Securities Industry Essentials (SIE) Exam

The qualification tests for several occupations in the financial services industry, formerly known as the Series exams, have been streamlined into one initial exam called the Securities Industry Essentials Exam—or the SIE Exam. Passing this exam qualifies you to pursue a career in the financial services industry.

Back in 2015, Financial Industry Regulatory Authority (FINRA) streamlined its testing structure by consolidating the fundamental knowledge shared across several of the Series exams into the SIE. Candidates can then take an additional "top-off" qualification exam for the specific field they hope to enter.

The SIE had a major structural impact on the qualification exams. The SIE replaces portions of every previous exam, including the Series 6, Series 7, Series 22, Series 55/56 (replaced by Series 57), Series 79, Series 82, Series 86/87, and Series 99. These tests were shrunken, becoming qualification exams that focus on the specialized knowledge needed for each particular qualification.

Top-off exams are offered for the following representative categories:

Overall, this was clearly an effort to remove some of the duplicated information in the tests, but it also opened the door to a much more important change to the process of qualification, which is no longer having to be associated with a FINRA member firm to take the SIE.

Under the former FINRA rules, you generally needed to be employed or otherwise sponsored by a FINRA member in order to take the exams. The SIE removes this requirement, although you still have to be associated with a FINRA member firm to take the top-off exams. This means that an individual can choose to start on the path towards a FINRA qualification on their own.

Successfully taking the SIE doesn't guarantee anyone a successfully break into the financial industry, but it is safe to say that passing it prior to looking for a job may give you an edge as a prospective employer only needs to sponsor the top-off exam to get you qualified for a particular role.

FINRA supported the idea that recent graduates and people looking to get into the industry should take the SIE on their own. They’ve made it more attractive by extending the validity of the SIE to four years, giving a generous window for passing participants to then find a firm to sponsor the top-off exams. FINRA member firms are able to see who has passed the exam via the Central Registration Depository (CRD).

In their original Securities and Exchange Commission filings, FINRA targeted the fall of 2016 to early 2017 for a rollout of their highest volume exams. This proved to be a bit optimistic. There were several shifts in the scheduling, one resulting from the requests of member firms and industry associations for more time to set their own processes in accordance with the new structure. The SIE and top-off exam rollout took place on Oct. 1, 2018 and was accompanied by the retirement of multiple low-volume exams, such as the Series 42 and Series 62.

Originally, March 2018 was targeted for the implementation of the SIE and top-offs for Series 6, 7, and 79. Oct. 1, 2018 became the date for a complete overhaul rather than a phased-in approach. Adding to some of the confusion was part of the attempt to modernize; the Series 55 was replaced by the Series 57, although it still appeared in the original notice for the SIE updates. That update was simply a standard part of FINRA reviewing and tweaking curriculum, rather than part of an overhaul of any core knowledge.

The SIE exam structure is largely based on the general knowledge components of the exams it replaced that portion for. In January 2018, FINRA provided more details on the structure. The sections and question count are as follows:

The 75 questions are actually 85, since there are 10 randomly distributed pre-test questions that do not count towards the score on the exam. Candidates have an hour and forty-five minutes to complete the entire exam. A full outline of the SIE content is currently available on FINRA's website.

Passing the SIE exam can provide a number of benefits to your career:

If you already passed one of the FINRA exams and are currently registered as a representative, you are considered to have passed the SIE already. If you passed one of the exams and are not currently registered, you may need to take the SIE depending on how many years elapse between now and your next registration. And, of course, if you passed the exam but your registration has lapsed, you will need to take the SIE and the new top-off for that qualification before being reregistered.

This is pretty much the same as it has always been, except you would be taking two exams instead of one. In fact, the exams are designed to take the same total time as the previous versions. For example, the SIE and Series 7 top-off exam take the same amount of time as the previous Series 7 exam.

For member firms, the cost of the top-off exams is less than the previous exams because the content was shifted to the SIE. So, if an individual has passed the SIE prior to joining a firm, it is a good indication that this person already has the basic aptitude and wherewithal to pass a top-off exam. The cost of getting that individual registered is reduced because they paid out-of-pocket for the SIE, which will likely help make a candidate more attractive to a firm.

