Top 12 Audit CPA Exam Tips

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The company was losing sales when its popular products weren't in stock so it stopped using static forecasts to anticipate demand.
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Brian Kalish began working this year with a spirits company whose products were so popular it periodically underestimated demand and lost sales from a lack of inventory.
"They had no stranded inventory," Kalish, a financial planning and analysis (FP&A) consultant, told CFO Dive last week. "They sold everything they could make."
Kalish said the company was on the classic Dec. 31 calendar-year close. "They were forecasting to the wall," he said. "They went into the budgeting process in late September, early October, to put together the budget, plan and forecast, but they weren't really getting a lot out of it. It was just more variance as they went through the year."
Absent accurate forecasts, the company could never be sure it would have enough product available to meet demand, he said.
"They were basically looking over what had happened the last 12 months, [made] a best-guess growth estimate, and assumed that’s how they were going to do it," Kalish said. “And it wasn’t bad. But the problem was stock-out. All of a sudden, orders were coming in and they just couldn't fill them as efficiently.”
His prescription: Replace their static, 12-month forecast with a rolling 12-month forecast, updated quarterly.
Longer Shelf Life
A rolling forecast covers a designated period of time — four months, a year, 18 months, whatever makes sense for your organization and industry — and is updated at regular intervals. As you update your forecast with the latest monthly or quarterly data, the data from the earliest month or quarter of your time period falls away, giving you a continuously changing forecast of your company's financial condition.
"By going to a rolling forecast, it gave them a much better idea, not only because they could see their internal information but because we structured it so they could start bringing third-party information in there," Kalish said. "All of a sudden, you can start seeing ramp-up."
The transition has been easier than it might have been, he said, because the company was ready to make a big move. "To make any of this work, you have to have four pillars: culture, process, people and technology," he said. "They wanted to go from having pretty immature to world-class analytics, so that's a beautiful situation to walk into. It's not a question of convincing someone."
The company is 25 years old, sells globally, and its finance function used Excel and an enterprise resource planning (ERP) platform. After conducting an audit to identify the tools and processes the finance operation was using, Kalish changed the company's architecture on the data analytics side and brought in a cloud-based tool for forecast planning and budgeting.
"What you don't want to do is what we call a lift and shift, which would be taking the [Excel] process and doing it in [a cloud] environment, because then you're missing 95% of the advantage of bringing on the new technology," he said.
Go for Small Wins
Kalish said it's unnecessary for a company to transition its entire forecasting process to a rolling system at once, especially if you're a larger company with multiple lines of business. In such cases, it can make better sense to pick a discrete line of business and forecast just that part on a rolling basis.
"It's always a challenge if you try to do something enterprise-wide, so I always argue, make little bets and wins and let them build, so there's nothing stopping you from doing it in parallel," he said.
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A few days ago the classic debate over who is the world's capital of Fintech again hit the Twitterverse as it does periodically.
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Two of my friends got into it in a jovial manner, but it belies a continued debate that has been going on for the better part of a decade now. Even PM Boris Johnson got into the debate back in 2014-2015 saying London had become a true "world centre of Fintech". London has given birth to some very impressive Fintech's and the Mayor of London's unfailing support (both in the guise of Johnson and Sadiq Khan) has been instrumental in the city's strong Fintech culture. But how might we measure that innovation, that success in order to benchmark the world's #1 Fintech city?

In terms of metrics, while the term Fintech predates the heady 2010-2020 decade of fintech, I'm going to limit this debate to the last decade, mainly on the basis of the incredible growth in household fintech names, venture investment and impact on the economy at large. Now, I recognize that I'm not the first to embark on this endeavour. Indeed, Crunchbase published their own ranking of fintech ecosystems in December 2019, as the first of it's kind identifying what they thought were the most innovative Fintech cities and unsurprisingly they had SFO beating out London and New York.
"The report, which evaluates 230+ cities and 65 countries, is designed to highlight opportunities and drive transparency across the ecosystem. The San Francisco Bay Area, London, New York, Singapore City, and Sao Paulo round out the top 5."
Introducing the World’s First Global Ranking of Fintech Ecosystems
Crunchbase, December 4 2019
Immediately what stood out to me was that this was a very Westernized view of Fintech. In China, according to research by both EY and Statista, fintech adoption rates peaked at 87 percent of the population in 2019 and were as high as 92 percent for certain segments of the market. Whereas, the UK trailed at 71 percent of the population and the USA didn't even reach the 50 percent mark. While consumer fintech adoption is just one measure, it's very clear that fintech has affected far more citizens day-to-day in China and India than it has in the United States or the broader UK outside of London. Lack of regulatory flexibility and incumbent lobbying of government administration has worked effectively in the US at slowing down consumer-level adoption in respect to fintech modality and brands. In the US it is a fight to disrupt, in China the disruption is embraced.

