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Facebook earns close to 99% of its revenue by advertising. Marketers pay for ad products based on the number of impressions delivered or the number of clicks done by users. The business continues to impress me given that my friends, family and colleagues are so hooked to the platform and most of them (albeit to varying degrees) can’t wait to give the lurking marketers access to their personal information at the expense of getting connected and endorsed (for posting their views/sharing pics etc etc you know it) with their network. I will cast aside my prejudice and value Facebook in this post.
First some facts
As of Sept’19, the platform reported to have 2.4 billion monthly active users world wide, which is 32% of the world population. FB earned an average of $28 per user over the the last 12 months (as of Sept’19). This translates to 4x growth in per user revenue since 2013 and ~3x since 2014. The platform draws $130 per user from US and Canada, followed by $41 per user from Europe (which includes Russia and Turkey), $12 from Asia and $8 from Rest of the world (which includes Africa, Latin America and Middle East). Although, US and Canada have the highest per user revenue, they account for only 10% of the user base.
The user base as a percentage of world population has increased from 17% in 2013, 19% in 2014 to 32% in 2019
Moreover, FB makes $11.6 as pre-tax operating profit on a revenue of $28 per user. This translates to a pre-tax operating margin of ~42% after capitalizing R&D expenses.
Valuation
Before jumping into valuation, let’s do a quick refresher on how a company is valued. Value of a firm is the present value of its projected Free Cash Flows (FCF). FCF is the the portion of net operating profit after tax that is left after meeting the firm’s reinvestment needs. So to value a firm, one needs to project operating profit (i.e. revenue x margin%) and reinvestments 5-10 years out (and discount them to present using the firm’s cost of capital).
Facebook story is that of an active user growth play. I go on to value FB under 3 scenarios using different revenue projections based on combinations of user base (as a %age of world population) and average revenue per user (ARPU). In all the 3 scenarios, I take the same margin, reinvestment cost of capital and return assumptions as follows –
Margin: I assume that the current margin will drop from 42.05% to 40% over the next 10 years. Your estimate of future margins may be higher or lower, but I believe the status quo will more or less continue which is reflected in the 2% margin drop that I have assumed.
Reinvestment: Again, I believe the existing state of operations will continue leading to the firm operating at current capital efficiency of 1.31 (i.e. FB generate $1.31 in revenue for every dollar invested) 10 years out. Capital efficiency ratio is used estimate reinvestments (Reinvestment = Change in Revenue / Cap Eff).
Cost of Capital: I have used 8.3% as the cost of capital which gradually reduces to 8% over the 10 year period.
Return on Invested Capital: Given the unwavering user engagement the platform has demonstrated, I believe that marketers will not pull out anytime soon and the platform will continue to increase the size of the digital marketing universe. The firm will continue to have competitive advantage and create value beyond year 10. With this belief, I assume an ROIC greater than the cost of capital beyond year 10.
1. Sane Scenario – I project user growth with the belief that FB’s active user base reaches 35% of the world population over the next 5 years from 32% today. This leads to the addition of 400 million new active users over the next 5 years which is under 40% of the new users addition over the last 5 years. Moreover, I make ARPU growth rate projections with the belief that ARPU will increase by ~1.75x in the next 5 years. (Overall ARPU has increased ~3x from $10 to $28 over the last 5 years). A combination of this ARPU and MAU growth (ARPU x Active Users = Revenue) leads to an implied revenue CAGR of 16% over the next 5 years, which is 40% of the growth over the last 5 years.
Using the above revenue growth (also operating margin, same capital efficiency and cost of capital) assumptions, the value of equity in common stock I estimate is $657 billion which is over 10% of its market cap as on 12/31/19. The intrinsic share value that I get is ~$225 as against its current trading price of ~$205 Model credits – Dean of Valuation Prof. Aswath Damodaran
2. Upbeat Scenario – Letting my prejudice towards the platform flow in, I project user growth with the belief that FB’s active user base reaches 40% of the world population over the next 5 years from 32% today. This leads to the addition of 790 million new active users over the next 5 years which is under 75% of the new users addition over the last 5 years. Moreover, I make ARPU growth rate projections with the belief that ARPU will increase by ~2x in the next 5 years. (Overall ARPU has increased ~3x from $10 to $28 over the last 5 years). A combination of this ARPU and MAU growth leads to an implied revenue CAGR of 20% over the next 5 years, which is half of the growth over the last 5 years.
