"smart banking- real time driven at number26", christian rebernik, cto at number 26 gmbh

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Smart Banking: Real Time Driven 1

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Smart Banking:Real Time Driven

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Real Time Banking Today

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Account opening

Money Transfer Card locking

Balance Statement

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Account opening

Money Transfer Card locking

Balance Statement

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Account opening

Money Transfer Card locking

Balance Statement

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Account opening

Money Transfer Card locking

Balance Statement

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Account opening

Money Transfer

Card locking

Balance Statement

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Banking “Innovation”

‘No Grandma ... listen, email is not a scanned letter!’

Steve Jobs

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Re-think banking from ground-up

NUMBER26

1 bank account

1 MasterCard

1 app

Our experience is designed for real time mobile first experience

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Account opening

Open your bank account online in less than 8 minutes

… every day from 8am - midnight

… including verification checks, risk scoring, whitelist/blacklist

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Money Transfer

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Intelligent push notifications inform you about

… successful card & bank transactions

… fraud attempts

… insufficient funds or exceeded limits

Transparency

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Block your card & report it as stolen

Set whether you want to pay abroad

… or online

… allow cash withdrawal or not

Real Time Control

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Technology

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Re-think banking from ground-up

NUMBER26

1 bank account

1 MasterCard

1 app

Our experience is designed for real time mobile first experience

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Account opening

Open your bank account online in less than 8 minutes

… every day from 8am - midnight

… including verification checks, risk scoring, whitelist/blacklist

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Money Transfer

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Intelligent push notifications inform you about

… successful card & bank transactions

… fraud attempts

… insufficient funds or exceeded limits

Transparency

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Block your card & report it as stolen

Set whether you want to pay abroad

… or online

… allow cash withdrawal or not

Real Time Control

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EC2ELB

SQL

No-SQL

Lambda

Machine Learning

Event Processing

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Create smarter banking

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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

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Linking transactions

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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?

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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

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Event based trigger

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Categorizing transactions

Where did I spend all this money?

Person To Person(Money Beam)

Person To Merchant (Bank Transaction)

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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 PersonUse 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 MerchantMerchants 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

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Linking and categorizing transactions

Async Inflow

machine learning for categorizations

functions for real time linking

grouped and categorized transactions

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Event based trigger

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What’s to come?

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Our Vision

Build world’s bestbank experience in every way

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Our goals

Innovation leaderby user focus.

Building a Smart Fintech-hub

Expansion to become the firstpan-European bank

70 people - 20+ nationalities

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Top 25 global payment companies -CB Insights Christian [email protected]

Top 100 hottest European startups 2015 -Wired

Top 25 hottest German startups -Gründerszene

Soundcloud, Bitcoin, Google, Rocket Internet, Zalando, Zanox, Bwin