Research conducted by Cambridge University, Zhejiang University (Academy of Internet Finance), and Sinai Labs came to a very different conclusion to the CrunchBase ranking where 4 of the top 7 Fintech cities in the world are in China!

While jobs created or VC dollars invested are great metrics, we could argue that the best fintech cities in the world must generate adoption of fintech across the broader population, and as a result, create demand for fintech services resulting in the growth of fintech companies, possibly unicorns. Thus, while I'm tempted to do a top 100 cities in Fintech, let's cover off the top 17 using the following metrics as a meld of previous rankings and available data:

Country-level consumer adoption - how can you call yourself a fintech city if your citizens aren't adopting fintech in their daily lives?
Venture capital investment over the last five years - investors need to see the city as attractive also, and continued investment sees an argument that both growth and ROI exists (we could have also measured successful exits I guess)
Unicorns born from the city, and value of - number of unicorns and aggregate valuations (at last round). A full list can be found here

For level setting, the largest privately owned company in the world is Ant Financial worth $150 Billion at the last valuation, and of the top 10 privately owned unicorns globally, 5 live in the US and 5 in China (based on 2018/2019 figures).
The top 17 Fintech Cities in the World (ranked)

By comparing citizen adoption, the number of unicorns produced and their aggregate value, along with overall fintech funding by VCs we get a very different picture of both the US (Crunchbase) and China (Cambridge) studies, as you'd expect. Interestingly enough, New York, Hong Kong and Singapore all fare rather poorly, in fact, Atlanta beats out NYC in pure Unicorn producing power. I'm sure that this will create some lively debate, but these are simple rankings based on an aggregate of primary factors. We certainly could add more data points, such as the number of people employed by city in Fintech, if we could get those data points.
The World's Fintech Unicorns (as of 2019)

This is as an exhaustive list as I'll think you'll find. If I've missed any please let me know, and if you want the spreadsheet/raw data PM me.
As it stands, it's pretty clear that neither London nor NYC or San Francisco have a claim on being the centre of fintech globally. In fact, the number of cities that don't align with traditional financial centres says a great deal about Fintech disruption itself - it's clear that old skills in finance have not translated into centres of fintech competency writ large.
Shenzhen Vying for the Most Innovative City in the World!

Image: It's very common to see rooftop solar deployed throughout Shenzhen city (credit: Author)
Ranked number 6 globally and #4 in China is the city that lies on the border between Mainland China and Hong Kong (SAR). With a population of just over 12 million, Shenzhen is ranked as the third most valuable economy in China (by GDP contribution) and first in terms of GDP per capita. Recently Jim Marous and I had the pleasure of visiting Shenzhen at the invitation of one of the most innovative companies in the world, Huawei. Today Shenzhen produces over half of the international patent applications coming out of China.

Image: Jim and I exploring a Huawei shipping container data centre (credit: Author)
Already, Shenzhen is home to some of the most innovative companies in the world including Huawei, Tencent, DJI and others. It's a young city. Just 35 years ago it was basically a fishing village with a population of around 30,000, but when Deng Xiopeng designated it as the country's first Special Economic Zone, the city boomed.
Today 90% of consumer electronics are built or have components shipped from Shenzhen. If Silicon Valley is the heart of the world's software industry, Shenzhen is it's hardware-based cousin. More than half of all international patents filled out of China are born in Shenzhen.

