Research Review Network Economies Innovators

Center for Future Banking

Network Economies

Research Review

November 10th, 2008

Confidential

1057 blogs 2007 French Presidential Election

Video links:

MS future vision on retail banking

ING Living Tomorrow - Retail Banking

2015 Banking Retrospective

Presentation by: Ray Garcia

http://www.youtube.com/watch?v=CNBJYH2jhko

http://www.youtube.com/watch?v=TAcMb2tfgGk

http://www.youtube.com/watch?v=1UnsVIGPDO8

2Proprietary and confidential

Ray Garcia [email protected]

Agenda

Innovators Alignment

Research Plan

Research Approach

Network Economies

2015 Outlook

Closing Remarks

2004 Oil Money contributions

to political campaigns



Innovators Alignment

Innovators alignment

Roles and Interaction

1924 Radial Org Char

showing concentration of power

Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook



The Research Innovators

Your Role

Create a vision and give voice to the future of banking

Develop and embody the grand challenges

Inform your business innovation through research

Foster an innovation culture

Charter research activities in collaboration with CFB

Find the opportunities to apply the research findings

Innovate associates, product, and markets

Think BIG and create entire new lines of business



Research Innovator Interaction

How we’ll interact

Speculate the innovation

Spot what remains to be known

Identify research that needs to be pursued

CFB finds who is working on the big problem already

Sponsor the research with CFB

Joint innovation and Research report to Executive Advisory Committee

Map of They Rule Corp Boards



The Innovators Challenge

Visioning that does not exist today and may be difficult to describe what will be tomorrow

Overcoming the fear of failure

Measuring risk and calculating when it too much or not enough

Treating ideas as a commodity, let them go, work on the ones that keep coming back

Making the vision real and executing through the challenges

Getting allies to see what your are imaging

Learning from the past and not repeating the same mistake twice

Knowing when to stop and not getting so committed to a failed path that you don’t change it

Finding the essence of the problem or the guiding principles at work

What is the framework or mental model being used, how can be to used to reframe the ideas

Getting a sense of the timing and pacing for the innovation

When it is good enough



Research Plan

Information Value chain

Behavioral Economies

Identity, Trust, Privacy, Security

Network Economies

Social Responsibility

Mapping Pigeon flight




Research Macro Themes Described

Macro Theme Description


Information flow is the signal versus and noise of information science. The value is an increase or decrease in signal. Information is the lowest atomic unit of measure for our research. The flows form interdependent chains or graph of relationships. The flows of value are not exclusive to money and include any convertible value.

Behavioral Economics

Includes any behaviors that happen before and after the decision of a consumer or producer. Behavior is observed, modeled, anticipated, projected, predicted as well as all the vagaries of the human condition. The unit of measure is at human scale and includes many uncontrolled factors.

Identity, Trust Privacy, Security

Identity includes concepts of privacy or public disclosure. Trust implies the concepts of gradations of security or no security if full trust is granted. Both included measures of credibility and honesty or value systems that are human. The concepts span system processes and human interaction.

NetworkEconomies

Networks are the systems that connect and the people acting in social interactions. Information flows, social behavior, identity and trust are aggregated into economic interactions within a network.


Includes individual actions representing corporations as well their household and raises questions of ethics. This aggregates the network economies into defined groups that care for direct and indirect impact and consequences of decisions.

* joined by a team of colleagues, researchers, students, support staff, bank line of business, committee



CFB Research Plan

Macro Trend

Questions Asked

Research Topics


How do we empower people to use information?

How will the next generation of information clouds emerge?

How do we de-mystify financial management?

Living Lab / Flagship store

Retail Banking Analytics

Sensing Stores / Speechome Video

Ambient Intelligence / Surface Computing/ Siftables /Word play

Affective Computing

Information flow is the signal versus and noise of information science. The value is an increase or decrease in signal. Information is the lowest atomic unit of measure for our research. The flows form interdependent chains or graph of relationships. The flows of value are not exclusive to money and include any convertible value.



CFB Research Plan

Macro Trend

Questions Asked

Research Topics


How do customers respond to “life events?”

How we predict what customers want?

How do we enable people to make rational decisions?


Prediction Markets

Affective-Cognitive Predicting Customer Purchase Decisions

Includes any behaviors that happen before and after the decision of a consumer or producer. Behavioral is observed, modeled, anticipated, projected, predicted as well as all the vagaries of the human condition. The unit of measure is at human scale and includes many uncontrolled factors.



CFB Research Plan

Macro Trend

Questions Asked

Research Topics

Identity, Trust, Privacy, Security

What will be the new deal for data and privacy?

What are the new platforms to manage risk?

What are the new economic models for trust and security?

Living Labs / New deal for Data

Identity and Identification Models

Personalized Customer Service

Trusted Investment Advisor

Face Reader for affective responsive computing

Identity includes concepts of privacy or public disclosure or fabricated personas which are both public and private. Trust implies the concepts of gradations of security or no security if full trust is granted. Both included measures of credibility and honesty or value systems that are human. The concepts span system processes and human interaction.



CFB Research Plan

Macro Trend

Questions Asked

Research Topics

Network Economies

How will hyper-connected mobility and locality change banking?

How do we enable frictionless interactions to customers?

How will networks change the way we live//transact?

