The Future of Financial Information Services

QCON Shanghai Nov 2013

Amish Gandhiwww.perpetualny.com

Amish GandhiFounder and Principal at Perpetual: Product innovation and development for financial, media and telecom www.perpetualny.com

Financial services background• Worked at Thomson Reuters for 3 years

– Global Product Manger for Reuters Messenger – Product manager for financial video service Reuters Insider

MS Computer Science from Univ of Texas, Austin

BS Computer Science from Bombay University

Finance

Media

Telecom

The Future of Financial Information Services

• The rise of consumer internet– 1995– 2007– 2013

• How did we get here?– Resulting technologies

• Difference between Consumer and Finance– Innovators Dilemma in Finance

• 10 Predictions for the Future of Finance

Outline

The Future of Financial Information Services

Financial Service Providers

Rise of consumer tech

Consumer Internet/Tech Landscape Pre 1995 Financial Technology Landscape Pre 1995

ServiceDistribution

Motorola Pageboy

Mainframe

1995

2007

Gaming-inspired system that would track and display the expertise of

users around the world.

Ideo Bloomberg Concept

Electronic notepad reused like a virtual Post-it

Bloomberg Wherever—allows users to take a small-scale Bloomberg terminal device beyond their desks.

Left to right info flow

UI similar to modern websites

2007

2013

Realtime

How did we get here?

SearchSocialCommunicationEcommerceGamingUser InterfaceInternet of things

??

?

?

Before 1995

Search

??

?

?

1995 Onwards

Search

Search

-Snail mail-/dev/null

Before 1995

Social

Comments

Social

Social

Big Data Ecosystem

Search/Social

WhatsApp Skype BBM

3G 4G

Communication

1990’s and pre

$$

$

$

ECommerce

Massively multiplayer online role-playing game (MMORPG) & Social Gaming

Gaming

Radian 6Consumer Products: Professional User Interfaces

User Interface

InternetInternet

HTML5CSS3Firefox/ChromeJavascriptJS frameworksBackboneEmberAngular

INTERNET OF THINGSSensorsEvent driven computingWebsockets vs. http Bluetooth and other NFCMaterial scienceElectromyography-sensorsAccelerometersSpeech recognitionPower consumption…

GAMINGAdvanced graphicsGame theory implementedAdvanced GPUsAdvanced GPU programming

UI:PROCESSUCDA/B testingLeanUser testing

ECOMMERCECloud Computing (EC2)Online paymentsMobile paymentsOnline payment gatewaysBitcoin…

COMMUNICATIONSmartphonesAndroidiOS 3G/4GSMSMMSiMessageErlangWebRTC… SOCIAL

NoSQL CassanrdaHbase/HadoopTwitter StormLocation based servicesNatural Language Processing…

SEARCHMapReduceGoogle BigtableGoogle BigQueryLAMP/Commodity scalingLuceneSOLRElastic SearchAjaxTwitter StormApache S24…

Technologies Born from Consumer

Technologies born from Consumer

USER INTERFACE

Pre 1995

AWS Android Mapreduce Bigtable Hadoop Hbase NodeJS Scala Cloud Computing Big Data D3.js Coffee Script/Backbone Data Visualization Elastic search Nginx Hudson GO R require.js less/sass/compass, HTML5…

Present

Consumer Internet/Tech Landscape

Difference between Consumer and Finance Applications

Consumer Experiences

FinancialExperiences

Highly competitive high volume market driven

evolution

Established traditionalbusiness model

ScalableFast

Reliable

SecureCompliant

OpenConnected

Rich

Innovators Dilemma

HTML5CSS3Firefox/ChromeJavascriptJS frameworksBackboneEmberAngular

INTERNET OF THINGSSensorsEvent driven computingWebsockets vs. http Bluetooth and other NFCMaterial scienceElectromyography-sensorsAccelerometersSpeech recognitionPower consumption…

GAMINGAdvanced graphicsGame theory implementedAdvanced GPUsAdvanced GPU programming

UI:PROCESSUCDA/B testingLeanUser testing

ECOMMERCECloud Computing (EC2)Online paymentsMobile paymentsOnline payment gatewaysBitcoin…

COMMUNICATIONSmartphonesAndroidiOS 3G/4GSMSMMSiMessageErlangWebRTC… SOCIAL

NoSQL CassanrdaHbase/HadoopTwitter StormLocation based servicesNatural Language Processing…

