how fintechs and blockchain technology might change banking · fintech landscape germany: key facts...

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How FinTechs and blockchain technology might change

banking

XXXVII Heidelberg Physics Graduate Days

Heidelberg, October 12th, 2016


Agenda

» 2 What is FinTech?

» 14 What can banks learn from the start-up world?

» 21 Is FinTech here to stay?

» 25 What is blockchain technology?

2016-10-12 | How FinTechs and blockchain technology might change banking


What is FinTech?

2016-10-12 | How FinTechs and blockchain technology might change banking | What is FinTech?


What are FinTechs?

Start-ups usually have one or more of the following characteristics:

Use new technologies, such as the blockchain

User friendly Address specific customer pain points

Unbundling Service offering is simple, clear and focused

Processes are automated and fast Efficient

Innovative

The term FinTech (Financial and Technology) refers to technology companies offering financial

products or services.

No exact definition: wider and narrower definitions are used.

2016-10-12 | How FinTechs and blockchain technology might change banking | What is FinTech? (1/11)


All stakeholders in the financial services industry are affected

Exchanges

By reshaping service offerings and business models, potentially all players are affected by FinTech.

Clearing houses Central Banks

Insurances Banks Asset Managers

Corporates Regulators …

Today our focus is banking.



Core service areas are affected

Source: Unbundling of a European Bank, CBinsights

Retail

Banking

» Basis banking (account, etc.)

» (Cross-border) payments

» Saving

» Investments

» Financing

Unbundling the bank: FinTech start-ups are evading most of the service areas of banking.

Corporate

Banking

» Trade finance

» Treasury and cash management services

» Financing

» Risk management (derivatives, etc.)

» Investment banking



FinTech landscape Germany: key facts

1 http://www.eu-startups.com/2016/08/german-fintech-companies-secured-80-more-funding-than-their-uk-based-counterparts-in-q2-2016

>300 FinTech start-

ups in Germany

Number of start-

ups grows rapidly

Areas: Lending,

Investment,

InsurTech and

many more

Total VC

investment

293M€

Q1+Q2 2016 1

Initially mostly

B2C, but B2B

segment grows

Berlin, Munich,

Frankfurt,

Hamburg



Spotlight on key areas in the FinTech space

Saving and investing

» Robo-Advisor

» Time money

» Crowdinvesting

» …

Example:

Scalable Capital

RegTech / RiskTech

» GRC solutions

» Ratings

» KYC

» …

Example:

Alyne

Banking

» Challenger Banks

» Corporate Banking

» Social Banking

» …

Example:

N26

Financing

» P2P lending

» Factoring

» Comparison

» …

Example:

wroomer

API-Banking

» Banks

» Aggregators

» Open Source

» …

Example:

SolarisBank

Payments

» P2P payments

» POS solutions

» B2B solutions

» …

Example:

Cringle

Blockchain

» Software Solutions

» Cryptocurrencies

» Applications

» …

Example:

Monax (Eris Industries)

Other areas

» IT-Security

» Donations

» Accounting

» …

Example:

Fenror7



Core capabilities of banks are affected

» Product offering

» Customer facing

applications

» Client services

» …

» Improved user

experience

» Innovative services

addressing specific

customer pain points

Front Office

Focus

» Calculation, controlling

and management of

risks

» Regulatory reporting

» …

» Manage risks more

efficiently

» Ease the burden to fulfil

regulatory requirements

RM & Compliance

Focus

» Back office functions

» Securities

settlement

» Payments

» Derivatives BO

» IT Security

» …

» Automated and efficient

processes to reduce

costs and enable better

services

» More agile IT allows

business to adapt

Ops & IT

Focus



What sets FinTech start-up models apart from existing offerings?

Embrace (innovative)

technology

New digital business

models

Addressing specific

customer needs

Example Credit Ratings

Use machine learning

approach and new data

sources to determine

creditworthiness of a client

Example P2P lending

Create P2P platforms to

match investors and

borrowers.