Image: The Huawei R&D campus houses 40,000 employees and puts all but perhaps the Apple campus to shame in style and grandeur (Credit: Author)
The Huawei R&D campus is modelled after European cities and is split into two areas, research and manufacturing. The research city is modelled after 7 different European cities covering almost 4 square miles of land. In the distance, hi-rise apartments are available also built by Huawei and provided to more than a quarter of the workers as prestigious local housing. All the perks of a SV startup are here with a range of services on campus, free food, free transportation and there's even a KFC and Starbucks on the campus.
The production line is a modern engineering marvel. The day Jim Marous and I visited Huawei was running production for the P30 Pro smartphone, and every 28.5 seconds one of these top-spec phones were rolling off the production line, more than 2600 smartphones a day. On the wall were faces of employees that had improved the production line process by 1 second here, 3 seconds there. A few years ago more than 60 people were required to run one production line in the factory here, but today it's typically 12 or 13. But rather than fear innovation as a mechanism for disruption, the entire company and indeed the entire city, seems to be energized by the possibilities of the future.
I first visited Shenzhen in 2001. The city has more than doubled in size since that time, but what is more inspirational is the innovation at the heart of Shenzhen's success. It's easy to see why much of the west is wary of companies like Huawei and Tencent. Their ability to innovate is powered by a culture that the West hasn't see broadly in more than 50 years. It's also why cities like Shenzhen and Hangzhou is where the Fintech Unicorn's of this decade are being born.

In the Huaqiangbei electronics market area of Shenzhen (local Westerners call it HQB), you see first hand the affluence, innovation and integrated nature of technology in this city. Every store you go to accepts facial recognition payments, robots greet potential shoppers and store clerks have hand-held translation units to help you out immediately despite language gaps. If you want to see first hand a real city of the future, this is where you should look for inspiration. Not London or San Francisco. This is a smart city where every citizen is living the future!
© AP
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As expected, RBI has kept the repo rates unchanged at 5.15% while maintaining an accommodative stance.
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Though a rate cut would have been welcomed by the real estate sector as a sentiment-boosting factor, a meagre change in repo rates would have done little to significantly boost consumer sentiments. 
As such, previous rate cuts did prompt some banks to lower their interest rates in the recent past - but that had no significant impact on residential real estate sales.
However, in a major relief to the real estate sector and further complementing many of the previous initiatives by the government in 2019, RBI has decided to extend the restructuring of project loans by a year. 
Loans for projects that have been delayed for reasons beyond the control of their promoters have been extended by another one year without downgrading the asset classification. 
This aligns with the treatment accorded to other project loans for the non-infrastructure sector.
This is a big move and will bring the much-needed relief to the cash-starved real estate sector - and to both developers and the HFCs from the liquidity perspective. 
It will help ease out the time for maintaining and managing cash flows for cash-strapped developers and help them to completing several stuck projects. 
That said, it will not address the other main issue prevailing in the real estate sector – that of continuing low demand.
 
