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AI in Retail & Wholesale Loss Prevention

Using game-changing technology to transform loss into leadership.

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To stay competitive while continuing to deal with the impact of losses, retailers and wholesalers must:

  • Effectively manage the order-to-cash cycle while improving the maturity of their loss prevention strategy.
  • Use predictive techniques to proactively detect instances of fraud.
  • Control inventory shrink while providing customers with a safe and satisfying shopping experience.
  • Manage innovation and continue to explore opportunities to apply technological advancements to prevent inventory loss and theft.

Our Advice

Critical Insight

Embracing AI can help retailers and wholesalers analyze operational patterns to predict and proactively prevent mounting losses from theft, fraud, damage, wastage, and stockouts while continuing to enhance the customer experience across channels.

Impact and Result

Info-Tech recognizes the value of adopting AI in retail and wholesale. AI can help get a handle on losses by enabling not only immediate response to incidents as they happen but also a more proactive, preventative approach.

Info-Tech will provide:

  • A comprehensive understanding of the benefits of applying AI-enabled technologies for loss prevention.
  • A tool to help you assess the maturity of your current loss prevention strategy and identify areas for improvement.

AI in Retail & Wholesale Loss Prevention Research & Tools

1. AI in Retail & Wholesale Loss Prevention Storyboard – Explores various aspects of loss prevention in retail, with a focus on the value of applying AI-enabled emerging technologies to various loss scenarios across the entire order-to-cash cycle.

This research highlights how advanced technologies like AI, machine learning, and sophisticated surveillance systems can transform traditional retail operations, specifically focusing on enhancing loss prevention strategies to ensure retailers and wholesalers continue to operate in a safe and competitive manner.

2. Loss Prevention Risk Tool – Use this tool to compare the risk levels of loss for various functions in your order-to-cash cycle.

This tool will help identify functions at risk based on current loss prevention solution stack maturity and compare that with the occurrence and frequency of loss scenarios specific to the function under consideration.

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AI in Retail and Wholesale Loss Prevention

Using game-changing technology to transform loss into leadership.

Analyst Perspective

Using game-changing technology to transform loss into leadership.

AI has had a transformative impact on retail and wholesale. Advanced analytics and insights offered by AI provide retailers with an unprecedented level of understanding of in-store and warehouse activities. Adoption of AI-based solutions is a necessary step toward survival and profitability in the competitive retail landscape.

Loss from shrinkage, fraud, theft, damage, and stockouts are costing the industry billions of dollars annually. This is a persistent problem that has been plaguing retailers and wholesalers for years. By embracing AI, retailers can not only enhance their loss prevention strategies but also ensure a safer environment for their employees and customers. AI's ability to detect patterns and anomalies is pivotal in addressing potential threats. Additionally, using technologies like motion detection and computer vision, AI proactively responds to suspicious activities or breaches in security protocols. This approach is a game changer, enabling retailers to address threats before they escalate into significant losses.

Ethical concerns regarding privacy and the potential for false positives in AI-based systems necessitate a careful and responsible approach toward implementing these technologies. However, AI's role in revolutionizing retail and wholesale loss prevention is undeniable. This research highlights the importance of AI in retail and presents compelling reasons for its wider adoption for loss prevention in the industry.

Shreyas Shukla, Principal Research Director, Industry Practice

Shreyas Shukla
Principal Research Director, Industry Practice
Info-Tech Research Group

Executive Summary

Your Challenge Common Obstacles Info-Tech's Approach
Staying competitive while continuing to deal with the impact of losses.

Effectively managing the order-to-cash (O2C) cycle while improving the maturity of your loss prevention strategy.

Using predictive techniques to proactively detect instances of fraud.

Controlling inventory shrink while providing customers a safe and satisfying shopping experience.

Managing innovation and continuing to explore opportunities to apply technological advancements to prevent inventory loss and theft.

Integrating AI with existing systems and infrastructure can be complex and resource-intensive.

Implementing AI solutions raises privacy concerns and ethical questions about surveillance and consumer rights, leading to issues with legal compliance.

AI can generate false positives, which can lead to customer inconvenience and mistrust.

