This is one of the eCommerce startup ideas from the 1001 Startup Ideas collection of YoStartups. This business idea is to build a tool for Fraud detection in eCommerce Transactions using Machine Learning & AI technologies. eCommerce fraud is one of the biggest concern for any online merchant, making them lose millions of dollars every year in terms of lost revenue.
Market Definition for Fraud detection in eCommerce Transactions
As per a report by fraud prevention specialist Signifyd Inc., eCommerce fraud over a two year period through the end of 2017 increased 7% across all merchant categories. The Index reported the level of total fraud losses increased from 3.8% of sales volume in 2016 to 4.09% in 2017. All in all, the eCommerce industry suffered an estimated revenue loss of $6.7 billion due to chargebacks alone in 2016, while the overall eCommerce frauds cost around $15 billion. Every dollar of fraud cost eCommerce merchants $2.40 in 2016, up from $2.23 in 2015. Below are some of the key insights based on the same study;
- 68% of the online businesses are anticipating fraud and 62% plan to invest more in fraud prevention
- 40% of consumers who file a fraudulent chargeback will do it again within 60 days and 50% within 90 days
- Credit card chargebacks are rising at a rate of 20% per year, and friendly fraud rose by 41% over the last two years
Competitor Analysis for Fraud detection in eCommerce Transactions
There are several companies globally that are operating in the online fraud segment, but most of them restrict themselves to curbing payment frauds. Yet there are few companies that have tailored their solution specifically to meet the needs of the eCommerce industry. Signifyd is San Jose based, SaaS enterprise-grade fraud technology solution for eCommerce stores. It simplifies fraud detection through a financial guarantee, allowing businesses to increase sales while reducing fraud losses. Another similar company is SaFo based Sift Science. It applies insights from a global network of data to detect payment fraud, content and promo abuse, fake accounts, and account takeover. Companies like Airbnb & Yelp rely on Sift Science’s real-time machine learning to prevent fraud, slash operational costs, increase revenue and create outstanding user experiences.
Pain Point & Target Audience for Fraud detection in eCommerce Transactions
The target audience for the proposed startup would be online sellers and eCommerce platforms. Fraud is one of the biggest problems for online sellers and eCommerce platforms, especially at the scale-up stage. It’s not that the companies are not doing anything about these frauds, but most of the existing methods are rule-based, which are not adaptive and therefore fail to identify new fraudulent patterns; and the general rules are not good enough to differentiate between genuine customers and fraudsters. For instance, at one point India’s largest eCommerce company was not shipping anything over INR 7000 to over 20% of the population in the country in order to curb fraudulent transactions.
Value Proposition for Fraud detection in ecommerce Transactions
The proposed startup will build a solution based on artificial intelligence and machine learning so as to be more predictive in identifying fraudulent activities and transactions. This will also help the online merchants in differentiating between a customer with genuine issues and fraudsters, resulting in better customer service and retention. Since the process will be mostly automated, it will reduce the cost and time in screening all the orders and transactions.
Business Model for Fraud detection in eCommerce Transactions
The startup will provide its services on SaaS-based subscription model, where the online merchants can integrate the service to their online ordering platform and screen all the activities made through their platform. The startup can have multiple levels of subscription model basis number of transactions and added modular functionalities.
Way to market for this eCommerce Business Idea
The startup would first need to perfect its algorithm to detect and learn upon the fraudulent transactions over eCommerce. For this, the startup should start by working with small online sellers and refine its process. Once the algorithm is full proof in identifying most of the fraudulent transactions, then only they should launch it for the eCommerce platforms. For launching the product, the startup can target some of the countries in Asia and South America, which are quite infamous for their rate of fraudulent transactions. Indonesia is one of such countries which is rated high for eCommerce frauds and provide enough market bulk as well.
Milestones for a Startup doing Fraud detection in eCommerce Transactions
The startup should look to develop the first cut of the eCommerce fraud detection algorithm in the first 3-4 months. Post that it should test the algorithm with a few of the online sellers in order to debug and make it more predictive in nature. Once the product is complete, the startup should target to launch it for the established eCommerce platforms by the end of the first year.
Investment Needed For Prototyping This Business Idea
For testing and building the product, the startup should look to raise about 50K USD from cybersecurity or SaaS-based accelerators or angel investors. The raised fund should be used for IT infrastructure and on-boarding & testing the product with early customers.
Team Capability For this eCommerce Business Idea
For building a startup that will do Fraud detection in eCommerce Transactions, the team must have a co-founder with a deep understanding of statistical modeling, machine learning & data mining concepts, and a track record of solving problems with these methods. The team would also need a member with hands-on experience in running and managing production distributed databases which would be critical in scale-up.
Investors / Expert Take on this eCommerce Business Idea
There are multiple ways the fraudsters are employing to rip the online sellers of their hard earned profits. These frauds include from Return to Origin (RTO), to using customers identity to fake the transactions. For years the eCommerce companies took these frauds as part and parcel of their trade but with the vanishing venture investments and shifted focus to profitability has made them to put further attention to these frauds. The growth of companies like Sift Science shows the adoption of the proposed product with the large platforms like Airbnb and Yelp. They have also raised $100 million plus investments from across various investors, further strengthening the relevancy of the proposed product.
Copyright All Rights Reserved © Yostartups | Please do not copy without written permission | www.yostartups.com
This 1001 startup ideas article is from Yostartups, YoStartups is a Pre Accelerator, and it empowers entrepreneurs to propel their business ideas into successful ventures. Yostartups’ core mission is to take the message of entrepreneurship to 1 billion people globally by 2020.
In case you are looking at scaling or launching a venture on similar lines, you can apply for our virtual acceleration program Excelrate on our website, Yostartups.com, Yostartups’ Excelrate program will help you in streamlining and structuring your startup idea. We have limited scholarships and discount packs for deserving business ideas, depending on the strength of your startup ideas, you may qualify for a discount.