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Smart investment on the planning side can help retailers better align forecasts with actual sales.
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Last year was a tough one for Barneys. The luxury retailer shuttered 15 of its 22 stores and turned the 2019 holiday season into a fire sale as it prepared to close its signature store in Manhattan. Other major retailers struggled, too, with at least 16 of them filing for Chapter 11 bankruptcy. 
The rise of online sales, now more than 11% of commerce in the Unites States, is a factor, and so are tariffs. Some of last year’s most popular goods, including electronics, shoes, and hats, were affected by the trade standoff with China.  
But retailers have done themselves no favors by missing the mark on the forecasting side. The stock price of Macy's, the largest department store company in the U.S., plunged 13% to a 9-year low of $15.82 in the second quarter of last year in part because of weak forecasting.
"A fashion miss in our key women's sportswear private brands [and] slow sell-through of warm weather apparel" forced the company to take markdowns to clear excess inventory, said Jeff Gennette, the company's chairman and CEO.
Anticipating demand is always a guessing game, but many retailers make unforced errors by clinging to inadequate forecasting processes, financial planning and analysis (FP&A) consultants told CFO Dive. 
"Retail forecasting is a little bit of science and a little bit of art," Carlos Castelán, founder and managing director of retail consultant the Navio Group, told CFO Dive. "We think of sales as an outcome of the transaction but there are a lot of steps ahead of that. Having a sense of, more broadly, the larger sales funnel can greatly improve your forecasting."
Here are three common forecasting mistakes retailers are making.
Running into the Forecasting Wall
Many retailers think they're engaging in dynamic forecasting when they build in a way to make updates throughout the year, but in reality their process is static, FP&A consultants say, because what makes forecasts dynamic isn't the updating process, but the time horizon.
"One of the common mistakes CFOs are making is what we call forecasting to the wall," Steve Player, managing director of the Player Group, told CFO Dive. "Large companies will many times prepare a forecast, but if you look at what they’re really doing, they’re preparing a descending forecast.
A descending forecast, or what planning specialists call forecasting to the wall, is when CFOs create a six-, 12- or 18-month plan and make subsequent updates as new data come in, but the time horizon remains unchanged. 
In a common scenario, the CFO will create a 12-month forecast starting in January, make quarterly updates, and leave the time horizon fixed at December 31. As a result, the company forecasts for shorter and shorter increments. 
"The first one is 12 months, the second's nine months, the third is six months and the fourth one's three months and then they pop out another year," said Player. "All they're really doing in that kind of situation is updating their projection to validate their budget target."
A better approach is to use a rolling forecast, in which the time horizon gets pushed out by the same number of weeks or months as the update. If you're using a 12-month forecast, in addition to updating your estimates every month or every quarter with new data, you push out the time horizon by another month or another quarter and remove the corresponding trailing time period. That way, the forecast remains 12 months, but you never reach the endpoint, or wall.  
Brian Kalish, an FP&A consultant whose clients include retail companies, said the rolling time horizon enables executives to make decisions based on market dynamics rather than an artificial target. 
"If your sales compensation is based on hitting your numbers for December 31, your behavior will be very different than if you're ignoring that deadline," Kalish told CFO Dive. "The business is going to exist on January 1, so what happens is, you start making economically suboptimal decisions to hit artificial targets."
For the past year, Kalish has been helping a spirits company move from a static to a rolling forecast to regain sales it was losing because of chronic inventory shortages. 
"They were basically looking over what had happened the last 12 months, [made] a best-guess growth estimate, and assumed that's how they were going to do it," Kalish said. "And it wasn’t bad. But the problem was stock-out. All of a sudden, orders were coming in and they just couldn't fill them as efficiently."
By going to a rolling forecast, he said, "it gave them a much better idea, not only because they could see their internal information, but because we structured it so they could start bringing third-party information in there. All of a sudden, you can start seeing ramp-up."
Conflicts of Interest
Whether you're doing static or rolling forecasts, unless you change the incentive structure in your annual budgeting process, you're almost guaranteeing inaccuracy in inventory levels, and by extension sales, consultants say. This is because most incentive structures are built around sales targets, not accuracy. 
"Budgets are a little bit of a negotiation process," Karen Sedatole, professor of accounting at Emory University, told CFO Dive.
"The sales team negotiates lower budgets than what they think they can meet, because they want to make sure they meet that budget by the end of the year because they want to get their bonus. If I think I can sell 100 units, when I'm negotiating my budget targets with people higher up in the organization, I negotiate a target of 90, because I think I can sell 100. That way I make sure I meet my budget by the end of the year."
