Sift, formerly known as Sift Science provides complete digital trust, online fraud prevention and safety to companies. Initially, they provided only online payment protection services but with the increased response from the customers, the company has extended its services to combat fake accounts, content abuse, and account takeovers. In this Sift review, we analyze how it makes use of machine learning and has developed various algorithms to detect online fraud and help in fraud prevention.
On the basis of these algorithms, they provide users a score on a scale of 0-100. The score indicates the probability of the user being fraudulent. Companies use this score before customer on-boarding. It helps the companies to reject fraudulent applicants and minimize the rejection of good customers. Overall, Sift’s software helps companies in fraud prevention even before they happen!
Addressable Market Size for Sift
We live in a digital world where the future is going to be ‘online’. Technology has enabled businesses to take the huge leap of going online from offline. As much as we love the ease of shopping and working online, there is an added threat: fraud. Thus, fraud prevention is highly required now more than ever.
According to a survey conducted by Merchant Savy, payment fraud is expected to continue to increase and cost $40.62Bn in 2027 which is 25% higher than what it was in 2020. The year 2019 registered a record high of identity fraud losses that amounted to $16.9Bn. The Federal Theft Commission (FTC) report of 2019 mentions that 1.7 million fraud cases were reported and 651,000 were complaints of identity theft.
Every industry, when operating online has a risk of losing revenues due to fraudulent activities. Online shopping sites, e-commerce sites, dating apps, hotel bookings, the travel industry, and many such industries are potential grounds for fraud.
Juniper Research predictions say that online payment frauds are set to rise by more than 50% until 2024. According to a PwC study, global economic crime has risen in the last two years. It has increased by 17% in North America, 16% in Asia, and 25% in Latin America. In dollar terms, it will exceed $25Bn per year. In view of the above numbers, any company would prefer a product that can shield them from fraud and ultimately from loss of revenue. This makes us say that Sift is operating in an environment where it has a huge addressable market for fraud prevention. The company is solving a major problem for companies and helping them distinguish loyal customers from fake users.
Why is Sift a high demand product
There are various reasons due to which a company might choose to partner with Sift for fraud prevention. The most essential being the cost and time saved for the company. This time would otherwise be wasted in detecting fraud and providing customers whose accounts were used by fraudsters. Moreover, the company may also have to bear the loss due to fraud.
Reduces the cost of online fraud prevention for the company
Companies try their best to ensure online safety and fraud prevention. However, every company has data for their particular customers only. Apart from that, it is highly expensive for the company to develop foolproof software that can curb online frauds. According to Security Magazine, it costed $57.8B to businesses in 2018. Data from the Global Fraud Index indicates that in Q2 2017, account takeover escalated to 45%. Account takeovers attributed a loss of $3.3 Billion to merchants. Every successful fraud also takes a toll on the company’s revenues. This is where Sift comes into the picture. They have developed algorithms that every company needs, to run its operations smoothly and to prevent fraudulent activities.
The companies cannot afford to lose out on huge revenues figures. It is also very difficult to develop software to curb different fraudulent activities. Putting too much focus on these aspects can derail the company’s core business area and ultimately reduce the quality of service. Putting such huge software in place is an additional expenditure that can be avoided using Sift. Any company would prefer partnering with Sift as it has already developed the algorithms and will do the job for the company. Therefore, Sift should have huge demand as it eases clients’ operations and improves efficiency of businesses by letting them focus on their core products.
Facilitates enhanced customer service
A company always has to face a trade-off between security and customer service. To ensure complete security and have zero cyber thefts, they have to put more time in background checks during user on-boarding. They also have to do a thorough KYC for customers. This entire process may sometimes seem a bit too much for the user, hampering their experience with the company. Many users may not want to go through such solid checks and decide not to be associated with the company. It is also difficult for a mid-scale company to invest so much time and resources for these purposes, as they have limited budgets.
Sift’s solid software enables the company to clearly distinguish between fraud and loyal customers. With this, its clients can be in a better position to serve their loyal customers. They can provide better customer service to these customers as they don’t have to worry about fraudulent users, as it is taken care of, by Sift.