Using the above revenue growth projections, the value of equity in common stock I estimate is ~$722 billion which is over 20% of its market cap as on 12/31/19. The intrinsic share value that I get is ~$247 as against its current trading price of ~$205
3. Downbeat Scenario – In the event that FB’s active user base increases at the same rate as the world population i.e. active user base remains at 32% over the next 5 years and ARPU grows ~1.6x, this yields a revenue CAGR of 12 % over the next 5 years.
The value of equity in common stock I get using revenue CAGR of 12% is ~$542 million, which translates to an intrinsic share value of ~$186 making the share overvalued by 9%
Conclusion
Not letting my prejudice overpower, my story of Facebook is centered on the “Sane” scenario, which makes the platform undervalued by 10% as of this writing. For long, I have made this business earn of me as an active user of the platform, now I will be looking to own a few shares if the price offers more than 10% of the value I have estimated in my story. Your story may be more “upbeat” or “downbeat”. The value that FB offers depends upon your story.
Thank you for reading!
Gautam
Disclaimer โ Currently, I do not own any stock of this company. This analysis should not be misconstrued as a buy / sell recommendation. Readers are advised to do their own analysis. Moreover, any opinion expressed in this blog post is solely my own and does not represent views of my employer
This blog post has two sections – In the first section, we value Gruh Finance separately (before merging into Bandhan). We have analysed and valued Bandhan separately here (in our previous blog post). In the second section, we value the merged entity and estimate the value of synergy to assess if Gruh’s pricing as per the deal was justified.
1. Gruh Valuation (just prior to acquisition by Bandhan)
Loan Asset Profile
As of Jun’19, Gruh operated primarily in the rural and semi-urban areas of Gujarat and Maharashtra, which together comprised 63% of the outstanding portfolio
Period
10Y
5Y
3Y
2Y
1Y
31/3 – 30/9
Outstanding Loans CAGR
24%
20%
16%
15%
12%
5%
Although, Gruh has done well with outstanding loans demonstrating good growth over the past 10 years, but with increasing base from concentration in the West, growth rate has shown a decline as shown in table above.
As of Jun’19, GRUHโs outstanding home loans to individuals of 14,665 crore constituted 83% of the total outstanding loans. Loan Against Properties (LAP) of Rs. 1,820 crore and other loans to individuals for non residential premises (NRP) of Rs. 343 crore constituted 10% and 2% respectively of the outstanding loans. The outstanding loans to developers of Rs. 876 crore constituted the remaining 5% of outstanding loans.
Though, cumulative disbursements as at March 31, 2019 stood at Rs. 33,392 crore with a CAGR of 14% over FY14 – FY19, but the loan disbursement decreased from Rs. 5,259 Cr (in FY18) to Rs. 4,936 in (FY19) for the 1st time in this period. In FY19, Gruh disbursed home loans to 37,599 families (previous year 43,473 families) and the average home loan to individuals increased to Rs. 9.59 lakhs from Rs. 9.40 lakhs in previous year
Liability Profile
FY15
FY16
FY17
FY18
FY19
Jun-19
Outstanding borrowings
8216
10244
12018
14046
16584
18430
Banks/NHB
67%
77%
67%
55%
63%
69%
NCDs
8%
9%
20%
29%
26%
20%
Public Deposits
16%
14%
13%
10%
9%
9%
CPs
9%
0%
0%
5%
1%
2%
Commercial Paper (CP) is a short term cheap source of funds. Since the IL&FS and DHFL crisis, Gruh has reduced its reliance on CPs as a source of funding.
CAR = (Tier 1 Capital + Tier 2 Capital) / Risk Weighted Assets, where Tier 1 is the core bank capital, which comprises of equity and disclosed reserves. Tier 1 can absorb losses without requiring the bank to cease operations and Tier 2 capital on the other hand can absorb losses in the event of liquidation. (We have described CAR and how does it impact growth and valuation of an FI in our previous blog post on the analysis and valuation of Bandhan Bank).
We observe that return on equity (ROE) has decreased consistently from 31% in FY15 to 26% in FY19 (and 24% in Jun’19). Since capital comprises of equity, a CAR ratio which rises over time with decreasing return on equity denotes that the FI is not using capital effectively to grow. This is further corroborated by declining loan growth.