Significant investment required for advanced AI systems can be a major barrier, particularly for medium and small enterprises.

Absence of specialized skills to implement and manage AI systems.

Resistance to change, lack of buy-in from stakeholders, and cultural barriers.

Info-Tech recognizes the value of adopting AI in retail and wholesale.

AI can not only help get a handle on losses by enabling immediate response to incidents as they happen, but also take a more proactive, preventive approach.

Info-Tech will provide:

  • A comprehensive understanding of the benefits of applying AI-enabled technologies for loss prevention.
  • A tool to help you assess the maturity of your current loss prevention strategy and identify focus areas for improvement.

Embracing AI can help retailers and wholesalers analyze operational patterns to predict and proactively prevent mounting losses from theft, fraud, damage, wastage, and stockout while continuing to enhance customer experience across channels.

Retail and wholesale loss results from a variety of errors, inefficiencies, and stakeholder actions

Loss prevention practices are put in place by retailers to preserve margins, profitability, and, in some cases, their brand reputation. Understanding and identifying sources of loss is critical for retailers to ensure they provide their customers with a safe shopping experience and continue to function in a viable, profitable manner.

Types of Losses

Inventory Shrinkage
Loss of inventory due to theft, damage, or errors in stock management.

This can be external (shoplifting) or internal (employee theft).

This includes payment fraud via stolen credit cards, return fraud, and warranty fraud.

Returns Loss
When customers return used or damaged goods, or due to the cost of handling returns.

Supplier Fraud
Overcharging, short deliveries, or billing for goods not received.

Administrative Errors
Mistakes in pricing, accounting errors, or mismanagement of inventory.

Damage in Transit
When goods are damaged while being transported from suppliers or to customers.

Perishable Goods Loss
Loss occurs when items that have a short shelf life, like food, expire or become unsellable.

Operational Inefficiencies
Inefficient processes or systems, leading to increased costs and reduced margins.

Cybersecurity Incidents
Data breaches or cyberattacks can lead to financial losses and damage to brand.

Product Obsolescence
Products becoming outdated or irrelevant, leading to markdowns or disposal of stock.

Natural Disasters or Unforeseen Events:
Events like fires, floods, or pandemics.

Legal and Compliance Violations
Fines or legal costs arising from noncompliance with regulations.

Price Markdowns
Reducing prices to clear excess, outdated, or slow-moving inventory.

Resources wasted due to inefficiency, such as excessive energy use or over-ordering of materials.

Stores lose an average of $559 per shoplifting incident (National Retail Federation, 2018).

For every $100 in returned merchandise accepted, retailers lose $5.90 to return fraud (National Retail Federation, 2020).

Each step of the O2C cycle is impacted by loss

It is critical for retailers to understand the potential losses they can incur at each step of the O2C cycle. This helps retailers to better focus their loss prevention efforts, optimize processes, and implement effective controls to mitigate these losses.

Order-to-Cash Cycle Types of Losses
Order Management Incorrect Processing Order Fraud/Stolen Credit Card
Credit Management Credit Fraud/ Falsifying Information
Inventory Management Inventory Shrinkage External & Internal Theft Perishable Goods Loss Product Obsolescence Wastage
Order Fulfillment Damage in Transit Operational Inefficiencies Supplier Fraud or Error
Shipping & Delivery Damage in Transit In-Transit Theft
Invoicing Billing Errors Invoicing Fraud
Payment Receipt Chargebacks Fraudulent Payment Methods Cybersecurity Incidents/Data Breach
Returns & Refunds Returns Loss Return Fraud Improper Returns Handling
Reporting & Analysis Legal & Compliance Violations Cybersecurity Incidents
Accounting & Finance Price Markdowns Legal & Compliance Violations

The actual dollar loss associated with shrink is likely greatly underreported, since 78% of respondents do not include e-commerce goods loss in their shrink calculation, and 57% do not include supply chain loss or theft (National Retail Federation., 2023).

External theft and organized retail crime are major sources of concern for retailers

Retailers are highly concerned about the impact of organized retail crime (ORC) and theft on their customers and employees. Approximately 80% of retailers feel that the violence and aggression associated with ORC incidents increased in the past year.