The Securities Industry Essentials (SIE) Exam is designed to assess your knowledge of the securities industry. It ensures that people entering the industry are qualified and knowledgeable for the work they are doing. It streamlines the previous initial qualification exams into a single test, supplemented by "top-off" qualification exams.

If you want to be registered to work in a securities business, you must pass the SIE and the appropriate qualification exam for the type of securities work you'll be doing. If you already took one of the old exams and your license lapsed—assuming two years have passed since you were last registered—you have to retake the Series 7. You need to retake the SIE only if four years have elapsed since you last passed it or were last registered.

The overall content covered over the two tests—the SIE and the Series 7 top-off exam—will be nearly identical to the previous Series 7.

FINRA does not share the SIE pass rates. However, various test prep companies state that around 25-27% of candidates fail the exam on the first try. If you fail and want to retake the exam, the wait time is 30 days for the first and second attempts, then six months if you fail the third attempt.

If you were already sponsored to take one of the qualification exams, go for it. These changes won't impact you at all. If you expect to be sponsored in the future, the overall content you need to master won’t change even though you have to do it in two chunks. If, however, you are not currently sponsored or in the industry, the SIE will open the door for you to start down the path of a financial career without having to associate with a member firm first. This change gives you a choice you didn't have before.

Exam Information

An exam proctor will begin reading exam instructions approximately 15 minutes before the exam start time. Students must be in the exam room with their exam at this time. If taking the exam on a laptop, it must be booted up and have passed the security check. Hand writers must not have a laptop with them in an exam room, unless otherwise allowed according to the professor’s instructions. A student entering the exam room after the proctor begins reading instructions will not receive additional time for booting up their laptop, passing the security check, and/or reading exam instructions.

When instructed by the proctor, write your exam number on the cover page of your exam, bluebooks, and any scratch paper you turn in as part of your exam. Handwritten exam answers must be written in blue books in blue or black ink. Number the bluebooks you use (1 of 1, 1 of 2, 2 of 2, etc.). Proctors will allow time to read the professor’s instructions. Other than counting the number of pages of the exam, students are not permitted to turn the page of an exam past the instructions page until the proctor instructs them to do so.

When taking a closed-book exam, no books, outlines, book bags, purses, or scratch paper (other than the scratch paper provided) may be at your seat during the exam. These items must be left outside of the exam room or in the front or sides of the exam room. Students may not begin to write anything, including on scratch paper, before the proctor begins a closed-book exam.

Students taking in-class exams are prohibited from having any electronic communication device, other than a laptop as allowed per the professor's instructions, during the exam. Cell phones and smart watches must be turned off during the exam and placed in a bag or backpack. Violations of this rule may be considered an Honor Code violation. A clock in each exam room will be the official timekeeper for the exam.

Non-alcoholic beverages are permitted in exam rooms; however, the container must have a lid.

After the exam instructions have been read and the exam begins, the proctor will remain in the room. Any student who has a question or problem during an exam should see the proctor.

Students may use the restroom or take a break during an exam. However, all exam materials must be left in the exam room and no additional time will be given. Students must sign in and out at the front of the room with the proctor.

Evident In Its Recent Earnings That Synopsys Reaping The Rewards Of Its Long-Term AI Investments

As I’ve written about recently, for years Synopsys has been using AI to push the envelope on the electronic design automation (EDA) software that makes today’s semiconductors possible. Now its latest quarterly numbers are out, and if anything I’m even more impressed by what the company is doing and the impact it’s having in the industry.

Synopsys CEO Aart de Geus at the 2023 SNUG Silicon Valley conferen

At a moment when lots of companies are shaky because of broader economic conditions—and when the chip industry is facing lower demand—Synopsys’ numbers are moving up and to the right in every important area. Sure, some of this have to do with the offset between designing chips and building and inventorying them, but it’s still impressive.

The latest results blew past previous guidance, the company hit another record for quarterly revenue, operating margin is up, EPS is up and the company raised its guidance for annual revenue. It’s all a testament to strong execution of its “Smart Everything” strategy that Synopsys launched more than a decade ago.