Mobile Commerce / Physical interaction / Living Lab

Future Consumption / Living Lab

Social Network Risk models

ATM & Mobile Phone interactions

Understanding Associates interaction – peers /managers/customers

Networks are the systems that connect and the people acting in social interactions. Information flows, social behavior, identity and trust are aggregated into economic interactions within a network.

Webiste map



CFB Research Plan

Macro Trend

Questions Asked

Research Topics


How can we enable people to live better?

How do we transform the image of banking?

How do we foster consumer financial health?

Volunteerism and activism

Civic Media and Voice of the Community

Financial Life Time household Literacy and decision making

Account Ability and sensible consumerism

Next Billion in our Neighborhood / Living Labs

Includes individual actions representing corporations as well their household and raises questions of ethics. This aggregates the network economies into defined groups that care for direct and indirect impact and consequences of decisions.



Research Theory and Impact

Macro Theme Consumer Impact * Theory Basis Research Unit


Usability

Sensing Store

Communications

Signal/Noise

Bits/Bytes

Numbers/Time


Consumer

Buying Decision

Individual

Choice Theory

Psychology

Mind/Emotion

Identity, Trust Privacy, Security

Consumer

Confidence

Risk Containment

Chaos Theory

Safe

Systems

NetworkEconomies

Connected

Consumption

Complexity/Game/

Graph Theory

Societal

Knowledge


Consumer

LiteracyPhilosophy

Values

Ethics/Law

*sampling of research projects summarized



Research Approach

What is it?

How does it work?

Converting research to commerce.

Zaha Hadid Architect 3d Nurbs




“if you always do what you always did, you always get what you always got”

- Einstein

What is observed

learn

What they say Market OpeningWhat they offer What we offer

Customer needs (discovered)

Proprietary VOC

and market research

Opportunities

identified (size, growth, profitability)

Comprehensive

review, financials and market share, etc.

Leader and innovator

in banking product and distribution

Customer needs (observed)

Customer needs (told)

Market opportunities

Competitor driven

Product driven

New worldviewProduct centric Customer centric

Banking Design CFB

Consumer Banking TransformationTraditional Model

CFB Approach: ‘Real-world’ connection

Academic

Research

Methods

Consumer insightMarket research

Ethnography

Corporate and University

collaboration on research



CFB Approach: Future Created

What we can observe / learn

(discovered)Customer needs

Customer Banking Design

Consumer Banking Transformation

Available thru cutting-edge

research

What we can observe / learn

Customer needs (discovered)

Customer needs (observed)

New worldviewCustomer centric

Customer Banking Design


Consumer Banking Transformation

Banking TransformationNew Markets Created

Blue Ocean Strategy

Value the customer could not imagine.

This is the voice of the future.

Market value innovations developed using strategic investments in emerging lines of

business and ventures.

Requires service innovation culture, informed by research and creative open visionary

leadership.

Sustained Competition



CFB Approach: Design Research and Business Model Development

InformationValue chain

Network Economies

Customer Needs Observed (IDEO & Design Research)

BehavioralEconomics

Identity/TrustPrivacy/Security


TANGIBLE COMMON SENSE CLARITY•help people grasp the bigger financial picture•Go beyond a menu to a recipe; “I need expert financial guidance”•Make financial information more understandable and tangible instead of using abstract concepts.

WISDOM OF CROWDS•Enable people to use collective knowledge of fellow customers•Foster reassurance by connecting like-minded customers

CULTURE OF ACHIEVING•Create moments of pride and mementos of achievement. “Account alerts are embarrassing – they make me feel poor” •Set an atmosphere of encouragement

MY PACE, MY ROUTINE•Infer preferences: “Amazon knows me better than my bank” •Know and accommodate people’s schedules and daily patterns.

TransformativeBusiness Model

-------------------------Outside-In

Customer Analysis / Research

Inside-Out Competitive Analysis

Compelling Offer

Finance ModelDISTRUST•Trust is difficult to attain, fragile, and can be easily eroded. When trust is broken, we are often the last to know.



Existing Innovation Ecosystem informed by Macro Theme Research

Commercialization:New Product Introduction (NPI) & Product Enhancement (PMI)

Product Management

Ide

as

TG0

Define Measure Analyze Improve Control

Strategic Planning

Idea Generation

Stabilized Stabilized Products / Products / ServicesServices

Ide

as

Ide

as

Ide

as

Process Management & Initiative Governance

Approved Approved ConceptsConcepts

Strategic Themes / Strategic Themes / OpportunitiesOpportunities

Intellectual Property

Inte

llec

tua

l Pro

pe

rty

Review IPlandscape

Evaluate ideasfor IP value

Patent corefeatures

Limit exposurefrom existing

external patents

Patent additional key features

Review/revisePatent app

Monitor forIP opportunities

Concept Development

Idea Management

RapidPrototyping

CFB Macro Themes ResearchMedia Lab concept Prototypes

CBT Market Research

New LOB Formation



CFB Approach: Understanding Research

“The Media Lab may have lots of useful artifacts or techniques

that may be re-purposed in completely different ways than

they would expected… ”

“Build first…ask questions later”“Break what is fixed””

“action oriented inquiry”

“Academia can be very useful when applied to Bank data and

may help uncover new understanding that would

otherwise not be available to the Bank”

What is foundational Research?

A process of continuous inquiry. An examination of a subject from many points of view.

Pursuit of what works, what does not work and why

Uncovering a theoretical proof or essential truth.

The construction of knowledge for the public good.