Top Concerns % of respondents who think this is a priority in 2022 % of respondents who considered this a priority in 2023
Organized Retail Crime (ORC) 70.7% 78.1%
In-Store Violence 67.8% 65.6%
E-Commerce Fraud 61.1% 57.8%
Employee Theft 56.9% 48.5%
Loyalty Program Fraud 49.1% 48.3%

Sources: National Retail Federation, 2022; National Retail Federation, 2023.

More than 60% of retailers use technologies or software to identify ORC groups and monitor items lost to ORC.

Only about 31% of retailers have a dedicated team to deal with ORC.

44% of retailers have increased their use of technology, hardware, and software to combat ORC.

93% of retailers strongly favor federal ORC legislation.

72% of retailers reported an increase in average value per incident.

Source: National Retail Federation, 2023.

REI closed one of its best-performing stores in downtown Portland due to shoplifting. Spending on in-store security topped $800,000 in 2022 for that location.

Source: Investor's Business Daily, 2023.

"It's a real challenge for the industry right now, and it's not clear how quickly it's going to go away."
– Joe Feldman, Managing Director, Telsey Advisory Group, in Investor's Business Daily, 2023.

ITRG Loss Prevention Framework

Retailers are dealing with unprecedented levels of loss from inventory shrinkage

Inventory shrinkage is one of the highest contributors to a retailer's overall loss. Shrinkage results from criminal activities, fraud, wastage, obsolescence, damage, and discounting. Shrinkage is putting a dent in retailer margins and profits and the impact of these losses are being seen by retailers of all segments, sizes, and locations.

Chart of Inventory Shrink Calculated at Retail

Source: National Retail Federation, 2023.

Target saw a 120% increase in theft incidents involving violence in 2023. Target warned that inventory shrinkage would reduce profits by more than $500 million.

Dick's Sporting Goods cut full year earnings per share targets by 10% due to high levels of inventory shrinkage from organized retail crime and theft.

Kohl's, Dollar Tree, Home Depot, and Academy Sports & Outdoors all reported impact on gross margins from inventory shrinkage.

Source: Investor's Business Daily, 2023

The average shrink rate rose to 1.6% in FY2022, representing $112.1 billion in losses, up from $93.9 billion in 2021 (National Retail Federation, 2023).

Retailers are stepping up investments to deal with losses from theft and fraud

Retailers are seeing higher levels of violence in instances of retail theft and are also reporting an increase in e-commerce fraud, returns fraud, and loyalty fraud. Retailers are increasing investments in trained personnel, security budgets, and emerging technologies while also partnering with law enforcement at all levels.

Theft accounts for nearly 65% of retailers' shrinkage.

Source: National Retail Federation, 2023.

Stepping up Investments

"[M]ajor retailers are teaming up with technology companies to develop and deploy next-generation video surveillance systems, facial-recognition cameras, license-plate and vehicle readers, autonomous security robots, radio-frequency identification (RFID) tags, smart case locks and predictive analytic software. While versions of this type of security tech have been in place for years, they're now being superpowered by AI."
– CNBC, 2023.

Retailers are having to take immediate measures to deal with rampant crime and theft

Many retailers are experiencing such high levels of violent theft that they are left with no choice but to close several affected stores. Additionally, retailers are also taking immediate actions to curb the impact of rising crime by limiting products available in stores, locking commonly stolen goods behind protective displays, and reducing operating hours.

Operating Hours
45% of retailers have reduced operating hours in several locations.

Product Availability
30% of retailers have reduced/altered the availability of products in stores.

28% of retailers have completely closed some locations.

Source: National Retail Federation, 2023.

"Retailers are seeing unprecedented levels of theft coupled with rampant crime in their stores, and the situation is only becoming more dire. Far beyond the financial impact of these crimes, the violence and concerns over safety continue to be the priority for all retailers, regardless of size or category."
– David Johnston, VP of Asset Protection & Retail Operations, National Retail Federation, in National Retail Federation, 2023.

"These are crime levels we haven't seen before."
– Jeff Gennette, CEO, Macy's, in The Daily Mail, 2023.