FY10
FY11
FY12
FY13
FY14
FY15
FY16
FY17
FY18
FY19
Jun-19
D/E
8.8
9.3
9.9
10.0
10.7
11.5
12.3
10.8
9.0
8.7
8.8
As of Jun’19, borrowings were 8.8x of equity (from highs of 12.3 in FY16), which was higher than most of its listed peers. Please note that in FIs, capital is defined as including only equity (not debt), while debt or borrowing is viewed as raw material.
Asset Quality
Non Performing Assets – An asset is marked as NPA if the interest or principal instalment is overdue for 90 days. Gruh reported NPA of 0.95% in Jun’19 up from 0.66% in Mar’19. Historically, reported NPAs have remained below 1% expect in FY10.
FY10
FY11
FY12
FY13
FY14
FY15
FY16
FY17
FY18
FY19
Jun’19
NPA
1.11%
0.82%
0.52%
0.32%
0.27%
0.28%
0.32%
0.31%
0.50%
0.66%
0.95%
Asset Liability Mismatch – We have described ALM in the blog post on Bandhan Bank’s valuation. ALMs can pose a greater threat to HFCs than to companies primarily focussed on microcredit financing since microcredit loans are relatively short term.
Gruh had no negative cumulative mismatches in the up-to one-year bucket which indicates an adequate liquidity profile
Again, we will mention that of late FIs have not been very transparent in reporting out bad loans. We can rely on some key credit indicators like NPAs, ALM, LCR etc and also reports from credit agencies to form a picture of their asset quality. An investor needs to do a very thorough analysis to assess the management quality of any company to build trust on what is being reported.
Management
As of Jun’19, promoter HDFC Bank owned 47.4% of Gruh Finance. Mr. Sudhin Choksey is the MD and he has been with the company since 1996. Gruh’s stock price traded at close to Rs. 11 towards the end of FY10 and shot up beyond Rs. 300 in FY19. EPS increased 6.5x over the same period. Over this period, Gruh has declared dividends with a payout ratio of above 30% every year. This indicates that the management has been sharing the fruits of its good performance with the shareholders. If we look closer an investor would observe that the management has rewarded itself handsomely over public shareholders. Of the 73 cr shares market float before the impending merger, 7.3% of the shares (including the effect of the two bonus issues) have been created by allotment of Employee Stock Options, which lets the management increase its shareholding at a cheaper price than the prevailing market price. Stock options are aimed at incentivizing the management to work hard towards increasing business performance. An investor notices that after the merger announcement (on 7th Jan’19) the management called for a special resolution on 22nd Apr’19 to allot 90 lacs stock options, which is 2.6x of the yearly average of allotting 34 lacs options over the last 10 years. It seems the management handsomely incentivized itself since as per the terms of the merger, Gruh shareholders were supposed to receive 568 Bandhan shares for 1000 shares of their own.
DCF Valuation of Gruh Finance (just prior to merger with Bandhan)
Value of equity is the present value of its future Free Cash Flows to Equity (FCFE). Click here to look at how we have estimated future FCFE for this financial firm and discounted them to present using Cost of Equity (COE) to arrive at the equity value.
Gruh does not look like it was priced to be a bargain. We have at arrived an intrinsic value of Rs. 80 per share as against its market price of Rs. 312 before the deal. We have outlined the assumptions and guiding principles in the exhibit below. ROE set at a mean of 25% (max 26%, min 24%) over the next 5 years and then declines to a mean of 20% (max 22.5%, min 17.5%) as the firm transitions to stable growth. 100 Monte Carlo simulation trials are run with ROE oscillating between min and max values (We would have liked to run 100x more simulations, but we have not purchased any software which lets us do that. We have used just excel’s inbuilt NORM() and RAND() functions to run 100 manual trails). We have assumed a growth in loan assets to be 12% over the next 5 years which tapers to 10% when the firm reaches stability. This may seem low, but our assumption is based on the back of Gruh’s declining growth in the last 5 years. On bumping up the growth expectations to 20% every year over the next 10 years, the intrinsic value that we get is Rs. 125 per share, which still makes it massively overpriced.