A systematic experimentation of observable phenomenon.

Creating Innovations!

Information gatheringScenario analysisProduct developmentMarketing research Collecting VOCBusiness development



CFB Approach: Doing collaborative Research

“Triple Helix; Industry, Academia, Government”

1. Identify and create tectonic shifts in the global socio-economic landscape

a. Experimental Research on what may impact the way people live, work and thrive.

b. Long-term partnership with collaboration between academia, industry and the civic bodies

is the only way to identify potential mass adoption of new standards, behaviors and

business frameworks

2. Research to Predict, build, and test future drivers of business models

a. Agreed on a rapid extreme experimentation approach in live environments

b. Macro Themes generate emerging concepts to research real scenarios

c. Inform existing product innovation by pipelining the experimental research findings,

techniques, and artifacts into the enterprise to create a sense of ownership and urgency

to formulate or seize these emerging business models



CFB Research Outcomes Categories

“All outcomes need to be converted to products before they are useful”

Artifacts

Research results with tangible embodiments that demonstrate what is possible

Early indicators of physical interfaces afforded interaction designers

Example: Patties Maes, Siftables devices

Techniques and methods

The invention of new techniques for analysis of experimental data.

Example: Deb Roy, Speechome fish lens and video processing

Observations

Speculative insights based on observations that inform hypothesis for experimentation

Example: Dan Ariely Behavioral Economies patterns

Understandings

Theories that challenge the prevailing beliefs. Intangible experimental demonstration

Example: Sandy Pentland, Sociometer discovery of Honest Signals

Philosophy

Radical thinking that breakthrough common practice

Example: Stallwart, Free Software Foundation, Open Source Software



Converting Research into Business

“Finding and creating new billion dollar markets”

Company creates the innovations

Leadership provides the Vision for the Future

Prioritizes innovation as part of its Hoisin planning

Associates engaged in innovation are trained to think creatively by working with CFB

Creates service concepts from marketing research and ethnographic studies

Generated insights from its own data repositories with superior quants and tools

Product Innovation teams collaborate across the company

Product Teams create new IP and acquires IP to secure it position

Engage its strategic partners to help create breakthrough products and services

Uses the investment fund to fuel new market innovations



CFB Informing Business Innovation through Research

“Inform innovation through world class research engagements”

CFB Through engagement with Academia

Engages with researcher to influence their focus areas

Spots interesting research outcomes

Keeps a focus on the future horizon

Informs the product innovation teams

Provides creative context and inspiration to market innovations

Assist leadership in realizing long term vision for Banking futures

Trains the top talent in creating the future through Executive in Residence rotation

May directly conduct research where gaps in conceptual knowledge are present



Research Conceptual Structure

Value

Creation

TACTICS TODAYNow – 12 months

STRATEGIC HORIZON1 – 3 years

RESEARCH FUTURES+3 to 10 years

VALUE CREATION

SERVICE SCIENCE

RESEARCH

Data

Human Interaction

Economic Models

Information Behavior

System Dynamic Knowledge

NetworkRelationships

Financial Ecology

TECTONIC SHIFT



Network Economiesdefinition: any complex system where value is stored and exchanged

Why it matters!

Grand Challenges

What is it?

How does it work?

Impact

CFB Examples

Ethnography study map

Visualization link: World Growth in PC and Cell Phone Adoption




Network Economies – Why it Matters!

Conceptual inclusions into Network Economies All matching and routing systems

All computing and communications systems

Human and Biological systems

The connected planet Estimated 1 billion bank accounts worldwide, 2 Billion Cell phones and growing rapidly

Network economies are responsible for entire country and regions economic development

Network economies are integral to globalization

Financial/Banking systems are wholly dependent on network economies

Range of Network Economies dependencies Trade systems of various types

Reputation systems

Supply and Demand chain dynamics

Electric Power Grids

Modern Food and Health delivery are not possible without Network Economies

Transportation systems use network economies



Grand Business Challenges

Market Discovery

What techniques can be used to uncover hidden insights and unmet needs from the voice of the customer as captured in a social network application?

Can we identify and unlock the commercial potential of social capital inherent in communities?

How do we evaluate ways of fostering user generated content and a free exchange of expertise within the community?

Network Economic Models

How can a social networks extend beyond a communication vehicle to have more relevancy in managing a business effectively?

Can labor be shared, cost spread, profit pooled?

Can a network be used to manage business risk?

Could it be used as a source of capital?

Can the network aggregate its purchasing power?

What is the balance between competition and cooperation within a network?Tsunami



Grand Research Questions

Networks converging physical and virtual spaces

How do networks emerge and scale? How are physical and virtual different?

What is the inherent value system and constraints under which they form?

How is knowledge shared and problems solved within social networks.

Do SmartMobs behave predictably? Can they be controlled?

How would augmented reality retail emerge with social networks?

Network Economic Models

What are the micro-economic forces at play?

How do new currencies impact group decisions?

New currencies could be coupons, loyalty point systems, barter systems, time trading systems, money within games, micro/nano payments, one time use codes, media capture and exchanges, peer to peer value exchanges.

How do networks behave in physical spaces when using mobile Location based services and can form spontaneous connections?

Strange Attractor



Network Economies – What is it?