"This is traumatizing for our associates and is unacceptable. … We are doing everything we can to try to create as safe as possible environment."
– Corie Barry, CEO, Best Buy, in The Daily Mail, 2023.

"I can say that there's active conversations about closing stores right here in Vancouver."
– Clint Mahlman, President and COO, London Drugs, in Global News, 2023.

ORC-related closures

Cargo theft has an exponential effect on retailers by adding to continuing supply chain disruptions

Cargo is at risk of being stolen at multiple points in the supply chain. This is especially prevalent when cargo is at rest at key nodes of the supply network such as distribution centers, inspection centers, loading/unloading points, and at retail locations.

Cargo theft occurs at several points along the supply chain network

Source: National Retail Federation, 2022.

  • 47.4% of retailers experience cargo theft en route from distribution centers to retail stores.
  • 42.1% of retailers experience cargo theft at stores.
  • 68.5% of retailers identified movement of cargo between distribution centers and stores to be the most problematic part of their supply chain.
  • 53.9% of retailers identified distribution centers to be the most vulnerable supply chain node for cargo theft.
  • The third quarter of 2023 alone saw 692 instances of cargo theft in the US and Canada totaling over $31.1 million in losses.

Source: Verisk, 2023.

AI-led emerging technology is shaping up to be an important contributor to loss prevention

Retailers have begun researching, piloting, and implementing AI-led emerging technologies for loss prevention purposes. While electronic article surveillance (EAS) systems continue to be the most widely implemented anti-theft technology, retailers have begun looking into the viability of implementing AI-led facial recognition, feature matching, behavioral analytics, vision systems, and other solutions.

Top Technology Priorities of Retailers in 2023

Top Technology Priorities of Retailers in 2023

Consideration of Loss Prevention Technology

Technology % of respondents actively researching % of respondents actively testing % of respondents actively using
AI-led fraud analytics for e-commerce 37% Data not available 13%
Body-worn cameras for employees 35% 11% None
Mobile surveillance units 19% 10% 18%
RFID 33% 17% Data not available
Facial Recognition 40% Data not available 3%

Source: National Retail Federation, 2023.

"Artificial intelligence (AI) emerged as a primary driver of holistic LP programs, which explains the sudden boom in popularity this approach has experienced. It seems AI is the latest piece of the LP puzzle, providing the context retailers need to elevate the deterrence value of their connected systems and safeguard their operations for a new era."
– "AI Is Transforming Loss Prevention," RIS, 2023.

AI offers significant potential in loss prevention

Leading AI-led loss prevention use cases in retail and wholesale.
(Order does not reflect importance)
Value Drivers
Ops. Efficiency Business Growth Customer Experience Employee Experience Risk & Resilience ESG
Suspicious Behavior AI-Powered Surveillance: AI can analyze video feeds in real time to detect suspicious behaviors and alert staff, reducing shoplifting and theft.
Facial Recognition: This technology can identify known shoplifters or banned individuals as soon as they enter the store, allowing staff to take preemptive actions.
Employee Theft AI Monitoring Systems: These systems can monitor point-of-sale transactions to identify patterns indicative of employee theft, such as voided transactions or unusual discount applications.
Return Fraud AI in Return Processing: AI can analyze return patterns to identify fraudulent behavior, such as repeated returns by the same customer or unusual return patterns of specific items.
Administrative Errors Automated Inventory Management: AI systems can automate inventory tracking, reducing errors in stock levels, pricing, and ordering.
AI for Data Entry: Machine learning (ML) algorithms can detect anomalies in data entry and correct them, reducing human error in administrative tasks.
Vendor Fraud AI-Enhanced Auditing: AI can quickly analyze large volumes of transaction data with vendors to identify inconsistencies or fraudulent activities.
Operational Errors Predictive Analytics: AI can predict and identify potential operational issues before they occur, allowing for proactive management.
Process Optimization: AI can optimize various operational processes to reduce errors and improve efficiency.
Loss Training AI-Driven Training Programs: AI can tailor training programs for employees based on identified weaknesses in handling theft, fraud, or other loss-preventing practices.
E-Commerce Fraud Fraud Detection Algorithms: AI can analyze transaction data to identify potentially fraudulent activities, such as the use of stolen credit cards or fake identities.
Behavioral Analysis: AI can monitor user behavior, transactions, and interactions on e-commerce platforms to detect and prevent fraudulent activities.
Dynamic Pricing Price Optimization: AI algorithms help in dynamic pricing, reducing losses from overpricing or underpricing.
Supply Chain Management Predictive Analytics for Stock Levels: Using AI to predict stock requirements, reducing losses from overstocking or stockouts.
AI in Logistics: AI can optimize supply chain logistics, reducing losses due to transportation mishaps or inefficiencies.
Counterfeit Detection: AI systems can analyze products to identify counterfeits, thereby reducing losses due to fake goods.
Demand Forecasting: Predictive models to accurately forecast demand, preventing losses due to unsold inventory.
Customer Experience Automated Customer Service: AI chatbots and virtual assistants to provide efficient customer service, reducing losses due to poor customer experience.
Personalized Experiences: By improving customer experience through AI-driven personalization, retailers can increase customer satisfaction and loyalty, indirectly reducing the likelihood of fraudulent returns and complaints.

