SECURE SIMPLE EFFICIENT

BIG DATA, ECONOMICS AND CONFIDENTIALITY - ON OPTIMIZING THE MANY SMALL DECISIONS

Kurt Nielsen, CEO Partisia

Agenda •  Big Data - economics and private info •  Case 1: Towards an automated middleman •  Case 2: Confidential benchmarking

SECURE SIMPLE EFFICIENT

BIG DATA Economics and private info

More Information …

More detailed production More individual preferences Positions, images, samples, yours and others …

Clickstreams, previous decisions, yours and others …

Many Optimal Small Decisions

Without big data With big data

Strategic • Top objectives

Tactical • Tactical prior ”rules of thumb”

Operational • Operational prior “rules of thumb”

Strategic • Top objectives

Tactical • Linking the many operational decisions …

Operational • Optimal small scale decisions • Automated decisions

The challenge

Private Info is Valuable – Of Course

E.g. buying •  What is it worth to you and

others? •  Is anyone cheating? •  …

E.g. hiring •  Before hiring – who are

you? •  After hiring – what did you

do? •  … Sensitive personal

info Sensitive business info

Regulation (law/rules) Typically more

strong regulation E.g. rules to

enhance competition

Risk concerns (cost of leakages) Greater diversity in

perception … Mostly incentive

driven …

Great insight from 1979 •  Holmstrom (1979) Informativeness principle

–  Use any measure of performance to promote incentive

•  Myerson (1979) Revelation principle –  The best solution is to tell the truth to a trusted

third party acting on your behave

•  Shamir (1979) How to share a secret –  The ideal (technical) foundation for a trusted third

party

pk

Partisia (2009), “Secure Multiparty Computation goes live” Financial Crypto 2009 and commercial use …

Cited by 7302

Cited by 1841 (Nobel prize)

Cited by 8793

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TOWARDS AN AUTOMATED MIDDLEMAN

Many optimal small decisions

The Many Optimal Small Decisions Switching supplier (automatically) when optimal!

Customers

Traders

Exchange

Production Power plants

Nordpool

Lack of competition

Consumers Small firms

Fair competition

Large firms

Supply

Demand

Our primary focus

Professional Procurement – made simple and secure

4. Finding best price

3. Submit bids

1. Request auction

2. Learning your type

5. Accept = contract

1. Request auction 1.

3.

2. 4.

5.

STRONG SECURITY AND AUTOMATION

By the way – we also address cloud security

SECURE SIMPLE EFFICIENT

CONFIDENTIAL BENCHMARKING

Big data through security Danish strategic research www.cfem.dk

European strategic research www.practice-project.eu

Benchmarking to Assist Credit Rating

I need to invest to stay competitive!

Will he go bankrupt?

How competitive

is he?

Their debt: (Mostly known)

BUT too many with too much debt …

Farmers:

Secure  Benchmarking  to  Assist  Credit  Ra6ng  -­‐  Based  on  more  and  richer  data  …  

VFL

Data

Farmers

Data

RES

Confidential: •  Customers id •  Valuation of assets

Confidential: •  Individual accounts and

production data

Controlled by VFL

Controlled by banks

TTP

The consultancy house

… did I mention that we also address cloud security

Richer  Data  Set  and  New  Results  

ID Bank Score 1 Bank A 0,8 2 Bank A 0,76 3 Bank B 0,9 4 Bank B 0,87 5 Bank B 0,89

Known by VFL (a consultancy house)

Known by Bank A

Known by Bank B

Unique results!

An Example (Portfolio Benchmarking)

Portfolio benchmarking Portfolio benchmarking with bank specific values on land

My bank The other banks

Best Worst Best Worst

My bank

The other banks

SECURE SIMPLE EFFICIENT

CONCLUDING REMARKS

Concluding Remarks •  Harvesting the many small gains requires:

–  Lots of “true” and relevant information –  Simplicity and automation

•  As always: –  Good models! –  Good data!

•  Commit to compute directly on encrypted data ! a tool to access better data