What are Network Economies Value exchanges based on relationships that transcend a single transaction Frictionless matching of producers and consumers, freescale growth Communities of Practice with convertible social capital Rebalancing of power asymmetries and disequilibrium

Enablers of Network Economies Internet and ICT Mobility, cell phones, laptops Software that affords self organizing activities

US Industry Examples using Social Networking Google, EBay, Amazon, Paypal, Skype, Joost Intuit Small Business Community Facebook - Visa Business Network Facebook - Fiserv MyMoney program Prosper Peer to Peer Lending



Network Economies – How does it work? a research history

6 (5.5 – 6.6) Degrees of separation

In 1960’s S. Milgram (psychologist) demonstrates 6 degrees using US postal mail

In 1973 M. Granovetter (sociologist) theory “Strength of Weak Ties” spread of info in networks

In 1994 R. Reynolds paper on Cultural Algorithms using computational models

Online 3 degrees of separation is more likely

A. Barabasi (physics) demonstrates preferential attachment model, nodes with lots of links have higher probability of acquiring more links.

Yahoo research discovers growth in members and connections are needed for healthy networks to thrive. If either stall the network dies.

R. Dunbar (anthropologist) argues a maximum of 150 social relationships can be maintained which is the historical size of farming villages.

The world is highly clustered geographically and socially, enabling short paths traversals within networks and across groups

Social Contagion, diffusion of innovation, people imitate each other 0 1 2 effect where the probability of imitation is great once 2 friends have done something

Jared Diamond posits a theory for Societal Collapse inferring social networking theory



Network Economies – How does it work? Current research finding Nov. ‘08

mathematical model “hidden metric space”

may explain the “small-world phenomenon”

relates to man-made and natural networks

human language to gene regulation

neural networks connecting neurons to organs and muscles within our bodies.

Natural world routing only uses local knowledge and not global knowledge of the network which is how communications routing works today.

Natural networks transmit information very efficiently without any single node having knowledge of the structure of the entire network

Many complex networks share similar shapes that maximize their communications

Implications range from cancer research on gene therapy to more efficient routing on the internet.

How the hidden metric space guides communication. If node A wants to reach node F, it checks the hidden distances between F and its two neighbors B and C. Distance CF (green dashed line) is smaller than BF (red dashed line), therefore A forwards information to C. Node C then performs similar calculations and selects its neighbor D as the next hop on the path to F. Node D is directly connected to F. The result is path ACDF shown by green edges in the observable topology.

Source: CAIDA, UC San Diego Supercomputer Center



Network Economies – What are the numbers?

Simple Math explains the net effect Potential number of interactions within a Social Network may be expressed as

n ( n -1 ) / 2 where n is the number of people in the network

Given a starting social network of 100 people with 100% growth rate to 200 people

The number of potential connections grows from 4,950 to 19,900 or 302%

d-2 probability of being friends decreases exponentially as the distance/dissimilarity increases

What this produces? Facebook example: Post money Valuation of 15 Billion as of June 08

130+ Million unique visitors in June 08, comscore avg. internet Ads spend $132/user

Technical statistics

10 Million request/second (500,000 to database tier)

1+ Terabyte/day of data volume and growing

Visa & Fiserv on Facebook to access growing installed user base.

Thousands of custom applications with a rate of innovation accelerating



Network Economies – It is not New, and has a Global Impact

Globalization

Thriving interdependent Social Networks

Silicon Value/Alley, Boston, Austin

Hsinchu-Taipei, Bangalore, Tel Aviv, Singapore

Local Social Networks

Cambridge, Helsinki, Sophia Antipolis, Stockholm, Munich

Silicon Valley Innovation example

Three large network facilitate new entrepreneurs

Firms, R&D Labs, Universities

VC’s, Investment Bankers, Law Firms

Suppliers and Customers

They all rely on reputation and trust to make decisions

They are highly purposeful and dynamic with adhoc communities of practice

The networks are highly diverse and global



Network Economies – Consequences of not taking it seriously

Global Salafi Jihad

Most complex systems are not random and present similar topologies

Properties like:

small-world = high clustering, low path length

scale free properties = self-organizing, preferential attachment.

Robust against random failure but vulnerable to targeted attacks.

Same pattern for:Meth WorldGang NetworksDark Web



Network Economies


Media Lab Examples

Related projects

China Globalization Map




Network Economies – CFB MIT projects examples

Catching up with today

Situated Mobile Commerce a Living Lab

Future Consumption Network

Call Center and the Socio-meter

Corp Social Media

Related Projects

Future Proof the Company

Information Economics

Silicon Valley Network



Network Economies – Future Consumption Network / Living Labs

Inquiry – What is the value of Hyper-Connected Social Mobile Networking at the Convergence of Virtual and Physical Spaces?

Inputs – Mobile and Telecom Infrastructure, Social Networking Capabilities

Outputs – Idea Market connecting consumers, merchants, product manufactures, and financial services, as well as Small Business Mobile Living Lab

Academic Team

Faculty - Sandy Pentland, Andy Lippman, David Reid

Students - Kwan Lee, Dawei Shen, Aithne Pao, Anmol Madan, Taemie Kim,



Network Economies – Future Consumption Network

Connected Consumption Mobile-informed consumer through open

contribution

Reverse auction environment

Collaborative shopping

Rewarded for participation

Bank products offered as participation incentive

Sensing consumer short-term/long-term interests

Future Consumption Network Intelligent, on-demand network that brings

together loosely integrated entities in an efficient and highly integrated manner

Open transaction network

Socially responsible network that rewards savings & investment

Dis-intermediating payment network

CFB Exec: Hans Schumacher



Network Economies – Future Consumption Network

Budget Envelope Card

Restrict spending behavior while being rewarded/incented for staying within predefined budget by category

Budget surplus dynamically invested

Real-time expenditure tracking

Compete with peer groups

Concrete Budgeting

Actively manage short to long-term financial goals and evaluate purchase decisions on-demand to attain a “concrete” financial future

Comparisons to peer group

CFB Exec: Hans Schumacher



Network Economies – Call Center Social Analysis

Inquiry – Examination of associate interactions with peers, managers and customers, and activity analysis for predicting group behavior by including all available communications traces.