Optimizing self-checkouts to prevent losses

AI-enabled cameras helped Kroger analyze unstructured video data in real time to identify and mitigate instances of retail shrink.

SOURCE: Lenovo, 2023

Challenge Solution Results

The Kroger Company operates supermarkets and department stores throughout the US. Kroger is headquartered in Cincinnati, Ohio with a revenue of $100+ billion from over 2,500 stores.

In their quest to provide their customers with a quick, easy, and convenient experience in-store, Kroger has been expanding its use of self-service checkouts (SCOs) throughout the US.

With the increase of self-service checkouts, Kroger noticed an increase in losses due to missed scans and product switching. To address losses from these actions, Kroger decided to turn to AI.

Kroger chose Everseen's Visual AI platform that uses high resolution cameras, computer vision, and AI developed on Nvidia's Accelerated Computing Platform. The Everseen solution can intelligently intervene when problems occur at the SCOs.

Everseen's AI runs on Lenovo's Edge AI servers. Video footage from SCOs is analyzed in real time to identify when a customer has not scanned a product or moved the barcode from a cheaper to a more expensive product.

The system will flag these problems and prompt the customer while simultaneously informing a store associate on their mobile device so they can intervene and rescan the item.

With Everseen's AI solution, Kroger was able to flag and correct over 75% of checkout errors without involving a store associate. This resulted in a direct reduction in retail shrink.

Since this solution works with legacy equipment, Kroger was able to rapidly scale its initial deployment to over 1,700 stores.

Given the success of this platform, Kroger has decided to employ other AI-enabled technology such as front-door face watching technology, camera monitored back-door delivery areas, and license plate recognition in their parking lots.

Using AI to boost performance of fraud operations

AI-powered decision frameworks allow Wayfair to accurately identify fraudulent transactions while maintaining no-friction customer experiences.

INDUSTRY: e-Commerce
SOURCE: Riskified, 2022

Challenge Solution Results

Wayfair Inc. is an e-commerce company that sells home goods online in many major international markets. Wayfair is headquartered in Boston, Massachusetts and operates a complex international logistics and infrastructure network to fulfill orders from over 20,000 global suppliers.

The vast selection that Wayfair offers has resulted in many years of hypergrowth for the company. They have a large internal fraud team that manually reviews up to 10% of all orders placed on the site.

Wayfair soon found it inefficient to keep expanding this team to keep pace with the growth of order volumes.

Wayfair chose to partner with Riskified to start by reviewing their declined orders. Wayfair was impressed with Riskified and soon expanded their partnership to use AI and manage fraud for all their US orders.

Riskified's solution uses AI for analysis of comprehensive data including device data, behavioral insights, past chargebacks, e-commerce activity, and known fraud patterns.

AI then draws insights from historical transactions and takes decisions in near real time. Data is used to continuously train Riskified's decision models to improve their chances of identifying false declines.

With Riskified's solution, Wayfair was able to reduce their cost of fraud by over 50%.

When Wayfair saw an unprecedented increase in order volume during the pandemic, Riskified was able to help them reduce their chargeback rate by 50% to 60%.