After the earnings call, I had a chance to talk with CEO Aart de Geus and CFO Shelagh Glaser to get the Synopsys perspective on what’s happening at an interesting time for AI and the tech landscape as a whole. In this piece, I’ll share some of the highlights of that conversation and where they see things heading in the months and years to come. Let’s dig in.

Synopsys beats guidance for revenue, EPS and margins

First, the numbers. Quarterly revenue of $1.395 billion was above the high end of guidance, as was non–GAAP EPS of $2.54. The company generated $703 million in quarterly operating cash flow, and its non-cancelable backlog rose to $7.3 billion.

Given how it’s firing on all cylinders, the company now expects revenue for the full year to be about $5.8 billion, or 14 to 15% higher than its $5.08 billion of revenue in fiscal 2022. In line with that, it expects non-GAAP EPS to grow 21 or 22% year over year, and it projects an even bigger improvement in non-GAAP operating margin—150 basis points total—than its previous guidance.

That’s what I’d call a great quarter: top-line growth, bottom-line growth, higher guidance for the year. And from talking with Glaser, it’s very clear that Synopsys is serious about continuing to improve margins, both short- and long-term. By the way, the company also has plenty of cash and almost no debt.

The numbers are even more impressive when you consider the volatility of the market that Synopsys operates in. Demand for semiconductors has been down, especially for the chips that go into consumer products. But Synopsys says that its customers continue to invest in R&D for new chips so they can take advantage of opportunities when demand does pick up again. In de Geus’ words, for the chipmakers, “The worst is to miss an upturn, because that's where most of the money is made.”

Leadership in AI helps Synopsys navigate a turbulent market

Synopsys is able to deliver such strong results because it’s in the right market space with the right technology—and AI is at the heart of that. “I think there has been great sensitization in the last few months around the whole notion of AI,” de Geus told me. “And you know, this is not new to us, because we had predicted the world was going to go to ‘smart everything’ about 12 years ago and built in that direction.”

Right now, generative AI like ChatGPT is getting most of the attention in the press, but Synopsys has already spent many years using machine learning (ML), big data and different types of AI to help develop and debug chips. As covered in my earlier post, its recent announcement of the Synopsys.ai platform means that the company is now applying AI to the entire EDA stack: design, verification, test and manufacturing—even for analog chips.

How’s that approach working? In a word, great. Nine of the top 10 semiconductor companies are already using AI-driven tools from Synopsys, and the uptake for these tools is only picking up pace. It started in mid-2021, when Samsung announced it had achieved the first AI-driven commercial tape-out in the world by using Synopsys’ DSO.ai. (DSO stands for “Design Space Optimization.”) By the end of 2022, Synopsys customers had already achieved 100 AI-driven tape-outs, and when I talked to de Geus in the past two weeks, he told me that it’s now “well over 200 tape-outs.”

To pick one example out of the many design wins Synopsys achieved in the past quarter, the company is now collaborating with TSMC to deliver EDA flows for the foundry giant’s most advanced 2nm process node. Renesas achieved up to 10X improvement in reducing functional coverage holes and up to a 30 percent increase in verification productivity.

Just think about the demands of that in terms of design complexity and zero tolerance for error.

The role of hyperscalers and generative AI

While he didn’t name specific companies, de Geus did verify that the list of his customers using AI-driven tools includes not only pure-play chipmakers, but also hyperscalers. This makes sense when you consider that about 45% of Synopsys’ business comes from what de Geus calls “systems companies,” meaning companies that intersect both hardware and software. This includes big cloud providers, car makers and others that are massive users of computing power and that have particular needs for operating at lower power consumption.

For example, think about how much onboard computing power will be needed by the end of this decade for fully autonomous cars—and yet all that computing power must still be delivered at the lowest possible level of energy consumption. As de Geus said, “If [chips] go into a car, they also better be as low-power as possible, because every 100 watts that you use in compute essentially takes away 10 to 15 miles of distance that you can drive on the battery.”

To address these needs, generative AI of the type used in ChatGPT isn’t yet ready to contribute to EDA processes. “Generative AI has fantastic results” in other contexts, de Geus told me, “but its results can have imperfections. In what we do, there's zero room for that. No, we are a company that has to deliver 99.99999—you know the number of nines can never be enough.” This is so because even the slightest error in a chip design can have huge consequences in terms of efficiency, yield, time-to-market and so on. “So therein lies a very profound distinction between the level of precision that our AI has to have for these designs versus these more search-type AI capabilities.”