Example Robo-Advisory

Create an easy, transparent

and cost-efficient way for

investments



Barriers to market entry are reduced more and more: some examples

» Amount and complexity

» Interpretation

» Applicability

» Uncertainty about future changes

Regulators are interested

in new market

participants and

technologies

Regulation

Demography

» Large parts of assets currently sits with older part of

population that are less technically experienced Millenials

Proprietary

structures

» Expensive, slowly changing complex systems

» e.g. proprietary networks like SWIFT, MarkitWire

etc. API Banking

Complexity of

finance

» Finance is complex, intransparent and

mathematical Innovate a niche area first

Technology

» In the past often high investment in IT infrastructure

where necessary Technology became less

and less expensive



How regulators are helping to support the FinTech developments: two

examples

» Aims of the regulations:

» Same competitive conditions for all

players in the payments space

» Increase in transparency,

efficiency and choices for users of

payment services

» Introduction of new payment services

through Third Party Providers (TPP)

» Banks will need to allow these provides

in certain circumstances to access their

IT systems (XS2A)

» Payment Initiation Services (PIS)

» Account Information Services (AIS)

Payment Services Directive 2 (PSD2)

» Financial Conduct Authority (FCA) is

the main regulator for banks in the UK

» FCA interested in financial innovation in

the interest of consumers

» Dedicated team and contact that

provides help to FinTechs in regulatory

questions

» Assistance in preparing and making an

application for authorisation

» Regulatory sandbox

FCA Innovation Hub

This type of support reduces barriers to entry in financial markets.



Clients expectations towards digital service offerings increase

Source: ING-Diba

Millenials

» Today 10 to 19 years of age

» Also 19 to 30 years old that have fully adapted to the digital world

» Currently around 10% of the population in Germany

80%

sleep with their phone next to their bed

56%

would refuse to work at a company that

bans social media

53%

would give up their sense of smell instead

of their social networks

27%

prioritize keeping up-to-date on Facebook

above dating, listening to music and going

to parties

Innovations is partially driven by changing customer expectations.



Surveys show that clients are not fully satisfied with their banks

Source: http://www.millennialdisruptionindex.com/

71%

would rather go to the dentist than

listen to what banks are saying.

33%

are open to switching banks in the next

90 days.

53%

don‘t think their bank offers anything

different than other banks

68%

say that in 5 years, the way we access

our money will be totally different.

70%

say that in 5 years, the way we pay for

things will be totally different.

33%

believe they won’t need a bank at all.

73%

would be more excited about a new offering in financial services from GOOGLE,

AMAZON, APPLE, PAYPAL or SQUARE than from their own nationwide bank.

Customers are open to offerings of new market participants.



What can banks learn from the start-up world?

2016-10-12 | How FinTechs and blockchain technology might change banking | What can banks learn from the start-up world?


Banks have capital, resources and client base. Start-ups have…

Agility

» Agile product development (no waterfall approach)

» Learn and fail fast

» Acquire quick customer feedback and take into account in

product offering (iterative approach)

Customer focus

» “Get out of the building” approach

» Often start in a niche market and address specific

customer pain points

» Extend the product in a stepwise manner

Technology

» Start-ups can build their product from a clean slate

» Modern IT architecture (e.g. cloud)

» Use innovative technologies (e.g. machine learning)

2016-10-12 | How FinTechs and blockchain technology might change banking | What can banks learn from the start-up world? (1/3)


Example: Development of a Minimum Viable Product (MVP)

Ries, Eric: The Lean Startup

Avoid building products customers do not want.

Minimum Viable

Min. and viable

Crappy product Two many

resources spent

before validation

Definition 1 Definition 2

Idea

Product Data

Build

Measure

Learn



MVP Case Study

confidential



Is FinTech here to stay?

2016-10-12 | How FinTechs and blockchain technology might change banking | Is FinTech here to stay?


A lot of start-ups fail. Can we conclude that FinTech will eventually vanish?

Source: CBinsights

2016-10-12 | How FinTechs and blockchain technology might change banking | Is FinTech here to stay? (1/3)


Example Robo-Advisory: a new offering that is here to stay

Robo-Advisors offer automated investment services through web based and mobile platforms.

» Different models, from simple one-time advice

of how to invest to automated rebalancing

» Customer needs to be onboarded and answer

a set of questions depending on the service

» Personal data

» Objectives

» Knowledge & experience

» Financials

How does it work?

» Mobile / web offering that is user friendly and

easy to use

» Transparent and low costs

» Automated allocation taking out the “human

factor”

» Access to allocation strategies that can

practically not be executed by an individual

» Further additional offerings

Why use it?

No exhaustive list of German Robo-Advisors



Example Machine Learning: a technology that is here to stay

» Automate repetitive

tasks

» In customer

interaction (e.g.

chat bots) or

internal processes

Automate

» Augment

employees / clients

knowledge

» Provide further

insights

» Convenient user

interfaces

Augment

» Spot relationships

and trends in data

that could not be

discovered earlier

Discover

» Make predictions

about future events

Predict

We see four key ways in how Machine Learning can impact financial services.