Riskified's solution was also able to reduce false-positive callbacks by over four times, thus continuing to maintain Wayfair's objective of 0% friction due to fraud reviews.

Using AI for accurate, competitive pricing analysis

AI-powered pricing strategies allow Neiman Marcus to make data-driven decisions, improving their competitive position in the market.

SOURCE: Centric Software, 2023

Challenge Solution Results

Neiman Marcus is a privately owned luxury goods retailer headquartered in the US. Neiman Marcus has 36 location across the US and brings in revenue exceeding $5 billion annually.

Neiman Marcus had a team managing pricing functions that had to manually manage markdowns across tens of thousands of SKUs. The team had to manually scrape competitor websites for pricing intelligence on each individual item. This process was too slow, costly, and inefficient.

Neiman Marcus started looking for an effective competitive pricing tool to replace their outdated pricing practices.

Neiman Marcus chose to partner with Centric Market Intelligence for their user-friendly and capable pricing system.

Neiman Marcus first tested the system with a few categories and a couple of competitors. They leveraged Centric's Product Matching module which helps compare the SKUs that Neiman Marcus carries with products from their competitors and execute like-for-like price matching and discounting. The tool was able to analyze trends to ensure that Neiman Marcus was doing assortment the right way, resulting in more buying conversion.

Given the Centric platform's user-friendliness, its use was expanded by Neiman Marcus to cover all of their categories and competitors.

Neiman Marcus experienced several benefits by using Centric Market Intelligence:

  • They achieved a more efficient and streamlined process for competitive pricing analysis.
  • Centric allowed for more accurate and timely decision making regarding pricing strategies.
  • It facilitated a deeper understanding of the competitive landscape, aiding in smarter pricing decisions.
  • Neiman Marcus was able to respond more dynamically to market changes and competitor pricing strategies.

Using AI for faster, accurate checkouts

AI-based smart scales with deep learning cameras allow Colruyt to enhance their customers' checkout experience.

SOURCE: Robovision, 2023

Challenge Solution Results

The Colruyt Group is a privately owned chain of stores that includes supermarkets, organic groceries, online shops, bakeries, toy stores, gas stations, and apparel stores. The brand is headquartered in Belgium and brings in over EUR$10 billion in revenue annually.

Colruyt faced challenges in speeding up checkout times, especially for products like fruits and vegetables that do not have barcodes.

The manual process of typing codes for these products at the checkout was time-consuming and could lead to confusion, queues, and delays.

Colruyt collaborated with Robovision to develop an AI-based system involving a "deep learning" smart camera installed above the checkout scales.

This camera automatically recognizes different kinds of fruits and vegetables when customers place them on the scale. The system proposes the right label to the customer, who then confirms the selection on a tablet.

Robovision's technology was a significant step in digital advancement for Colruyt, making the checkout process more efficient and reducing the workload for sales employees.

The AI technology provided by Robovision proved to be highly effective.

Robovision's solution could successfully identify over 97% of the products correctly. This not only sped up the checkout process, but also enhanced customer experience at the checkout counter.

The technology continually improves with each interaction, resulting in faster, more accurate product recognition and quicker checkouts for customers over time.

Using AI for improved security, integrated analytics, and useful customer insights

AI-based video surveillance streamlines Canadian Tire's security process and enhances customer conversion analysis.

SOURCE: Solink, 2023

Challenge Solution Results

Canadian Tire is a well-known Canadian retail company specializing in automotive, hardware, sports, leisure, and housewares sales. Canadian Tire is headquartered in Toronto, operates over 2,000 stores across eight different brands, and brings in over Can$17 billion in revenue annually.

Canadian Tire, particularly the Caledonia store, faced challenges with their traditional DVR security system. This included the difficult process of retrieving video footage for law enforcement and the inability to efficiently analyze customer behavior in the store due to limitations in existing technology.

Canadian Tire Caledonia opted for Solink's cloud-based video surveillance solution.

Solink provided a modern system that could integrate with Canadian Tire's existing hardware and provide more functionality:

  • Solink was able to connect to cameras that belonged to three different generations.
  • Solink was also able to provide Canadian Tire with a way to measure conversion rates.