Inputs – Frontline call center interaction, work flows, email and phone data, including socio-meter instrumentation.

Outputs - group behavior analytics, models for successful interactions across multiple channels, define behavioral characteristics that are critical to driving success.

Academic Team

Faculty - Sandy Pentland

Students - Ben Waber, Coco Krumme, Anmol Madan, Iolanthe Chronis




Predicting Associate Interactions

Predict the outcome of an associate/customer interaction after seconds of listening?

Discover patterns of activity that usually go unobserved in organizations/call centers?

Track and evaluate the unconscious human behavior with the collaborative and social side?

Honest Signals hidden in Human communications

People have 2 distinct “channels” of communication –

verbal rational channel, which information flows linguistically

nonlinguistic channel, often ignored, but carries as much information.

Human behavior can predicted accurately by capturing thin slices of what people do.

We need instrumentation since people can’t observe others objectively.

Cannot manage what is not measured.




Experimental Proposal

Test Social/Human Behavior in Contact Center

Outfit 80 agents (4 teams), their managers, and Unit managers with wearable sensors.

Track and record conversational and physical interactions between associates, team and unit managers.

Capture email, instant message and telephone records for the duration to contribute to the analysis.

Duration to last 30 days.

Impact

.004% shrinkage

(80 agents @ 15 minutes)

Hawthorne Effect

CFB Exec: David Price



Network Economies – Corp Social Media

CFB will utilize an external blog to … Promote dialogue with innovators, competitors, MIT & Academia, BAC Associates

Communicate activities of the Center, disinformation to competitors;

Position Bank of America as a progressive innovative leader;

Learn in a lower risk environment strategies to utilize Social Media to engage key constituents.

Experimental Analytics Implemented Coremetrics, I2A tags, and collect Cluster Map data.

iCrossing has included a reporting tool that CFB Team can access on-demand

Post Launch SLA for detailed reporting work with Supply Chain

iCrossing will provide a detailed 6 & 12 month summary post-launch summary

Team CFB Exec’s, Legal, Social Media, PR, Marketing Communications

CFB Team with Jeff Carter



Network Economies – Corp Social Media



Network Economies – Related Projects

Initiated by innovators in collaboration with CFB

Oct 21st Design Charette, 70 people, Faculty, Students, BAC, City of Boston, guest speakers

Event stimulated research possibilities not previously considered

Video Documentaries available for Leadership Learning.

Highlights of Projects Initiated:

Living Labs project initiated with Mobile Initiative, Sandy Pentland

City of Boston engaged with CFB, MIT, BAC in Living Labs project

SBOC Data analysis – discovery of internal competencies in data and text analysis prior to engaging MIT students.

SBOC used in the EpiCenter project – connecting the virtual with the physical for richer engagement with customers.

Peer to Peer Lending Analysis – pattern recognition class doing analysis, possible academic paper with significant finding pending. Ray Garcia with Dawei Shen and Hyungil Ahn

Information as a Product

Community Change Card, Jon Ramer, City of Boston

Merry Miser project Charlie DeTar



Network Economies

Future Proofing the Company with

Information Economics of Network Knowledge




Team and Inquiry – Information Economics of Network Knowledge

Bank Strategic Champions – Laurie Readhead and Lance Drummond

Business Tactical Leaders – Margaret Weichert, Ross Feldman, Beverly Ladley, Indur Koul

Innovators Committee – CFB - Hans Schumacher, Todd Inskeep; BAC - Marc Keller, Matt Calman

Quant Committee – David Joffe and David Joa

Audience – Quant doing Informatics and business leaders needing to understand information economics, network and emergence theory.

Business Inquiry –

How might data and information captured within Bank systems be converted to knowledge that informs a Financial Ecology and Network Relationships such that they can be leveraged as residual products.

How would the Economics of Information assess value or reveal insights to be discovered to inform service innovations, generate revenue, reduce risk, or improve operations?

How does value emerge from a network and how would Quants use Informatics to continuously discover emerging opportunities and threats given the severe challenges of data quality management.

Research Inquiry –

How do personal, social, commercial, knowledge networks emerge?

What is the inherent value system and constraints under which networks form?

How does using information economics to show how fairness contributes to efficiency and innovation?

How is knowledge elicited, assessed, shared and problems solved within networks?

What are the micro-economic forces within information intensive service businesses?

What experimental methods are used to model, simulate, predict, inform, improve, knowledge products?

What are the learning models, cognitive models, and affective models that influence knowledge economies?