SEARCHMapReduceGoogle BigtableGoogle BigQueryLAMP/Commodity scalingLuceneSOLRElastic SearchAjaxTwitter StormApache S24…

Technologies Born from Consumer

Technologies born from Consumer

USER INTERFACE

Innovators Dilemma

AWS Android Mapreduce Bigtable Hadoop Hbase NodeJS Scala Cloud Computing Big Data D3.js Coffee Script/Backbone Data Visualization Elastic search Nginx Hudson GO R require.js less/sass/compass, HTML5…

The Future of Financial Information Services

10 Predictions

There will be a revolution in financial information visualization

Prediction 1

Visualization

-Financial Data is complex & large scale-Visualization of financial mostly same last 15 years-Current visualization relies on a variety of charts-Consumer BigData visualization has evolved rapidly

Products at the forefront Current Custom HTML5 Support/

Javascript API

Prediction 1

Prediction 1

Technologies in play

Emerging Technology: Present Future Technology >3 years:Gaming Engines

-Canvas -Raphael-Protovis

Prediction 1

Cloud services will be used much more for computation

Prediction 2

GPUs in Finance

• Significant advancement in GPUs for gaming physics engines• High speed computation• Can have 512 cores (<10 in avg. CPU)• Can have 10x bandwidth• 100 X fast calculation of typical derivative model

Pros: Ideal for well defined structured computationCons: Not very flexible, steep learning curve

Prediction 2

GPU Opportunities in Finance

• Derivatives Pricing• Speeding up risk analysis (can take days/weeks)• Trading strategy prospecting (back testing)• HFT (complex event processing)• Tick data (added value data feeds in real time)• Data visualization

High Performance Computing (HPC) to leverage GPU arrays available on Amazon

Prediction 2

Realtime solutions will be adapted from consumer world

Prediction 3

Realtime in Consumer World

• Ad serving user real-time • Capture and process model

Advertising Social media data processing• Multiple streaming sources• Capture and process model• Real-time ad response• Real-time engagementAnalytics

• Usage in realtime• Content usage tracking to

adapt strategies• Usage tracking to manage

load

Messaging and Communication• 2 way real-time comms

– Mobile vs - Text– Desktop -Images

-Video

Prediction 3

Realtime in finance

Use-cases– Exchange streaming pricing– Reference data access and

display– Liquidity analysis & risk– News– Communication– Alerts– Active compliance…social media

Technical solutions today:-MQ Series/Tibco-FPGA processors-Custom C++ solutions-Traditional RDBMS-Rules engines-Processing-Storage…stream processing

Capture Stream Processing

Resultstorage

Distribution

Price servers

Marketmovement

News

Rates changes

Realtime Data Processing Model

Ref: Real Time Data Processing - Technical Terrain by Prakash Khemani

Prediction 3

Capture

Stream Processing

Resultstorage

Distribution

Exchange price servers ticker plants

Aggregates and indices

News feeds

Rates and otheradjunct prices

Realtime modeling

Best-effort delivery guarantee

-Write-ahead-logging -At-least-once delivery guarantees

Persistent queue

-Price queue-Index queue-News queue

Millwheel-Large scale fault tolerant stream processing-Used for Google Zeitgeist

JMS

-Transactional guarantees-Strict ordering guarantees-Limited throughput

In-memory database

Sensors

Realtime Data Processing Model

Prediction 3

Capture

Twitter Storm: at-least once processing guarantee for every record

Resultstorage

Distribution

Exchange price servers ticker plants

Aggregates and indices

News feeds

Rates and otheradjunct prices

Persistent Queue Input

YARN Hadoop NextGen MapReduce

Compute node/cluster Management

-Pull data from persistent Q-Scheduling computation -Maintaining checkpoints

Zookeper

Trident: Exactly-once processing mode of storm. Allows you to seamlessly mix -high throughput + stateful stream processing-low latency distributed querying

Stream Processing

Streaming

Local state

-Does not persist output at every stage-Keeps track of each record's lineage -Can replay the data to recreate the records when needed-Fast-Cons: Unordered batch completions, low guarantees

PregelAll in the same system:-Event Capture Storage-Computation State-Result Storage

(Built on Bigtable)