The Caledonia store decided to upgrade their cameras to Hanwa's latest models to leverage the Solink platform's additional capabilities related to behavioral and conversion analytics.

By implementing Solink and upgrading their camera setup:

  • Canadian Tire gained a more efficient and user-friendly surveillance system that made it easier and faster to access security footage, saving significantly in the process.
  • Additionally, Solink's people-counting capability enabled Canadian Tire to better understand and improve customer conversions and sales.

The store could now accurately track the number of visitors and their purchasing behaviors. This led to more informed decisions regarding store layout, product selection, and customer service tactics, ultimately impacting the store's revenue positively.

Using AI for email attack/phishing prevention

AI-based attack prevention allows Pres Les IT employees to focus on more productive pursuits.

SOURCE: Ironscales, 2023

Challenge Solution Results

Pres Les is a 50-year-old South African direct-to-consumer sales company that sells luxury bedding, home accessories, and cookware.

Pres Les embarked on a massive digital transformation initiative that included new service delivery tools, a new website, extensive cloud infrastructure, and other digital innovations.

As new digital systems came online, Pres Les had to deal with phishing attacks, ransomware, and other cyberattacks that could not be handled using native Microsoft 365 security capabilities.

Pres Les employees had to deal with a large volume of emails from customers, suppliers, and consultants. Some of this communication included proof-of-payments and other business-critical communication. Pres Les partnered with BDO and Ironscales to deploy a proof of concept (PoC) which was overwhelmingly successful.

Based on the success of the PoC, Pres Les decided to implement Ironscales' AI-enabled email filtering and advanced phishing detection capabilities.

After implementing Ironscales, Pres Les saw tremendous improvements. In a three-month period, Ironscales:

  • Inspected over 400,000 emails.
  • Identified and prevented over 451 incidents.
  • Remediated over 1,000 emails.

Ironscales continuously runs in the background and blocklists suspicious emails, allowing users to safelist the correct ones if not identified by AI. Since deploying Ironscales, Pres Les' IT team is spending less time dealing with these attacks and instead are focusing on more productive activities.

Organizational maturity informs the readiness to implement advanced loss prevention methods

Basic Structured Enhanced Integrated Advanced
  • Minimal training in loss prevention
  • Basic security measures without specialized roles
  • Increased awareness regarding loss prevention methods
  • Basic training programs available
  • Roles with specific focus on loss prevention exist
  • Staff receives ongoing training in loss prevention strategies
  • Loss prevention integrated into various business functions
  • Staff across departments are engaged in loss prevention
  • Culture of loss prevention throughout the organization
  • Highly trained staff, specialized roles in analysis and technology
  • Ad hoc and reactive processes
  • Limited standard procedures for handling theft or shrinkage
  • Structured processes for handling incidents
  • Regular security audits
  • Systematic processes for loss prevention, driven by insights from data analysis
  • Cross-functional processes established
  • Proactive and predictive processes
  • Continuous refinement based on real-time data
  • Basic security equipment like locks and simple cameras
  • Upgraded surveillance systems and anti-theft devices like EAS tags are implemented
  • Introduction of data analytics tools for monitoring and reporting
  • Implementation of advanced technologies like AI and ML for predictive analysis
  • Cutting-edge technology like AI-driven surveillance, real-time analytics platforms, and sophisticated data integration tools
  • Minimal collection and use of data
  • Initial collection and review of theft and fraud data
  • Limited analysis
  • Regular analysis of theft and fraud data
  • Use of data to identify patterns and inform loss prevention strategies
  • Deep analysis of data for predictive insights
  • Integration of data across different systems
  • Real-time data monitoring and analysis
  • Use of big data and predictive modeling
Measurement & Outcomes
  • Basic incident tracking, with no dedicated KPIs for loss prevention
  • Tracking of basic KPIs like incident rates and training completion
  • Dedicated KPIs including shrinkage rates and inventory accuracy
  • Advanced KPIs measuring the effectiveness of loss prevention systems
  • Comprehensive KPIs including response rates, AI effectiveness

Most retailed are at the Structured maturity level.

Using game-changing technology to transform loss into leadership.

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Shreyas Shukla


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