Research Design - Information Economics of Network Knowledge

Theoretical Basis – Information Economics, Social Science, Computation, Information Science, Ontology

Business Basis – Financial Ecology, Human Dynamics, Knowledge Management, Social Media

Methods – Qualitative Research methods, quantitative analysis, ethnographies

Techniques - data processing, statistical analysis, pattern recognition, text processing, machine learning

Business Inputs – Bank transaction data, data from information network experimentation, marketing research databases, external market data sources, financial data feeds, expert annotation

Research Inputs – MIT prototypes in; common sense knowledge, social media, cognitive/affective markets, knowledge markets

Experimental Platform – communications market borrowing from several MIT projects and creating a system for on-going long term research.

Informatics Toolkit – an assembly of open source, or low cost, tools used in the analysis and visualizations of data.

Key Outputs –

Valuation of latent Network Knowledge factoring system dynamics, content, membership, relations between nodes.

Knowledge elicitation, discovery, and dissemination, modeling, simulation and prediction of human systems including cultural algorithms which inform market dynamics.

A formulation of the research discipline in Service Science merging techniques from Qualitative and Quantitative research borrowing from various practices. This Service Science would determine how to convert research findings into innovative services that can be formulated, tested, disseminated within a large scale global company.

The Network Knowledge and information economics would include a synergistic co-generated service innovation between consumers and producers. This may include a communications marketplace that is both internal and external and reconciles the need for knowledge elicitation and dissemination.

Quant tools, techniques, and methods for applied information economics against bank data.

Academic Team (proposed)

Research Scientist – Marshall Van Alstyne (Sloan School), Kelly Hewett (BAC Market Researcher)

Phd Candidates – Dawei Shen, Hyungil Ahn, Polychronis Ypodimatopoulos, Ankur Mani



Related Research to Information Economics of Network Knowledge

Economic Choice Theory and Group Decision Making

Problem Statement – How do people learn to make important economic decisions that impact their personal finances and/or company value from the social engagements and information sources they have available? What are the cultural forces at work? What methods could be used to experiment, model, simulate, predict, inform, improve, group decision making within tribes, co-workers, and communities of practice? How does economic literacy impact other important decisions such as health, home, children, work, and consumer behavior? How does economic literacy change throughout ones life and how is it inter-generational? How is economic literacy taught and learned. What are the educational psychological models and cognitive models that help inform personal and group decisions and how do social values systems influence the choices and expectations.

Scaling the Service Innovation Process to create breakthrough new products (Cooperative Collective Intelligence Elicitation and Dissemination)

Problem Statement – Service companies lack the experimental research activities that are prevalent in product companies and therefore do not have a science of service to create and build a body of knowledge. The research methods and process for converting research findings into innovative services requires a discipline to be formulated, tested, and disseminated to be effective within a large scale global company. Can these service innovations be co-generated between the consumer and producer such that they evolve into a synergistic relationship? Using Social Media to elicit knowledge and applying methods for evolving the knowledge into innovations while opening communications to a free exchange of ideas between consumer and producers is a challenge for industries where confidentiality and proprietary information is consider a risk to the business and therefore all communications is controlled. How to balance the economic benefits of a free communications with the desire for control requires research in the economics of information to devise techniques to resolve these conflicting goals.



Candidate Research Collaboration

Academia

Sloan School Center for Digital Business

CSAIL

Auto-ID Lab

Corporate

IBM Center for Social Software

Rueters and Bloomberg

Appforge

Selectminds

Government

Fed Reserve

City of Boston



IP Generation

Technology disclosure with MIT

Personal Augmented Reality in a Retail Environment

Inventors: Ray Garcia and Stephen Miles

An intelligent personalized agent running on a mobile wireless connected device that monitors and advises a user in recommendation-making process in a retail setting through both private and public information services, whereby the identification of the mobile device and rfid transponder impacts both the personal display and the public display

Conceptual Ideas under development

Multi-function card associate with a mobile device that acts as a dual factor authentication using a transparent card, embedded image that is reveal through matching with the display on the phone. The card is anonymous with no markers. The information on the card includes dual magstripes, barcode, optical storage, contactless rfid with a coil.

Communications market which is a hyper network of knowledge and affective associations of constructed information amongst a large group of participants. The knowledge is hyper connect to the people, context of situation and circumstance, and has a financial ecology that expands in a free market with minimal regulatory rules. Small world scale free networks of efficient information economies are allowed to emerge.



Pattern Recognition Analysis of Peer to Peer Lending data from Prosper

From Sergio, Rahul, and Aithne, they are exploring the effects of social capital:

1. Social profile Friend: number of 1st-degree friends, number of 2nd-degree friends Endorsement: Endorsement number Group: Group leader reward rate, Group Rating, Group Size

2. Social Interaction - Bids from friends and group members

3. Classifiers were built to determine whether a list could turn into a loan.

4. Social factors are not determinant, but they do increase the chance of getting a loan when all other financial features are similar. This is demonstrated clearly by using clustering.

5. Users do not have time to maintain many social profiles, it's beneficial to use existing social networks as a foundation.

From Charlie, Matt, Ernesto, and Coco:

1. A Bayes belief network and a decision tree are formulated for classification. The unique benefit of Bayes network and decision tree is that it graphically presents some good practice for users if they try to increase their odds to get a loan.

2. Textual information, such as words used in endorsement, description, etc. is analyzed and proved to be very influential.

3. A risk assessment model built on Hidden Markov Model is formulated, and works very well. It can effectively predict a loan carrier's financial health, and predict potential delinquency.