The over pricing is further corroborated by doing a reverse DCF*. We find that only 16% of Gruh’s market cap of Rs 23, 320 cr was justified by its current performance (non growth perpetuity) and the rest 84% is the value market believed that Gruh will generate from future growth. *Reverse DCF is nothing fancy – All one needs to do is take the profit after tax Rs. 468 Cr (or preferably net operating profit after tax for non financial firms) and divide it with cost of equity 12.5% (or preferably cost of capital for non financial firms). The Rs. 3,744 Cr value that you get is the value that is justified by company’s current performance assuming no growth in perpetuity. This value formed 16% of Gruh’s market cap before its merger.
Market seems to have rewarded Gruh’s good performance exorbitantly. The stock was trading ~50x earnings, which is high relative to its peers.
Interesting thing to note is that the claim of *Gruh’s ESOP holders is 2% on Gruh’s value of equity, which is much higher than the 0.14% claim of Bandhan’s ESOP holders on its value of equity. *We do not know the exercise price of the 90 lacs stock options alloted by Gruh before the run up to its merger. We have assumed that these options had the same exercise price as that of options allotted under ESOS-2015 Tranche 2
Bandhan came out with the consolidated numbers (Bandhan and Gruh combined) in its FY20-Q2 investor presentation. They have stated growth, cost and transformational synergies as the motive behind the deal besides promoter stake dilution (synergy motive of the deal posted in the snippet below). Two entities come together with the motive of synergy when it is believed they will be able to do things that they could not have done as separate entities
In this section of the blog, we will value both Bandhan and Gruh together to estimate the value of synergy for assessing if the deal was priced to be a bargain. Value of Synergy = Bandhan and Gruh valued together with updated (growth, return, etc.) parameters reflecting the benefits of synergy – (Valuation of Bandhan before the merger + Valuation of Gruh before the merger)
Value of equity is the present value of its future Free Cash Flows to Equity (FCFE). Click here to look at how we have estimated future FCFE for this financial firm and discounted them to present using Cost of Equity (COE) to arrive at the equity value.
Based on Sepโ19 data, the intrinsic value we have estimated is Rs. 415 per share based on base case assumptions outlined in the valuation exhibit above. This makes the merged entity overpriced as of this writing. (Bandhan was trading at ~Rs. 555 immediately following the merger and slid to Rs. 515 on 13th Dec).
In our valuation of Bandhan, we have considered a growth in loan assets to be 25% over the next 5 years which tapers to 20% when the firm reaches stability. We extrapolate the same growth rate to overall merged entity with the belief that Gruh will be able to expand further through Bandhan’s existing branch network (refer Synergy snippet above) and moreover Bandhan will be able to tap on Gruh’s network as well. These assumptions reflect my perception of future growth potential.
ROE is set at a mean of 23.75% (max 25%, min 22.5%) over the next 5 years and then declines to a mean of 20% (max 22.5%, min 17.5%) as the firm transitions to stable growth. 100 Monte Carlo simulation trials are run with ROE oscillating between min and max values.
On running 100 simulation trails we find that 51% of the intrinsic values lie between Rs. 409 and Rs. 439 per share, with half of the these values lying between Rs. 429 and Rs. 439. Merged entity was trading at Rs. 515 as of this writing (13th Dec, 19)
Moreover, we have estimated Rs. 1907 Cr as the value of synergy (which is under 3% of the estimated intrinsic value of the merged entity) in our base case valuation (please refer valuation exhibit). However, we see that Gruh’s pricing of Rs. 23,599 Cr. as per the deal is 2.9 times Gruh’s intrinsic value (Rs. 6,029 Cr.) combined with synergy.
We go onto run 100 simulation trails to get a range of synergy values. We observe that 65 of the trails show a positive value indicating that Gruh and Bandhan coming together will create more value than they could have as separate entities. However, 93% of those trails indicate that Gruh was acquired at a premium. (At the risk of repeating ourselves, we reiterate that we would have liked to run 100x more simulations, but we have not purchased any software which lets us do that. We have used just excel’s inbuilt NORM() and RAND() functions to run 100 manual trails)
Conclusion
Our base case valuation and the simulation trails we ran corroborated that Gruh was not priced at a bargain and Bandhan paid a high premium for the acquisition. This is not hard to conclude since the merger was priced based on a share swap and we saw in the first section of this blog post that Gruh was massively overpriced. (Again, please bear in mind that DCF is subjective and is as good as the underlying assumptions. Our assumptions are based on our perception of future growth potential, which we have outlined in the blog post above. Infact, we stretched the growth parameters in our valuation of Gruh and still found it overpriced). Moreover, the intrinsic value of the merged entity we have estimated is Rs. 415 per share based on base case assumptions. This makes the merged entity overpriced as of this writing. (Bandhan was trading at ~Rs. 555 immediately following the merger and slid to Rs. 515 on 13th Dec). Post the acquisition of Gruh, the intrinsic value of Bandhan dropped by Rs. 80 (from Rs. 495 to Rs. 415)
We do see (in 65 of the 100 simulation trails we ran) that both of the entities coming together will create more value than they could have separately. However, a great deal has to go right for Bandhan to break even on the deal.