Mind you, de Geus’ enthusiasm for generative AI came through loud and clear. “I think it's fantastic, what's happening” with generative AI, he said, “and this will impact the world massively.” In the longer term, Synopsys president and COO Sassine Ghazi believes that although these are early days of research and development, we believe generative AI is at an inflection point and a game changing technology that will offer significant opportunities for EDA applications.

Meanwhile, Synopsys engineers are exploring how cutting-edge large language models (LLMs) of the type used by ChatGPT can help streamline internal processes and augment existing solutions. According to Ghazi, “Synopsys pioneered AI-Driven chip design and this is the only the beginning of our AI journey to deliver productivity breakthroughs for customers.”

If you want to know more about the AI journey Synopsys has been on for the past several years, I recommend a fascinating post the company published after its recent SNUG conference, where Synopsys.ai took center stage. At the conference, Ghazi celebrated the crucial work done by Synopsys engineers who were inspired by the 2016 and 2017 victories of Google’s AI-driven AlphaGo over masters of the ancient game of Go. Those engineers began to dig into the ways that AlphaGo’s reinforcement learning (RL) techniques might be applied to EDA. What started as merely an idea then quickly became an MVP, and is now being used to design some of the world’s most complex multi-die architectures.

While generative AI will definitely have a role in the future of EDA—and Synopsys is bullish about taking a leadership role there as well—the company’s existing AI tools are providing big improvements in productivity and speed for chipmakers in the here-and-now.

The future of EDA is “Smart, Secure and Safe”

For de Geus and his team, the mission is broader than just using more AI to speed up and smooth out EDA. In his earnings report and again in his call with me, the CEO reiterated the need for Synopsys to help deliver technology that is smart, secure and safe.

The “smart” part gets harder all the time as companies demand more from chips: greater speed, more sophistication, higher performance-per-watt and so on. Besides the automotive example mentioned above, this certainly applies to things like AI-driven search, which requires several times as much computing power as traditional text search. Other chips used for AI functions are similarly compute-hungry.

De Geus made the point that Synopsys itself is adding to this demand. “We are using AI, very advanced AI, now ourselves to help our customers design super advanced chips,” he said. He compared it to the famous M. C. Escher picture of two hands drawing each other, adding that “I've always loved that representation because we are in the midst of that.”

He also believes that safety and security are “increasingly, jointly important” alongside smarts. This is so, he told me, because “the very complex system, if it’s not secure—there are enormous dangers in that.” He added that “these dangers get aggravated if they touch human life in any form.” It’s not hard to come up with contexts—cars, medical devices, navigation systems and so on—where any of us would insist on super-high safety and security.

For customers looking to bolster security and safety, de Geus said that Synopsys helps “by virtue of putting mechanism in chips that help encrypt the data, provide root of trust, a unique identification, et cetera. And that's built into the IP and the design flows.”

For de Geus, all these considerations are “interwoven and looped, and the really fantastic thing for us is we're literally in the middle of many of these loops” of design, AI utilization and so on. In his view, that gives Synopsys lots of room to run. As he put it, “The roadmap of optimizing, automating and generative AI use cases is wide open to deliver productivity breakthroughs for years to come.”

The future of AI in EDA

As he answered a question on the earnings call, de Geus summed up his business philosophy when he said, “Whenever the world changes, there's opportunity.” I found that telling and ironic, given that is where technology industry analysts grow, when there’s chance.

Synopsys has certainly been following that path since it launched its Smart Everything strategy a dozen years ago, and especially since it started going deep into RL and other AI techniques around 2017. What once sounded like science fiction is now penetrating deeper and deeper into every part of the creation process for semiconductors, from the early stages of design to the final steps of manufacturing.

I agree with de Geus that Synopsys’ opportunities in this space are diverse and open-ended. Better, the company has shown year after year that it can take good ideas and quickly turn them into real-world engineering that addresses customers’ challenges. The combination of strategy and execution has really paid off for them, and I expect that to continue.

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