4. Coco starts some interesting games with the image posted by users.



Sloan Research to leverage in experimental design

Research Scientist Marshall Van Alstyne

Correlation of speed of Information Diffussion via social networks with productivity

Internal knowledge markets - Information economics applied to quantifying the effects of knowledge management using price theory, information asymmetry, and network theory. The goal is to discover information behaviors that predict success.

Anti-spam & Malware Research - A formal proof of information economics impact on eliminating spam without using a filter.

Open Platforms & innovation

The social efficiency of fairness



MIT Concepts prototypes to monitor

PolyQuest: It’s your data, your connections

Team: Polychronis K

Problem Description: A next generation social network that is distributed and provides users complete ownership over their data and social connections. Contrary to centralized social networking systems like facebook, each user maintains their personal information and their list of friends on their own private web space. The list of their friends are pointers to other web spaces, while public key infrastructure is used to provide different levels of access to different friends, while providing minimum or no information to strangers.

Experience Sharing Market for Forecasting Marketplace Success

Team: Hyungil Ahn

Problem Description: We develop a novel market game that harnesses people's collective perceptions and experience sharing to forecast the success or failure of new items (products / services / UI designs, etc). Companies can register their new items on this market (as a test bed) to ask people's collective opinion. In each trial session, a participant makes his or her own best prediction on other people's overall opinion about the new items to get incentives (e.g., real opportunities to experience the items) and have fun in gambling-like games. As a participants guess (or portfolio) approaches the collective guess of all participants, he or she has a greater chance of winning an incentive. Participants improve the accuracy of their next prediction by sharing their experiences. As participants have more trial sessions, their collective prediction converges into one common opinion (forecasting the success or failure of new items).

Funk 2

Team: Bo Morgan

Problem Description: Funk2 is a novel process description language that keeps track of everything that it does. Remembering these causal execution traces allows parallel threads to reflect, recognize, and react to the history and status of other threads. Novel forms of complex, adaptive, nonlinear control algorithms can be written in the Funk2 programming language. Currently, Funk2 is implemented to take advantage of distributed grid processors consisting of a heterogeneous network of computers, so that hundreds of thousands of parallel threads can be run concurrently, each using many gigabytes of memory. Funk2 is inspired by Marvin Minsky's Critic-Selector theory of human cognitive reflection, and is the foundation for the Neural Models of Mind project.



MIT Projects to License for use in future research

Selectricity

Team: Chris Csikszentmihalyi, Alyssa Wright, Benjamin Mako Hill

Problem Description: Selectricity is a web-based voting system that supports anonymous and voter-verifiable balloting, and includes an election-methods library that implements a variety of election techniques, includeing several preferential systems. Unlike most voting projects, Selectricity does not attempt to address the issues raised in mainstream political elections. Instead, it provides a simple set of tools that small groups and organizations can use to incorporate computationally complex decision-making into new areas, and for purposes where they ordinarily would find such decision-making into new areas, and for purposes where they ordinarily would find such decision-making prohibitively complex. By supporting a variety of election methods, it provides a way for users to explore and compare the effects of different voting systems and, ultimately, come to better decisions.

Common Sense Reasoning

Team: Henry Leiberman, Catherine Havasi, Robert Spear, Dustin Smith, Jayant Krishnamurthy

Collecting Common Sense – the open mind common sense project, acquiring knowledge from untrained people through the use of on-line interfaces and games.

Common Sense Recommendations – that are more user friendly than collaborative filtering systems. Uses tools to build intelligent recommendation agents and effective product exploration tools

Not-So-Common Sense – infusing data sets with common sense

Perspective Space – discovering distinct communities of people with jargon and belief structures from simple ratings

Analogy Space

Common Sense Investing

Common consensus: a game for collecting commonsense goals

ConceptNet

Divisi: Reasoning over Semantic Relationships

E-Commerce When Things Go Wrong



MIT Project techniques to re-build in future research for new inquiry

Behavior Capture from Thousands of People On-line

Team: Jeff Orkin, Deb Roy

Restaurant game simulation of patron to host interaction to capture dialogs and sequences of common actions. The analysis is statistical and produces dialog that mimics frequent occurrences of phrases.

New Media Medicine

Team: Frank Moss, John More

Collaborhythm – collaborative decision making between doctor and patient

Collective Discovery – a massive collection of “everyday experiments”

HealthMap – real-time disease outbreak tracking and visualization system

I’m Listening – pre-visit interviews to help categorize patient symptoms for efficient diagnosis.



Tentative Research Milestone Plan

Network Economies Defined Dec-08

Grant Draft based on initial research design Jan-09

Grant submittal and review Feb-09

Stakeholder commitment, Biz Relevancy, Funding, BAC staffing secured Mar-09

Research PI commitment and plan Apr-09

Executive Course in Information Economics to support research created Jun-09

Experimental Instrument created Jul-09

Initial Research execution and Analysis Dec-09

Research Paper Submittal to peer review conference Jan-10

Trial adoption of tools, methods, techniques, by quants for internal use Feb-10

Quant discovery of major revenue impact in network effect Apr-10

Journal Article submittal Jun-10



Network EconomiesAnalyst Future Outlook

2015 Context Aware Computing source: Gartner ITExpo 2008, William Clark

Analogous to MIT Sandy Pentland vision of an

Aware Society of Tribes in a Living Lab

Champion Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook



Situation and Context Aware Tribes

What is Context Aware Computing

Emerging context-enriched services will use location, presence, social attributes, and other environmental information to anticipate an end-user's immediate needs, offering more-sophisticated, situation-aware and usable functions.