With the acquisition of Gruh, it remains to be seen how Bandhan delivers on the growth synergies due to geographic complementarity. An investor needs to closely track the loan asset quality and also loans given to non-priority sector including exposure to Construction. Moreover, an investor needs to keep tabs on new ESOPs that may be issued to assess if the management is not overly compensating itself over common shareholders.
Thanks for reading!
Gautam
Disclaimer โ Currently, I do not own any stock of this company. This analysis should not be misconstrued as a buy / sell recommendation. Moreover, any opinion expressed in this blog post is solely my own and does not represent views of my employer.
Bandhan Bank constituted ~20% (Rs. 39,061 Cr) of the outstanding micro loan portfolio in the industry (Rs. 1,90,684 Cr), which itself formed ~25% of the total micro loan potential in the country (as of Jun’19)
In Cr.
Unless
otherwise stated
FY17
FY18
FY19
Jun’19
Sep’19 (as per investor presentation)
CAGR
(FY17-19)
Outstanding Advances (including IBPC)
โน23,642
โน32,389
โน44,776
โน45,420
โน45,927
37.6%
Microcredit %
69.6%
87.1%
84.6%
86.0%
Microcredit
โน16,457
โน28,211
โน37,889
โน39,061
51.7%
Overall outstanding advances have increased at a CAGR of ~38% over FY17 – 19. Although, this growth is commendable, but the Bank has high concentration in the East with West Bengal forming 46% of the loan book last year.
RBI has mandated Priority Sector Lending (PSL) of 40% of advances for all the Banks. For Bandhan, ~85% of the outstanding advances over FY18 and FY19 have come from PSL by issuing loans to micro customer. Bandhan was able to sell PSL certificates worth 58% and 76% of its PSL loans in FY18 and FY19 to other banks which fell short of their PSL target. These certificates are akin to social credits with no underlying risk and asset transfer. Bandhan earned 151 Cr and 309 Cr (income close to 1% of the PSLCs sold) by selling these certificates to other banks un FY18 and FY19 respectively. This looks good since with the microcredit focus, Bandhan can earn ~1% extra income on the portion of its PSL loans which it can sell as PSL certificates.
Moreover, focus on micro credit coupled with loan growth allowed Bandhan to sell loans in the form of Inter Bank Participation Certificates (IBPC). Such certificates can we viewed as similar to securitization which provide liquidity (cash flow) by selling less liquid loan assets. Bandhan earned interest income of Rs. 318 Cr and Rs. 201 Cr in FY18 and FY19 from IBPC sales.
Liability Profile
Debt comprises of both Current Account Savings Accounts (CASA) and term deposits. CASA deposits provide a stable source of low-cost funding, which formed 36% of their total deposits as of Jun’19 (Sept’ 19 CASA % not reported separately from Gruh) . On the other end, ~85% of their lending is to microfinance borrowers which earns them relatively high yields of 18.40%. Bandhan has maintained a Net Interest Margin (NIM) of over 10%, which is a characteristic of FIs which have CASA as a low cost source of funding.
FY17
FY18
FY19
Jun’19
CASA
29%
34%
41%
36%
D/E
5.5
3.6
3.9
Bandhan has the lowest debt to equity ratio in the industry. Please note that in Financial Institutions, debt is viewed as raw material and capital is defined as including only equity.
Asset Qualityand Risk Factors
Financial institutions have increasingly been opaque when it comes to reporting loan asset quality. It is very challenging to get a true picture of asset quality from annual reports, investor presentations and reports from credit rating agencies. In the past (case in point DHFL) credit rating agencies have not been great at indicating a looming credit crisis on the horizon.
