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Smart Banking:
Real Time Driven
1
2
Real Time Banking Today
3
Account opening
Money Transfer Card locking
Balance Statement
4
Account opening
Money Transfer Card locking
Balance Statement
5
Account opening
Money Transfer Card locking
Balance Statement
6
Account opening
Money Transfer Card locking
Balance Statement
7
Account opening
Money Transfer Card locking
Balance Statement
8
Banking “Innovation”
‘No Grandma ...
listen, email is not
a scanned letter!’
Steve Jobs
10
Re-think banking from ground-up
NUMBER26
1 bank account
1 MasterCard
1 app
Our experience is designed for
real time mobile first experience
11
12
Account opening
Open your bank account online in less than
8 minutes
… every day from 8am - midnight
… including verification checks, risk scoring,
whitelist/blacklist
13
Money Transfer
14
Intelligent push notifications inform you about
… successful card & bank transactions
… fraud attempts
… insufficient funds or exceeded limits
Transparency
15
Block your card & report it as stolen
Set whether you want to pay abroad
… or online
… allow cash withdrawal or not
Real Time Control
16
Technology
17
Re-think banking from ground-up
NUMBER26
1 bank account
1 MasterCard
1 app
Our experience is designed for
real time mobile first experience
18
19
Account opening
Open your bank account online in less than
8 minutes
… every day from 8am - midnight
… including verification checks, risk scoring,
whitelist/blacklist
20
Money Transfer
21
Intelligent push notifications inform you about
… successful card & bank transactions
… fraud attempts
… insufficient funds or exceeded limits
Transparency
22
Block your card & report it as stolen
Set whether you want to pay abroad
… or online
… allow cash withdrawal or not
Real Time Control
23
EC2ELB
SQL
No-SQL
Lambda
Machine Learning
Event Processing
24
Create smarter banking
25
Identify transactions which should be linked
Clustering: Too many false positives
Vector Space Modelling allows better
grouping into logical groups
- represent each transaction as feature vector (d1, d2, q)
- Find the closest vector (lesser angle between two vectors) for
a query transaction vector (q) in terms of cosine similarity
- Similarity score quantifies the likelihood of linking multiple
transactions together
26
Linking transactions
27
Linking Transactions
Linking transactions helps you to keep track
of your finance
E.g. you order 10 items and return 9 of them
How can you make sure you received a
refund for all of them?
28
Simplifying the financial transaction overview
You’ll see all related transactions
in just one screen
… making it easy to follow up
… and to understand your spendings
and income
Linking transactions architecture
Async Inflow
functions for
real time linking
grouped
transactions
29
Event based trigger
30
Categorizing transactions
Where did I
spend all this
money?
Person To Person
(Money Beam)
Person To Merchant
(Bank Transaction)
31
32
Simplifying the financial transaction overview
Grouping your expenses automatically
into useful spending clusters
… making it easy to analyze
… and to understand your spendings
and income
To Person
Use reference text
State of the art NLP techniques to
parse, tokenize, lemmatise texts to
extract sense.
Semantic sense leads to smart
categorization
Based on a lexical database and
translation engines, it is possible to
find near exact sense from the texts.
Examples:
“Yufka for 2” => Food
“Nudeln” => Food
“debit from a doctor” => Health
“Babyoel” => Children
“Taxifahrt” => Cars 33
To Merchant
Merchants play a vital role. If you spend
money at “Vapiano”, we know instantly.
How can you teach a machine to
categorized it as “Bar and Restaurant”?
Using the Machine Learning
- Learn Model on card transactions
- Train model
- Test model on bank transactions
Tested methods to determine the
transaction category on F-1 score
- Naive Bayes 0.57
- Supported Vector Machines 0.80
- Multiclass logistic regression: 0.9
Best Result: multiclass logistic regression
34
Linking and categorizing transactions
Async Inflow
machine learning for
categorizations
functions for
real time linking
grouped and
categorized
transactions
35
Event based trigger
36
What’s to come?
37
Our Vision
Build world’s best
bank experience
in every way
38
Our goals
Innovation leader
by user focus.
Building a
Smart Fintech-hub
Expansion to become the first
pan-European bank
70 people - 20+ nationalities
39
Top 25 global payment companies
-CB Insights Christian Rebernik@number26.de
Top 100 hottest European startups 2015
-Wired
Top 25 hottest German startups
-Gründerszene

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"Smart Banking- Real Time Driven at Number26", Christian Rebernik, CTO at Number 26 GmbH