Player calls this practice a monstrous conflict of interest because it virtually guarantees sales estimates will be low-balled in the initial forecast. 
"The budget manager's not going to negotiate stretch goals or outstanding performance because he's going to be judged against that — and his bonus is going to be based on that —  so now his incentive is to give a sandbag budget, with minimal acceptable returns," he said. "If you're designing an internal control system, the first thing you try to avoid are conflicts of interest, and here the budget puts one right in the middle of its mechanism."
This sandbagging is a recipe for inventory shortages, and therefore lost sales, because once the budget's approved and the forecast set for the coming year, production planners set in motion a process for producing an inadequate amount of inventory, which can lead to shortages at crucial points in the market cycle. 
A rolling forecast can address some of the problems of sandbagging, but it doesn't solve the root problem. It can help ease the inventory mismatch by giving executives a chance to revamp the demand estimate at regular intervals as data comes in showing sales beating forecasts, or vice versa. But making changes in production capacity in the middle of the year is an expensive way to solve a problem. 
"Is there going to have to be some kind of capital expenditure to make another production line live to meet demand?" said Kalish. "Do we think we're actually going to have to build a new factory? Do we go out and borrow money? How does that affect our credit rating? Are we going to spend the company's resources in these ways or are there better things to do instead of building another factory? It's not the most efficient in the long run."
The root solution is to remove the conflict of interest in the first place by aiming incentives at forecasting accuracy, not sales targets, but consultants say most companies are unlikely to change their practices any time soon. 
"Letting the bonus be dependent on forecast accuracy sounds like a great idea, but probably fewer than 20% of companies do that," said Sedatole. "The reason is, we want sales people selling. So, we want really high-powered incentives for them to sell."
Sedatole said she's working with a company that sells chemical products that incorporated accuracy into its incentive structure but it was a small percentage of the sales bonus.
"When I talk to the sales managers, they say, 'We don't want to pay attention to that,'" she said. "'We just want to pay attention to completely meeting the sales target.' So, although they had it in principle, it really wasn’t anything that's effective."
Real-Time Data Sharing
One of the most straight-forward ways to improve forecasting accuracy is by communicating sales data to executives in as close to real-time as possible. By doing that, finance, sales, production, marketing and other business operations can track performance as it happens and make real-time adjustments. The more the forecast is updated using data with minimal lag, the more accurate the forecast becomes over time. 
"Communications is one of the biggest forecasting problems companies face," Kalish said. "What happens is, the information sits in silos. You’re just not leveraging it."
The most practical way to speed communication is to move from on-premise software to a cloud environment, because the cloud environment enables data to come in as it's generated and lets executives access it when and where they want.   
"If you're in spreadsheets, get out of them," said Kalish. "That's what's killing people. There's just so much technology out there that can really help support the business."
Castelán of the Navio Group pointed to the success of Lululemon in leveraging real-time data. It was one of the first retailers to use radio-frequency identification (RFID) technology to feed sales and inventory data from all of its locations into a central hub, enabling it to manage inventory across its operations in the most efficient way possible. If a consumer in Chicago buys an item online, that item might come from a store with excess stock in South Carolina as opposed to a central warehouse. 
"That helps from a forecasting perspective, because you're able to use all of your inventory across the network, which increases your inventory churn as well," he said.
Having real-time sales communication among executives is especially important in retail sectors that move too quickly to make year-ahead sales forecasting practical. Kalish pointed to the cosmetic sector as a good example. 
"A perfume company's horizon might only be one year, because [product designers] go to the Paris show, find out what's in fashion, then make it," he said. "There's no way to predict what that's going to be, so they just have to be really good at being reactive." 
Another example are smart phone cases. "The dimensions are changing all the time, and they can't be off at all," Kalish said. "They have to be perfect. So, they don't try to predict how Apple or Samsung is going to change the width and the length of the phone; they just want to be really good at changing their production line fast." And that requires instant access to real-time information.
A Better Forecast
There's a saying among FP&A specialists that all forecasting models are wrong, but some are useful. If you want to move your model into the useful category, here’s how to start: transition to a rolling forecast if you're not already doing that, remove bias in your budget by aiming incentives at forecast accuracy rather than sales targets, and move to a cloud-based budgeting environment to generate, and then apply, actual sales data as close to real-time as possible. That way, the forecast can be tweaked before inventory problems affect sales.
If you make these changes, your forecasts likely will still be wrong, but they might lead your company to better performance.  