Sift helps companies to expand & choose the right customers
A few regions are directly associated with frauds. Companies are always skeptical about expanding to such territories. Countries like Indonesia, that has observed more than 35% of transactions to be fraudulent, tops the list. Other countries include Mexico, Brazil, Venezuela, and Romania. These can serve as worthy locations for companies to expand but they might not consider these locations due to high fraud rates.
Sift solves this problem for its clients by taking care of fraud prevention. It helps the companies to expand to all possible locations and chose the right users from those regions. This can help companies multiply their revenues.
Sift review: Competitive Advantages
Sift has designed a product that ensures digital trust and safety using machine learning. The company has been able to develop an algorithm using the digital footprint of users across websites. It uses this data to map the user-provided credentials. Individuals are provided a Sift score on a scale of 0 to 100. This score indicates the probability of the user being a fraud.
Sift score is like a credit score, which is provided by the credit bureaus to individuals based on their credit history. The credit score proves the credit-worthiness of the individual. On basis of this, the companies provide loans to individuals. Sift on the other hand provides scores to individuals using machine learning based on their likelihood of doing a fraud . Companies use this score to make the decision to accept or reject the customer. The objective is fraud prevention and help companies reject fake users as their customers who can later defraud the company. They have multiple features that enable them to increase efficiency in fraud detection and fraud prevention.
As over 33,000 sites and apps use Sift, it is able to collect user behavior data from all these companies based globally. It is thus a custodian of massive data. Sift uses this data to compare users from one platform to the other. It tracks locations, email IDs, billing addresses, etc. With access to this massive data, Sift is able to easily detect fraudulent activities. Along with that, it has also helped Sift improve accuracy.
The company analyses over 5 million global frauds per month. The number is sufficient enough to make us believe the unmatched accuracy that the company has developed. It is almost impossible for any single company to gather such a huge data, as they only have access to their own customer records. Sift, on the other hand, uses the footprints from all the websites and companies it has partnered with, and provides a single score to the end-user.
Custom made Algos
Every business model is different and thus the type of fraud in every industry is different. Sift’s algorithms are custom made as per the industry. They have generated 16,000 fraud signals with the help of this custom learning. These signals are used to detect fake users and help companies in fraud prevention.
Sift review: Competitor Analysis
Sift faces close competition from companies that use machine learning and AI to detect fraud.
The company uses AI-powered programs to detect fraud. It combats hard-to-detect frauds in the e-commerce, travel, and financial service sectors. Fraud.net has offices in New York, San Francisco, and London. Fraud.net and Sift have very similar lines of operations, which makes us say that they are close competitors.
However, Sift is catering to all websites and industries. On the other hand, Fraud.net provides service only to the 3 industries mentioned above. Sift, having a wider base has access to more data. Serving different industries also allows it to improve its machine learning. The intuitive software can take inputs from these companies and identify custom frauds of each industry.
When the founders of Signifyd were working at PayPal and FedEx, they realized something was wrong about the way payments are processed. That’s when they decided to start Signifyd. Signifyd also uses machine learning to generate a yes or no signal for client on-boarding. The company currently is aiming to provide retailers friction-less delivery. Samsung, Lacoste, Stance are a few companies that are already benefiting from Signifyd.
Kount is another company that uses advanced machine learning to detect and prevent fraud. It has been serving in 130 countries and has customers such as Baskins & Robins, U.S. Polo Association, and Conair. The company covers all major sectors like Oil & Gas, travel, financial services, food and beverages, hotels, retail, and many more. Kount launched in 2007 and has raised $80M in funding as of now. Whereas, Sift was launched in 2011 and has raised $108.2M to date.
Sift review: Scalability
Any company that increases the revenues and decreases costs in the long run, is said to be highly scalable. Software is one such product that is highly scalable as it is not a physical product. This is the very reason that software companies attract huge angel and VC funding. It is safe to thus comment that Sift is already a lucrative business for VCs.
Initially, the company invested a huge amount in the programs that had to be developed. Now, it is only a matter of adding new companies to their list. They do not have any other huge variable costs as the software requires fixed cost investments only in the beginning. We believe that Sift can expand easily to new geographies and sectors. It is only a matter of time that Sift starts providing services across the majority of countries.