By 2012 estimates:

More than 7.3 billion networked devices worldwide

298 million subscribers of location-based services

>75% of new search installations will include social search element

• $150 billion of $1.8 trillion global telecom spending will shift from services to applications

• Global market potential that context-aware computing can impact: $215 billion

MVE algorithm plot on citywide activitySource: Sense Networks

source: Gartner ITExpo 2008, William Clark



Context-Aware Society in 2015

SocializationPersonal Services

Personal Commerce

Context Agents

Context Brokers

Fine-grained, anticipatory search

Context-Enriched Services

Identity

Knowledge Collaboration

Community

Environment

Process

me

Sensors

Universalgeo-fencing, hyper-optimized processes

A way to manage identity, reputation, and privacy

Virtualized worlds, avatars, persona-bots

Consistency across channels

Auto-tagging,

anticipatory

search




Socialization

Challenges in Context-Aware Society

PersonalServices

Personal Commerce

Context

Brokers

Fine-grained, anticipatory search

Context-Enriched Services

Identity

Knowledge Collaboration

Community

Environment

Process

me

Sensors

Universalgeo-fencing, hyper-optimized processes

A way to manage identity, reputation, and privacy

Virtualized worlds, avatars, persona-bots

Consistency across channels

Auto-tagging,

anticipatory search

Shared Shared TrustTrust InformationInformation

FederationFederation

Context Context SwitchingSwitching

Cross- Cross- Endpoint Endpoint

ExperienceExperience

Cross- Cross- Personna Personna

ExperienceExperience

Cross-Session Cross-Session ExperienceExperience

Agent Agent ProvisioningProvisioning

Sensor Sensor OverloadOverload

Real-TimeReal-TimeContext DeliveryContext Delivery

Cross- Cross- Application Application ExperienceExperience

Context Agents




Real-World, 2009: Context-Enriched Services in Mobile and E-Commerce

IdentityCommunity

Environment

Process

User-Defined Rules

System-Defined Rules

Reference

History

Network Capability

Endpoint Capability

Location

Presence

Groups

Tagging

Links

Bookmarks

CalendarPIM

Role

Security

Privacy

Reputation Tolerances

Trust

Journal

Calendar Tasks ContactsReputation

TolerancesTrust

Reference

HistoryWhat information do vendors and comparison sites provide?

What is my history with the various sites?

Are the network I'm on and my current device capable of supporting streaming video on the product at this moment?

Do I choose to share the fact I have just arrived at the store whose Web site I have been using for comparison shopping?

Can I easily validate the level of trust and security of the vendors I'm accessing on my smartphone?

Is the salesperson who I am working with available physically or online at this moment?

What are the tips from others making similar purchasing choices?

How much information do I expose to a vendor or a community? How do I repair my reputation if damaged?

What are my tolerances for m-commerce/e-commerce from an expense and usability standpoint?

Context

Brokers




Figuring all this out – Navigating through large scale complexity

Assuming

A desire to create the future

Triple Helix Strategy – Industry, Academia, Government

Experimental design

Quality data and its meta descriptions

Best research team

Best methods and techniques for analysis

Business willingness and patience to discovery the unknown

A new understanding of information economics

Then, how will you comprehend it all?

So that you make the best decisions based on evidence, analysis and intuition

Using transparency and access to complexity in a form that can be understood

We need to provide the methods for our top executives to fly through the complexity

Using new computational models, simulations, and interfaces

These interfaces would use Visualization, Sonification, and Kinesthetic navigation

One example of a new interface: G-Speak Overview



Suggested Next Steps for discussion

Grand challenges revised

Detail reviews of CFB project with each Executive in Residence

Detail review of Information Economics research proposal

Assessment on analysis and visualization techniques and methods applied to bank data

Presentation of MIT project assets to source innovations from

Consideration of grants to direct new research

Line up of innovation team within each LOB to work with research track

Alignment of marketing research, innovation team, and CFB research to spot Billion dollar opportunities

Advisory Board communication on effort to inspire the rest of the company



Big Company (statements heard in my first 90 days at BAC)

STAGNANT “We own the market we are just that big!”CYNICAL “It will never happen!”CONFUSED “What is going on in the market?”TOO LATE “How did that happen?”

Future Proof Company (why I am here)

THINK “Service as a Science”LISTEN “Co-create the future with the consumer”SERVE “Mass preference and configuration”SCALE “Human dynamics scale”ADAPT “Grow, split, shift, evolve”

Closing Remark



References and Suggested Reading list

CFB Research Macro Themes and research reviews posted on CFB website

CFB website for Network Economies blog posting by Ray Garcia

Hsinchun Chen and J. Xu The topology of dark networks: ACM Oct. 08

Bill Howard Analyzing Online Social Networks: ACM Nov. 08

Suggested Book List:

•Born Digital

•Honest Signals

•The Long Tail

•Crowdsourcing

•Network Power

•We are smarter than Me

•The Big Switch

•The Cluetrain Manifesto



For questions on this presentation contact:

Ray GarciaVisiting ScientistCenter for Future Banking at MIT Media Lab

[email protected]://www.linkedin.com/in/alterwork

Research Review Network Economies Innovators

Documents