Omni/Multichannel: Another Channel for Shrink?

Omni/Multichannel: Another Channel for Shrink?

Professor Joshua BamfieldDirector, Centre for Retail

Research

Centre for Retail Research, Nottingham

Another Channel for Shrink?Agenda The rapid growth of online trading Crimes against IT Order fraud Payment fraud Omnichannel Issues Refund fraud Clean fraud Delivery fraud

Multi or Omnichannel?

Currently, retail growth = Online plus some discount areas. The game is currently about linked multichannel Omnichannel is a direction of travel rather than a

destination. Online market share in 2012 - 12.7% [£35-38 bn]

Food online share 3.7% Non-food online share 19.2%

Online market share in 2018 - 21.5% [may take longer] Food online share 9.5% Non-food online share 32.1%

Around 60,000 stores expected to close


What are the issues?

New styles of retail and of IT. Mobility, cloud, virtualisation, end- point proliferation, big data, analytics.

Speed of Market development Faster than security, risk, shrink concerns

Language. Cyberattacks (never theft), hackers, terrorists, evil geniuses, hacktivists

Operational changes. New retail – driven by IT, analytics, finance; store retail – store operations & security and risk. Who owns multichannel shrink?



Cyber-Problems

Category A: Crimes against IT Website capture, data theft, customer ID takeover, DDoS, hacking. Govt believes cybercrime costs £27 bn pa

Category B: Crimes using IT Payments fraud, fake orders, consignment fraud


Crimes against IT

Category A. Crimes against IT Breaking your system:

Distributed Denial of service (DDoS) Email bombs

Website hacking: misinformation, or data theft Fake/Proxy sites: fraud or reputational

damage, website scraping or a spam site Website data feeds: get less attention than

visitor pages. SQL injection flaw – dump data to a new site

Your success breeds envy resentment and attacks

And there are plenty of retail own goals.


IT Solutions

Monitor/prevent scraping Excess traffic monitoring Blocking IP addresses Commercial anti-bot software Honeypot tests ? National Cybercrime Unit


Employee fraud

Collusion…. and ORC The man in the call centre -

multichannel Warehouse and distribution Poor treatment of stock

Similar issues to yesterday’s retailing.


Category B – Attacks using IT

False orders Employee frauds Payment fraud Return fraud Clean fraud


False orders

1.40%-1.65% of orders are fraudulent Loss around 1.26% or £429 million Loss:

Fraud loss Profit loss from refusing honest customers Administrative costs of avoiding loss

Screening for bad orders …….. 58% manually reviewed 71% of reviewed orders accepted 4.3% rejected for fraud


Rule-based Systems

Country or area – UK retailers pushing at borders.

Calculate objective risk factors: high value, high frequency, multiple items, risky postcode, expedited shipping, new customer. Behavioural risk: speed of purchase, use of website, hovering. Analytical software: monitor customer

conversion rates, metrics, average checkout time and no. of pages, 2-3 day changes in ordering/delivery postcodes or products.

Assess by channel


The Right Customer

Authentication – problem of abandoned baskets.

Do we want to know if this is the right customer?

User code and PIN usual + cookies Device information - Usually collect

IPaddress (PC) or IMEI (mobiles). Regular customer continuing usual

routine? Mobiles – authentication harder than PCs Multifactor authentication might be the

answer, but take-up even of 3D secure is weak.

May well be driven by payment technology (if at all), but problems with mobile transactions


Criminals taking over customer accounts: some options Account password storage. Password strength Taking control of cookies XSS/cross site scripting issues (mixed mode

website coding) Obviously IT has to fix these things..BUT White Hat Security Report – May 2013

- 86% of all sites – at least 1 major security flaw- Av no. of serious flaws 56 (230 in 2010)- Time taken to resolve issue - weeks- IT websites – most flaws


Payment fraud online

Raises same issues as any payment fraud, but no card required

Dependent on order acceptance Use:

Card verification/CSC 70% 3D secure/VbyVisa 61% Address verification 56% Postal address validation 24%

Supplementary IP Geolocation 17% Device fingerprinting 8% 2-factor authentication – eg PIN and token


Scope of Payment Fraud

Card fraud fallen by 70% since 2004 Online payments fraud around £90 mn or 0.26%

of t/o If near the barrier, banks more vigorous with

chargebacks and will change conditions of acceptance with limited notice.

Use of Paypal – security issues in concealing customer payment details


Delivery fraud and shrink

Click & Collect shows whether goods have been received. Really? Is Click & Collect a shrinkage hazard? Delivery address changes, hot

postcodes, & address checks help somewhat

Packaging and delivery affects waste Email and sms with customers – delivery

options and time slots. Reduces fraud, prevents revisits

Doorstep thefts


Omnichannel

Single view of customer – previous purchases, preferences/sizing, goods on order, payment methods, wish lists.

Means dipping into many databases, and auxiliary data pools.

= risk Shrinkage: analyse by

product/category and channel


Returns

Major online problem - difficult to control

Sizing and product info can be of some help

Storage issues of returned merchandise Use of returns to a physical store may

improve control. Option choice Sharing information with other retailers

will show excessive returners


Mobile phones

Mobile is Fastest Growing Area Users do not update their software Proportion of users check email thru

smartphones and can be compromised Authentication a problem Malware eg Certificate.apk security app

sending bank details to +44 number. Perkele diverts sms messages to malware owners.

Android OS used for 79% of 2012 malware. Non-pay exploits now v. popular.

Tablets – few security devices and anti-virus


Clean fraud

In the US, clean fraud is now seen as the biggest problem and is hardest to screen.

Customer behaviour and age of account Metrics: age of email account, electoral

roll, discrimination by product …. Dependent on continuous monitoring

Go deeper: social media, internet search.

Curbing online shrinkage Security risk and audit follow in the footsteps of

IT and marketing Omnichannel – multiplies risks. Vulnerabilities at

every stage Risks v reward has to underlie decisions There is excessive manual order screening Trends by value and by location mean more

screening tools required Shrink in distribution, return, and delivery very

important. Communication….. Data sharing will help with key metrics.



Thank You

Prof Joshua BamfieldCentre for Retail ResearchNottinghamNG22 9HQ01623 867559www.retailresearch.orgTwitter: cristobel75

http://www.retailresearch.org/

Omni/Multichannel: Another Channel for Shrink?

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