Use chat bots to

automate customer

interaction.

Create warnings for

analysts or IT security

experts in banks.

Use additional data

sources to enhance

credit rating models.

Use predictive models

for investment

management.



What is blockchain technology?

2016-10-12 | How FinTechs and blockchain technology might change banking | What is blockchain technology?


The topic blockchain has been on the rise in 2015

1Google Trends analysis

Online search trend statistics of the

expression “blockchain”1

» While remaining relatively constant in

2014, the search statistics shows an

increase by more than 3-fold since

January 2015.

News search trend statistics for the

expression “blockchain”1

» Extreme increase in news-search since

January 2015.

100%

1250%

x 12,5

100%

357%

x 3,6

Online and news search have substantially increased in 2015.

2016-10-12 | How FinTechs and blockchain technology might change banking | What is blockchain technology? (1/10)


Blockchain vs Distributed Ledger Technology: Clarification of vocabulary

Blockchain In a narrow sense the blockchain is

the distributed ledger that is used to

exchange Bitcoins in the Bitcoin

network. However, many people use

the word “blockchain” to describe

the set of technologies that

constitute a complete DLT system.

Distributed Ledger

Technology General term to describe a distributed,

append-only database in which records are

immutable and the state of the database is

defined by a consensus mechanism.

Bitcoin Network The largest distributed ledger with an

embedded cryptocurrency with a

market capitalisation

of several billion dollars.

Ethereum

A public distributed ledger with extensive

smart contract capability. The corresponding

cryptocurrency is Ether.

DLs can be used to provide an immutable history of records and reach consensus between nodes

participating in the network.



The Bitcoin network is a specific implementation of a distributed ledger

1 Nakamoto, S. Bitcoin: A Peer-to-Peer Electronic Cash System

Technological Elements Bitcoin Implementation

Decentralized data management: No central

authority

Blockchain e.g. distributed ledger technology:

Distributed „P2P“ database

Consensus mechanism Proof-of-Work / Mining

Anonymity Use of a public key instead of a real name: A new

identity can be generated.

Smart Contracts Rudimental functionalities through Bitcoin script

… …

Access to the network (public / private and

permissioned / permissionless) Public / permissionless

» A white paper1 published in 2008 by the alias “Stoshi Nakamato” describes the concept of a

virtual currency called Bitcoin.

Distributed ledger is only one technology element of the Bitcoin network. The technology has to be

complemented by further elements that are suited for the respective use case.



Schematic representation of a procedure of the distributed ledger technology

(DLT)

Block i

Hash

Block i+1

Hash

Block i+2

Hash …

» A hash-code is a “fingerprint” of the previous block.

» For a new block, a hashcode of the previous block has to be generated.

» Every 10 minutes a new block is generated within the Bitcoin network.

» If there are changes to either the hash code or the block, they are not consistent anymore.

» Therefore transactions can not be easily manipulated or reversed.

…

» Distributed ledger: Distributed database, with transactions saved block wise and single

blocks connected by nested cryptographic hashes.

The DL is a distributed “append-only” database.



There are two main types of consensus mechanisms

Proof-of-Work (PoW) Proof-of-Stake (PoS)

» Consensus is reached via solving a

computationally challenging

mathematical problem

» So called miners try to solve that problem

and are rewarded if they find the solution

to that problem

» By doing that they validated the next

block

» Via the PoW mechanism the rate at

which blocks are created can be adjusted

changing the difficulty of the problem

» Time between blocks gives the network

time to synchronize

» The Bitcoin network uses this consensus

mechanism.

» The PoS mechanism is not based on the

“hashing power” of the nodes rather on

the stake they either carry in a

corresponding cryptocurrency or voting

mechanisms

» Advantage of PoS over PoW is that it

does not require as much computing

power (simple calculations based on

stake)

» Ethereum will change to PoS

For a lot of use cases in financial services the PoW mechanism is not suitable.



Smart Contracts – A definition attempt

Definition Example (Ethereum)

contract token {

mapping (address => uint) public coinBalanceOf;

event CoinTransfer(address sender, address receiver, uint amount);

function token(uint supply) {

if (supply == 0) supply = 10000;

coinBalanceOf[msg.sender] = supply;

}

function sendCoin(address receiver, uint amount) returns(bool sufficient) {

if (coinBalanceOf[msg.sender] < amount) return false;

coinBalanceOf[msg.sender] -= amount;

coinBalanceOf[receiver] += amount;

CoinTransfer(msg.sender, receiver, amount);

return true;

}

} A tradeable token can be generated in the

Ethereum network based on around 20 lines of

solidity code.