Nonetheless, we have compiled the following to form a view about Bandhan’s asset quality
Increase in loans to NBFCs / MFIsand increase in Non Productive loans – Although, Non Priority Sector (which includes loans to NBFCs/MFIs) forms a small % of Bandhan’s portfolio, but loans to this sector have almost doubled over the past 5 quarters (FY19-Q1 to FY20-Q1). Moreover, as displayed in the exhibit above 75% (1759/2356) of loans are personal loan, which are non-productive. In a stressed economic environment, this class of loans are very susceptible to becoming bad loans since people are less likely to pay for discretionary things. In FY19, such loans (although small % of the portfolio) had an NPA of 1.97% which is very high when compared to PSL NPA of 1.06%
Business has grown with heavy concentrationin the East – As per the investor concall transcript from Jul’19, 55% of Bandhan’s customers have been with them for more than 3 loan cycles. These repeat customers have an outstanding loan ticket size of ~Rs. 49,000 and represent 65% of the total loan value as of Jun’ 19. The first 3 cycles of loans constitute newer customer with a ticket size of Rs. 29,000. Point to note here is that a customer traverses through cycles only if they are making timely payments else the relationship with the customer is discontinued. Moreover, loan sizes are increased as Bandhan feels more confident when a customer has matured beyond 3 cycles. While, this gives comfort but Bandhan is very concentrated in the East. They certainly have seemed to have developed a good relationship with customers in the East since the time they were a MFI. The challenge will be replicating a similar model in other parts of the country where Bandhan is aggressively foraying into.
Asset Liability Mismatch – There was a point in time until last year that everything was so hunky dory with MFIs/NBFCs, the institutional investors were so bullish until Mr. Market made everyone look at one of the most fundamental and crucial principle in Finance – Asset Liability Mismatch (ALM). Let’s try to understand what does it mean in simple terms. When FIs engage in short-term borrowings (liabilities) to give long-term loans/advances (assets) to its customers then what happens is that the FI may not be able to pay off its creditors since the money is stuck in long term loans that they have made to their customers. Typically, FIs roll over their short term borrowings i.e. make another borrowing to fulfill a short term borrowing, but if they are not able to do so then they face a severe liquidity crunch which is called ALM. Now the question arises why do FIs engage in short term borrowings at all? the answer is that such borrowings are cheaper than the longer term borrowings (long term borrowings have a higher interest rate since the providers of capital want to be compensated with a premium for bearing more risk which stems from a longer term loan).
Above exhibit has the maturity pattern of short term (<1 year) assets and liabilities for Bandhan in FY18 and FY19. The maturity bucket coded green are the ones in which assets have exceeded liabilities in their respective maturity buckets. Bandhan has negative asset liability mismatch (ALM) gap in two of the maturity buckets with an overall positive cumulative gap due to the short tenure (<1 year) of microloans vis-a-vis longer term funding which looks good.
Regulatory Constraint
As per RBI requirement, Bandhan is required to maintain a Capital Adequacy Ratio (CAR) of 10.875%. Please note that in Financial Institutions, capital is defined as including only equity (not debt). While a low ratio denotes that the FI is not adequately capitalized, a ratio which rises over time denotes that the FI is not using capital to grow. (CAR = Tier 1 + Tier 2 Capital / Risk Weighted Loan Advances) Tier 1 is the core bank capital, which comprises of equity and disclosed reserves. Tier 1 can absorb losses without requiring the bank to cease operations. Tier 2 capital on the other hand can absorb losses in the event of liquidation. Even though growth in equity has exceeded the growth in advances, but the CAR has decreased recently.
FY17
FY18
FY19
Jun’19
Sept’ 19
Tier 1 Cap
24.8%
31.5%
27.9%
25.8%
Tier 2 Cap
1.6%
1.2%
1.3%
1.3%
CAR
26.4%
32.7%
29.2%
27.0%
25.1%
In the snippet below, the CFO explains the decrease in CAR. Since FIs operate under a regulatory capital constraint, it can be argued that these firms have to reinvest in regulatory capital in order to grow in future. Portion of PAT which does not get paid out can be viewed as reinvestment since it gets added to the equity capital. We have forecasted the change in regulatory capital and used these as reinvestments to estimate Free Cash Flow
Management
Erstwhile Bandhan Financial Services Pvt. Ltd. (BFSL) was the largest NBFC-MFI in India and the first entity to receive an in-principle universal banking licence from the Reserve Bank of India. Bandhan Bank was established following the transfer of BFSLโs business to the bank and it commenced operations in August 2015.
