transfer wise data talk 2

FIGHTING FRAUD WITH GOOD CUSTOMERS IN MIND

LAUR

+

MAKING THE FINANCIAL SYSTEM FAIR AND TRANSPARENT

€700 MILLION IN TRANSFERS PER MONTH

€30 MILLION OF CUSTOMERS MONEY SAVED EVERY MONTH

TRUSTED ALL OVER THE WORLD

CAN SEND MONEY FROM

TRUSTED ALL OVER THE WORLD

CAN SEND MONEY TO

FRAUD 101

CHARGEBACK =

PRICE

WHAT TO DO ABOUT IT?

FRAUD AGENTS>>>

MANUAL REVIEW

TEAM

FRAUD ENGINE

STATIC RULES

SCO

RING

RULES

80+ YEARS OLD

+10“FUN”

FRAUD ENGINE

STATIC RULES

SCO

RING

MANUAL REVIEW

RULE BASED SYSTEM- Become outdated

- New rule for each pattern

PRICE

PRICE SPEED

PRICE SPEED

CONVENIENCE

PRICE SPEED

CONVENIENCE COVERAGE

TEAM

FRAUD ENGINE

STATIC RULES

SCO

RING

DYNAMIC RULES

FEATURE 1 FEATURE 2 FEATURE 3DYNAMIC RULE MODEL

SOURCE CURRENCY AMOUNT TIER £ NUMBER IN EMAIL?DYNAMIC RULE MODEL

FEATURE 1 FEATURE 2 FEATURE 3

SOURCE CURRENCY AMOUNT TIER £ NUMBER IN EMAIL?

USD 100-200 Yes

EUR 1000-1100 Yes

GBP 500-600 No

…

DYNAMIC RULE MODEL

DYNAMIC RULE 1

DYNAMIC RULE 2

DYNAMIC RULE N

FEATURE 1 FEATURE 2 FEATURE 3

SOURCE CURRENCY AMOUNT TIER £ NUMBER IN EMAIL?

USD 100-200 Yes

EUR 1000-1100 Yes

GBP 500-600 No

…

DYNAMIC RULE MODEL

DYNAMIC RULE 1

DYNAMIC RULE 2

DYNAMIC RULE N

FEATURE 1 FEATURE 2 FEATURE 3

30%

70%

76%

SOURCE CURRENCY AMOUNT TIER £ NUMBER IN EMAIL?

USD 100-200 Yes

EUR 1000-1100 Yes

GBP 500-600 No

…

THRESHOLD: 65%

DYNAMIC RULE 1

DYNAMIC RULE 2

DYNAMIC RULE N

FEATURE 1 FEATURE 2 FEATURE 3

30%

70%

76%

DYNAMIC RULE MODEL

SOURCE CURRENCY AMOUNT TIER £ NUMBER IN EMAIL?

USD 100-200 Yes

EUR 1000-1100 Yes

GBP 500-600 No

…

THRESHOLD: 65%

DYNAMIC RULE 1

DYNAMIC RULE 2

DYNAMIC RULE N

FEATURE 1 FEATURE 2 FEATURE 3

30%

70% ADD +10

76% ADD +10

DYNAMIC RULE MODEL

PRICE SPEED

CONVENIENCE COVERAGE

FRAUD ENGINE

STATIC RULES

SCO

RING

DYNAMIC RULES

MANUALLY DEFINED:- SCORES- THRESHOLDS

FRAUD ENGINE

STATIC RULES

SCO

RING

DYNAMIC RULES

MANUALLY DEFINED:- SCORES- THRESHOLDS

NEW RULE MODEL FOR NEW PATTERN

TEAM

MACHINE LEARNING

MACHINE LEARNING

BLACK BOX Machine learning algorithm

RU

LES

OU

TPU

T

FRAUD SCORE 0..100

PARAMETERS Θ .

..

Act

IteratePredict

Act

IteratePredictTRAINING

ENGINE AGENT

Act

IteratePredictGOOD

/

BADPARAMETERS Θ

FRAUD SCORE

TRAINING

ENGINE AGENT

STATIC RULES

MAC

HIN

E LEARNIN

G

DYNAMIC RULES

FRAUD SCORE 0..100

FRAUD SCORE 0..100

0%

25%

50%

75%

100%

FPR – % of customers stopped for manual review

0% 25% 50% 75% 100%* ILLUSTRATIVE

0%

25%

50%

75%

100%

FPR – % of customers stopped for manual review

0% 25% 50% 75% 100%* ILLUSTRATIVE

RISK MANAGEMENT

* ILLUSTRATIVE

PRICE SPEED

CONVENIENCE COVERAGE

JASON TAN“NOT A RACE BETWEEN ALGORITHMS”

BLACK BOX Machine learning algorithm

TRA

NSA

CTI

ON

DAT

A

FRAUD SCORE 0..100

PARAMETERS

SCALE DATA

FEATURE ENGINEERING• Number in email • Name in email • Device fingerprinting • Geo-location mismatch

• …

OUR CHALLENGE

80 - 20

THANKS! Q?