Sift review: Exit for VCs
Sift Science is a very lucrative business model for takeover by companies in the same line of business. Even if the company is not acquired by any bigger player, Sift has the potential to turn itself into a global business. Companies operating in the following sectors can consider acquiring Sift:
Credit rating agencies
Rating agencies provide credit ratings to individuals that indicate their credit-worthiness. Similarly Sift provides rating for fraud likelihood. Therefore Sift can be a good acquisition target for companies like Experian, Equifax, and TransUnion etc. The credit rating agencies can dervive lot of synergies from this product as they can provide a comprehensive score including the likelihood of fraud. Since apex institutions trust the scores given by CRAs, they have to ensure that they do not provide scores to individuals who are not trust-worthy. It can be tiring for these agencies to develop a foof proof software from scratch, instead, they could acquire Sift. This will give them an established algorithm and data that can help them reduce their rejection rates drastically. It can also help them in reducing customer on-boarding time.
With increasing online fraud, the onus is on the federal agencies to not only protect online transactions but also to solve existing frauds. These agencies have to hire software experts and forensic experts to investigate online frauds. The pressure is even more as huge amount of money is involved. Fraud may also happen in government accounts and in such cases, the stakes are very high for the federal agencies. At such times, these agencies can use Sift’s software which will help them not only solve these transactions but also prevent them in the first place. Therefore Sift’s technology can be utilized for national security matters as well
Sift review: Key facts
At present Sift has 11 team members;
Jason Tan is the co-founder and CEO of Sift. He has previously worked as a software engineer at various Seattle start-ups. Jason has previously worked at Zillow, Optify, and Buzzlabs. Five of the engineers at Sift have previously worked at Google to detect spam ads and scams.
Sift provides a complete Sift-Services Suite to its customers. The Suite comprises of SaaS-based digital trust and safety products. The products offered by Sift are mentioned in the following section. Each company can choose products based on its requirements and entail Sift’s services. Sift’s custom machine learning has also developed industry-specific signals that identify patterns in data. Moreover, digital footprint mapping helps them to detect the probability of the user being a fraud.
For example, Sift compares the email address of the user with the shipping address. In true cases, the shipping address and email address initials should be the same (eg- [email protected], Robin Paxton, Street-3, US) Along with this, the software also detects the IP address of laptops. If these are far apart, it raises a red flag and points towards the user being a fraud.
Products offered by Sift
Sift’s products include payment protection, content integrity, and account takeovers. These products provide features such as chargeback reduction, traction withdrawal, spam and scan protection, fake account signup, promo abuse protection, and many more.
Since Sift is based on custom and live machine learning, every company can choose the product suitable for their industry.
Total funding received till date
Sift has raised more than $108.7M over 8 rounds of funding.
- Series A funding of $4M on March 19, 2013. Union Square was the lead investor.
- Series B funding of $18M was raised on May 14, 2014. Spark Capitals was the lead investor for this round of funding.
- Series C was led by Insight partners on July 19, 2016. Sift raised at $30M
- Sift raised $53M in the latest round on March 21, 2018. Stripes Investors were the lead investor in this round.
- The company raised an undisclosed amount through secondary markets on July 10, 2018.
Sift review: Conclusion
Digital transactions have become part of our life, therefore it is high time that companies combat fake users. Doing so, will not only improve the efficiency but also contribute to the safety of users in the financial space. Sift claims that 56% of consumers are predicted to leave the brand forever if they fall prey to fraud on the brand’s website. As companies focus more on their core line of business, combating fake users and account takeovers takes the backseat.
Sift can prove to be the perfect solution for these problems. It has not only developed a solid system but has collected tons of data during its operating history of over 7 years. Today, it provides services to companies such as McDonald’s, Twitter, Airbnb, DoorDash, and many more.
Sift provides a complete solution to fraud prevention and has covered every possible kind of abuse that fraudsters can use to target a brand. The company has developed a robust software that can meet the needs of every brand and counter almost every type of fraud. Individual companies may have to invest heavily to get such tight security in place, therefore Sift becomes a reasonable option to go ahead with.
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