamp
- Founder/CTO of Yhat
- github.com/glamp
Here I am on the Internet.
Hi I’m
Greg!

4. Agenda
- Intro
- FinTech basics
- Alternative Lending
- 2 Case Studies: Ferratum & VIA SMS
- Q & A

5. FinTech

7. Consumer & SMB Lending
Wealth Management
Investing & Trading
Credit & Reporting
Financial Literacy
Mortgages

8. Consumer & SMB Lending
Wealth Management
Investing & Trading
Credit & Reporting
Financial Literacy
Mortgages

9. Alternative
Lenders

10. Banks are bad
at lending to
small entities
Inconsistent
data on Small
Business /
Consumers

11. Banks are bad
at lending to
small entities
Lots of due
diligence for
small amount of
capital

12. Manual
inaccurate risk
difficult to automate
expensive
time consuming
Bad Data

13. software
problem

14. ● Aggregate disparate data sources
● Advanced analytics to decrease risk
● Automate using software

15. Lending $500 requires
the same effort as
lending $500,000

16. Winning
Formula

17. Borrowers
seeking < $250K

18. Borrowers
Acceptable Risk
seeking < $250K
8%-12% loss rate

19. Borrowers Data
seeking < $250K
8%-12% loss rate
FICO, Social, Survey
Acceptable Risk

20. Borrowers Data
seeking < $250K
8%-12% loss rate
FICO, Social, Survey
Analytics
advanced modeling
Acceptable Risk

21. advanced modeling
Acceptable Risk
Analytics
Borrowers Data
seeking < $250K
8%-12% loss rate
FICO, Social, Survey
Sweet
Spot

22. Aggregate data and
use predictive analytics
to automate decisions

23. Difficult

25. ● Leading small business
lender in U.S.
● IPO in 2014
● $4 billion in loans
● Recently expanded
internationally (Canada,
Mexico)

27. Data
Science
Application
Developers

29. Data Science Application Developers
We let you ship analytics fast.

32. Europe
things get a little trickier

33. 742M people
$27,500 GDP / capita

34. 50 countries
different regulations, banking

35. 23+ languages
not everyone speaks English
50 countries
different regulations, banking

36. 50 countries
different regulations, banking
no central
credit data
hundreds of credit bureaus
23+ languages
not everyone speaks English

38. Case Study
Ferratum Bank

41. - Consumer lender HQ in
Finland
- IPO in 2015
- Largest mobile bank in EU
- 22 countries
- 1.5 million customers

44. 7 22
countries

45. 15%
decrease in loss rates

46. Case Study
VIA SMS

49. - 6 countries
- €60 million lent annually
- Loan size €300 - €700

50. 100K+
originations per year

51. Risk
Fraud
Pricing

52. Risk
Fraud
Pricing

53. 13%
better model performance

54. Bite-sized decisions
leads to better & faster
performance

55. makes it easy to
automate decisions

56. FinTech

57. FinTech ...and others

58. Founded in 2013
HQ in NYC
(Mighty) Team of 11
Investors

59. ● FinTech uses technology to beat
banks
● Alternative Lending runs on
predictive analytics
● Yhat automates decisions

60. Thanks!
greg@yhathq.com