1. Smart Contracts are autonomous, i.e. after they are deployed

they can not be modified anymore and can only be used by

applying certain rules and programs. The correct execution of

these is a part of the verification process ensured by the

blockchain network.

2. The generation of a smart contract or the triggering of a certain

function of a smart contract are put into effect by transactions.

3. Therefore, changes to the state of the distributed ledger can

be controlled by a programmable business logic.

4. Smart Contracts are autonomous accounts in a blockchain

network which can themselves hold tokens or units of the virtual

currency.

5. Smart contracts can already be used in the Ethereum network.

Smart contracts enable to implement complex business logic on the blockchain.



What are potential benefits of using DLT in the financial sector?

Less

intermediaries 4

» Intermediaries could be omitted or their role could change, since some of their services are carried

out by the DL

» Reduction of transaction costs due to lower process costs

Cost cutting 2 » Reduction of IT costs by replacing complex legacy systems

» Reduction of staff costs by more efficient processes

Simplification of

processes 3

» “Golden Source” is the DL. It allows a common view for all involved parties

» Efforts for reconciliation processes might be reduced dramatically

Risk reduction 1

» Reduction of settlement risk by shortening the settlement cycle and linking payment and delivery

» Process automation reduces process risks

» Up-to-date encoding methods (compared to username/password technique) increase IT security

Automation 5 » Smart contracts enable to encode business logic on the DL

» Examples: Automated payment of dividends / coupons, processing of corporate events

Clear focus are quicker, more efficient and cost effective processes.



Central clearing of derivatives based on DLT

1. Central clearing of derivatives is done using DLT. The role of the central counterparty is limited to the handling of defaults.

2. Collateral exchange, margin calculation and further functionalities are done on the DL.

3. Smaller players can connect to central counterparties due to more efficient processes and reduced costs.

Vis

ion

Central Clearing of Derivatives

Current process Process using DLT

» Currently, a central counterparty carries out various

functions.

» This includes: Valuation of derivatives, determination of

initial margin, exchange of margins (VM, IM),

processing of lifecycle events and implementation of the

risk waterfall.

Clearing

Member

CM1

CM

CM2

CM1 CM2

Central

Counterparty CCP

CCP

1

2

Execution, Trade capture,

Confirmation

Novation to CCP

Trade

Collateral

» Substantial functions of a CCP can be carried out by a DL with sufficient smart

contract functionalities.

» Valuation, calculation and exchange of collateral can be carried on the DL

» Implementing the risk waterfalls remains the biggest challenge for a realization.

Derivate DL

Cash/WP DL

1 2 4 3

1 After a digital signature of both parties the

trade can be booked in the DL if enough

margin is available.

Automated exchange of collateral

and payments with respect to that

trade

4

2

Rebooking of collateral to a custodian

account or implementation via a so

called DAO („Decentralized

Autonomous Organizations“)

3 CM1

CM2

Execution, Trade

capture, Confirmation



Current challenges

Confidentiality » A lot of use cases require the confidentiality of data

» However in a distributed system it is inherently

difficult to do this

» Permissioned chains, pseudonymity, hash or encrypt

data, zero knowledge proofs, …

Issue Comment

Scalability » With respect to the number of transactions processed

for a given use case current technology cannot

handle the most demanding use cases

» Use PoS instead of PoW

» It is constantly improved and some vendors claim to

reach thousands of transactions per second

Governance » The community currently discusses how updates and

bugs can be handled (compare DAO hack)

» One solution can be modularized code that is

referenced by addresses

» Hard forks are not final solution

» Is an independent body of governance needed?

Legal » How can one make sure that what happens on the

chain is legally enforceable in the real world?

» Some vendors directly include a coupling of the legal

contracts with the transactions on the chain

Standardization » Currently a lot of new technologies evolve. However,

it is not desired that the ecosystem becomes too

complex and no common standards emerge.

» This remains to be seen. Open source projects are

candidates for standard setting projects.



Conclusions

DLT is still in a PoC phase and it remains to be seen to which extent promised

advantages can be realized in practice.

It is not expected that change is happening in a big bang rather changes will

happen gradually.

Using DLT will drastically change processes and impact organisational structures.

The technology has the potential to change the roles of some of the market

participants dramatically.

There will probably several blockchain implementations tailored for specific use

cases.



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