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Real estate cannot remain a neglected stepchild - it must become the apple of the government's eye.
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Union Budget 2020-21's almost pointed negligence of the real estate sector was most puzzling - especially since the previous budget had envisaged an ambitious blueprint for the country's economic future. For realizing the vision of making India a USD 5 trillion economy by FY 2024-25, the development and growth of its real estate sector is imperative. Across developing and developed economies, real estate and economic growth are inseparable concepts.
Real estate is a key driver of economic growth, and by laying the groundwork of making it more organised and transparent, the government has already made it a more secure and attractive investment environment. The fact that the latest budget gave no more than a cursory glance at real estate is a missed opportunity to build further on this groundwork. To propel the Indian economy into the top league of global economies, the growth engine of real estate cannot be ignored.
Realty’s Contribution to GDP to Double
Despite global headwinds and slow economic growth in the country, the India Brand Equity Foundation expects India's real estate sector to grow to a market size of USD 1 trillion by 2030. It is also likely to contribute 14% of the country’s GDP by 2025 - almost double its current contribution of 7-8%.
Over the years, real estate growth - particularly in housing - has been crucial in driving the Indian economy. Regulatory reforms such as RERA, GST and IBC and relaxation in foreign direct investment have already made the industry more transparent and credible, leading to increased end-user demand.
It was expected that Union Budget 2020-21 would aim to keep this momentum going and thereby emphasise economic growth. To achieve this, radical changes in the taxation system and as well as regulatory policies are of paramount importance.
Infrastructure Creation - Driving Growth
While the latest Union Budget did not provide any real boosts to real estate other than in terms of affordable housing, it did continue to focus on infrastructure. Real estate development goes hand-in-hand with infrastructure as the latter opens up peripheral areas and creates new avenues of growth. Earlier, the government had already allocated INR 100 lakh crores for infrastructure investments to improve transport efficiency over the next five years. Multi-modal infrastructure development such as roads, rail and metro improves living conditions and spurs demand for residential, commercial, retail and warehousing real estate.
Supporting Job Creation
Union Budget 2020-21 failed to give clarity on the deployment of the previously-announced INR 25000 Cr alternate investment fund. Completing and handing over these stuck projects will increase buyer and investor confidence and help usher in a strong revival for the housing sector. Improved sales will lead to a strengthened housing supply pipeline and create jobs across the entire white-to-blue-collar segments of real estate development.
This factor cannot be ignored. After agriculture and manufacturing, the real estate sector has the most potential for large-scale job creation. Associated with over 200 allied industries including cement, steel and sand, housing development has a multiplier effect on several allied sectors.
According to the National Skill Development Council, there is a requirement of 109.73 million skilled manpower by 2022 in 24 key sectors. The building, construction and real estate sector alone is expected to generate 76.55 million jobs by 2022. The government's mega initiative of 'Housing for All by 2022' itself promises to be a major employment generator - and, by direct implication, an overall economic growth dynamo.
In the second phase of PMAY-G, during 2019-20 to 2021-22, 1.95 crore houses are expected to be provided to eligible beneficiaries. This effort alone can and will create large-scale employment for skilled and unskilled labourers.
The Need for Investor Participation
Major reforms such as GST, RERA, Insolvency and Bankruptcy Code and Benami Property Transaction Act have had a lasting impact on the real estate sector. Despite the initial churn and pain, they have increased financial discipline and a healthier ecosystem. By instilling renewed confidence in home buyers and domestic investors, these landmark reforms have improved the perception for India as a global hub for investments.
As per ANAROCK data, private equity investments in India’s real estate sector clocked in at over USD 5 billion in 2019, of which commercial segment comprised the lion’s share at over USD 3.3 bn, followed by retail sector with USD 970 mn and residential of USD 395 mn. A large chunk of these investments came from foreign private equity funds like Blackstone, Hines, Ascendas and Brookefield.
However, housing remains an unpalatable investment category for smaller domestic investors. The Union Budget was an ideal platform from which to announce initiatives to boost private investor participation. Currently, India's housing sector is riding almost exclusively on end-user sales, which are not enough to revive residential real estate and its related benefits of furthering the Housing for All by 2022 goal and generating increased employment.
As the second-largest employer and a major contributor to the country’s GDP, the real estate industry is one of the Indian economy's strongest pillars. It cannot remain a neglected stepchild - it must become the apple of the government's eye. A convincing revival of the Indian real estate sector is essential for the economy to move out of its current slow phase and achieve the mammoth targets - Housing for All by 2022 and making India a $5 trillion economy by FY 2024-25.
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