Realtime modeling

Sensors

Prediction 3

Capture

Result Storage Distribution

Exchange price servers ticker plants

Aggregates and indices

News feeds

Rates and otheradjunct prices

Persistent Queue Input

Stream Processing

-Store batches into storage-Do the aggregations at read time

-Buffer up the updates to many keys-Do a sequential merge with historical data

Distributed, scalable Time Series Database (TSDB) written on top of HBase

Specializes in exporting key/value data from Hadoop

Realtime modeling

Sensors

Realtime Data Processing Model

Prediction 3

CaptureResult Storage Distribution

Exchange price servers ticker plants

Aggregates and indices

News feeds

Rates and otheradjunct prices

Persistent Queue Input

Stream Processing

Realtime modeling

Sensors

Prediction 3

Wave of improved general UX

Prediction 4

Mozilla labs design contest: Flickr @peterheads

Prediction 4

Prediction 4

Prediction 4

Prediction 4

Prediction 4

Prediction 4

Prediction 4

Prediction 4

3

4

2

1

1

1 5

Prediction 4

There will be a major change in the tiered architecture with HTML5

Prediction 5

HTML 5

Offline DatabaseCross BrowserMultimediaMobileOffline App supportGeo-locationImproved forms support

Prediction 5

Current

Windows/HTML

Front End

MiddleLayer

(App server with business and

transformation logic)

Pricing Engine

NewsService

Research

Historical Data

Events

Other…

Prediction 5

Future

HTML 5UI

Pricing Engine

NewsService

Research

Historical Data

Events

Other…

SOA (Service Oriented

Architecture)

BA

External 3rd party services

Prediction 5

Technologies in-play

• Websockets– Realtime bi-directional– Event programming : no http overhead– Javascript coming to the forefront on top of web

sockets• Server support for Websockets

Products

Prediction 5

In-desktop communication will be enhanced with Web RTC and similar technology

Prediction 6

Communication over financial products

• Skype/Softphones exploded on the web• PSTN/VoIP/Cellular phones still used in finance

environments • Communication endpoints will emerge on

desktops & mobile finance apps – Enabling realtime comm. including video

conferencing

Prediction 6

Technologies• Jabber / XMPP– Open syndication of messaging across networks

• Web RTC will play a big role• Enhanced on-desktop communication and FIX

integration• Rise of Erlang for messaging eg eJabberd

Communication over financial products

Prediction 6

The rise of Erlang

• Large scale concurrency• Soft real-time• Distributed • Hardware interaction• Software maintenance on-the-fly• Fault tolerance …. and many more

Prediction 6

Analyst research will take on a much richer format beyond PDF and will be published to

permissioned microsites

*Same for other frequently shared information eg earnings calls

Prediction 7

Analyst Research

• Current analyst research reports– Static PDF

Physical file sent through several intermediaries

Advanced entitlement model restricting access.

Distribution through financial research aggregators

Prediction 7

Relevant Technologies

• HTML5• CSS3• Web app stack: PHP/Python/Ruby• JS frameworks– Backbone– Ember– Angular......

Prediction 7

Financial training will be revolutionized to incorporate gaming and other aspects seen on

consumer web

Prediction 8

Financial Training

There is a vast amount of financial related trainingSeries 7Series 86/87 certifications CFA prepCompliance related training

• Education based apps and readers are much more widely available on mobile

• Financial training will see a rapid adoption of mobile and gaming based innovations

Prediction 8

Technologies

• Game theory• iOS/Android/Windows Phone• ePub adoption

Prediction 8

Android based OS will become a dominant force, starting with consumer banking

Prediction 9

Android Usage

More than 1 million new Android devices are activated worldwide. Daily.

1.5 billion downloads a month and growing.

The next 1 billion internet activations in remote areas will be on an Android device.

Prediction 9

Technology

• Android• vs. Chrome OS

Prediction 9

Direct sensor tracking for assets like Commodities & Energy

Prediction 10

Changes• From vessel to batch level sensors

– Deeper insight into supply chain

• Connected sensors tracing – Volume– Quality– Speed– Location

• Combined with following real-time data– Weather – Transportation – Government events

Access to high volume, low latency data for new level of accuracy

Prediction 10

Predictions Summary

1. Revolution in financial information visualization2. Much more GPU and GPU cloud computing3. Realtime solutions will be adapted from consumer world4. Wave of improved general UX on financial terminals5. Major change in the tiered architecture with HTML5 6. Communication will be enhanced with Web RTC & similar7. Analyst research go from static PDFs to dynamic microsites8. Financial training will incorporate social and gaming aspects9. Android based OS will dominate for financial info services10. Direct sensor tracking for assets like commodities & energy

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