Bandhan Bank was incorporated as a wholly-owned subsidiary of Bandhan Financial Holdings Limited (BFHL). BFSL holds 100% equity in BFHL
As per the RBIโs New Bank Licensing Guidelines, a bank is required to reduce its promoterโs stake to 40% within three years of the commencement of its business (August 23, 2015). Subsequently, BBLโs IPO in March 2018 helped pare the promoterโs stake to 82.28% as on June 30, 2018 from 89.76% as on December 31, 2017
Upon completion of merger with GRUH, Bandhan Financial Holdings Limited โ BFHL, the non-operative financial holding company (NOFHC) was able to reduce its stake to 60.96% from 82.26% earlier, but it remains higher than the 40% requirement as per the banking license requirement of RBI. In Sep’ 18, because of this noncompliance RBI has restricted Bandhan from opening of new branches without prior approval from RBI and also frozen the remuneration of its CMD Mr. Chandra Shekhar Ghosh.
CMD’s total compensation remained Rs 2.04 Cr in FY18 and FY19. He made up for the no increase in compensation by exercising 50,000 (of the 200,000 granted to him) options at a strike price of Rs. 180 (i.e. bought 50,000 shares at Rs. 180) on Feb 14th, 2019 when the shares were trading at Rs. 479. Had he sold the shares around that time frame, he would have made a profit of Rs. 1.5 Cr on an investment of Rs. 90 lakhs (180 * 50,000). This is a perfectly legal way for risk-free gains made possible by the magic of employee stock options.
Of the total 22.2 lakh options (granted in FY18), 4.1 lakh have been granted to senior management personnel including the CMD. It seems rest of the 18.1 lakh options have been granted to mid level management employees. This is good since the higher management does seem to be keeping the free gains to themselvesalone.
Live options are a double whammy for the common shareholders since not only they reduce the value of equity, but also provide free gains to the promoter group and employees holding them. It becomes important to value them and assess the degree of impact they have on the overall value of equity for common shareholders. At the end of FY19, there were 18.57 lakh options outstanding, which have a negative drag on the value of equity. The reason is that the employees holding the outstanding options represent another claim on equity (besides that of the common stockholders) and the value of this claim has to be netted out of the value of equity to arrive at the value of common stock. I have estimated this negative drag at around Rs. 82 Cr using the Black Scholes Model for pricing options. We will see in the valuation section that this value of options seem to have a very low impact on Bandhan’s value of common equity.
Another point to assess the management quality is to look at related party transactions. It seems that the promoter group (BFSL and holding company BFHL), the key management group (KMP) and their relatives make deposits in the bank and in return earn interest. An investor needs to assess the interest% on such deposits and see that it does not exceed the interest% that the bank offers to its customers for specific maturities. Moreover, the huge difference between the maximum outstanding deposits and outstanding deposits at the end of the financial year are also indicative of the fact that a significant chunk of these deposits are short term in nature. The proportion of maximum outstanding deposits to overall deposits by related parties was ~2% in FY19. It could be that the intention is to inject liquidity, in that case we need to ascertain if the bank experiences funding challenges in short-term.
DCF Valuation of Bandhan Bank (just prior to Gruh acquisition)
Value of a firm is the present value of its future cash flows. So it becomes important to estimate the future cash flows to value any entity. Buffet says that he eliminates a company from consideration upfront if he cannot roughly estimate a businessโs key economic characteristics 5โ10 years out.
Click here to look at how we have estimated future FCFE for this financial firm and discounted them to present using Cost of Equity (COE) to arrive at the equity value.
We have forecasted the change in regulatory capital and used these as reinvestments to estimate Free Cash Flow. Based on Sep’19 data, the intrinsic value we have estimated is Rs. 495 per share based on base case assumptions outlined in the valuation exhibit above. We have outlined the assumptions and guiding principles in the exhibit below. ROE is set at a mean of 23.75% (max 25%, min 22.5%) over the next 5 years and then declines to a mean of 20% (max 22.5%, min 17.5%) as the firm transitions to stable growth. 100 Monte Carlo simulation trials are run with ROE oscillating between min and max values. Moreover, we have assumed a growth in loan assets to be 25% over the next 5 years which tapers to 20% when the firm reaches stability. This translates to a CAGR of 24% over the next 10 years. These assumptions reflect my perception of future growth potential based on the fundamental analysis posted above. Infact, on running 100 simulation trails we find that 67% of the intrinsic values lie between Rs. 474 and Rs. 524 per share, with 1/3rd of the these values lying between Rs. 484 and Rs. 494. Distribution is pasted below (Please bear in mind that DCF can be very subjective and is as good as the underlying assumptions. One of my favorite people from the Finance world, Prof. Sanjay Bakshi humorously describes future cash cash flows in a spreadsheet as “mungeri lal ke haseen sapne”. We can’t agree more :-). We have tried not to be too “haseen” and not overly “badsurat” in our future estimates ๐ ) Bandhan was trading under Rs. 500 per share in early part of Oct’ 19, but then the stock shot up well above 500 reflecting market optimism right before the impending merger with Gruh Finance
Bandhan was trading at Rs. 584 (as of 16th Oct, 19 just before the merger), which is the highest value we get in our simulation. On doing a reverse DCF*, we find that 30% of Bandhanโs market cap of Rs 69,670 cr (as of 16th Oct,19 just before the merger) was justified by its then current performance (non growth perpetuity) and the rest 70% is the value market believed that Bandhan will generate from future growth on the back of positive sentiments regarding the merger with Gruh.
*Reverse DCF is nothing fancy – All one needs to do is take the profit after tax and divide it with cost of equity 12.5%. The value that you get is the value that is justified by company’s current performance assuming no growth in perpetuity. This value formed 30% of Bandhan’s market cap before the merger.
Conclusion
Bandhan Bank has demonstrated good growth and constitutes 20% of outstanding micro lending portfolio in the industry. The additional income from selling PSL certificates augurs well for Bandhan. The bank reaches micro loan customers largely through an extensive network of low cost doorstep service centers (DSC) with a cost-to-income ratio of 32.6%. The bank gets a most of its business (65% of value) from repeat customers. Bandhan is very concentrated in the East, which formed 46% of its loan book as of FY19. The challenge will be replicating this model in other parts of the country and building customer relationships (the way it has done in the East) in an industry which has become increasingly competitive. With the acquisition of Gruh, an investor needs to track how Bandhan delivers on the growth synergies due to geographic complementarity (post on the merger with Gruh is up next). An investor needs to closely track the loan asset quality and also loans given to non-priority sector with the limited arsenal of quality indicators (NPA, ALM mismatch, productive/non-productive loans and reports from credit rating agencies) at their disposal. Moreover, an investor needs to closely watch any new ESOPs that may be issued (to see if the management is not overly compensating itself over common shareholders) and also assess deposits made by promoters and interest earned.
Prior to the acquisition of Gruh, Bandhan looked slightly over valued. In our next blog post, we have analyzed and valued Gruh Finance. We have also valued both Bandhan and Gruh together to estimate the value of synergy (which has been outlined as the motive of the deal besides dilution in promoter stake). We then go on to assess if Gruh’s intrinsic value combined with synergy justifies Gruh’s pricing as per the deal.
Disclaimer โ Currently, I do not own any stock of this company. This analysis should not be misconstrued as a buy / sell recommendation. Moreover, any opinion expressed in this blog post is solely my own and does not represent views of my employer.
Edit (9th March 2019) – Using the user based statistics and financial information made public in Lyft’s S-1 prospectus, I have revalued Lyft at ~$17 billion. My valuation is presented in the link alongside https://investandrise.com/lyft-ipo-2019-valuation/
Ride sharing companies have revolutionized the way we commute. Both Uber and Lyft would be going public next year. While Uber has gone global and continues to expand to other businesses, Lyft has shown a much smaller narrative and is present only in US and Canada.
The most important parameter for companies born in the gig economy is the number of users/subscribers. VCs typically value (read price) such companies by “pricing” users/subscribers. The intrinsic value of an asset or business is the present value of its future cash flows (DCF – Discounted Cash Flow Valuation). So, an ideal way to value such companies would be to value users
In this blog post, I have attempted to value Lyft by valuing users using a framework taught by the renowned NYU Stern Prof. Aswath Damodaran. In his paper, Prof. Damodaran has explained how to incorporate user economics in a DCF Valuation or rather how would you use DCF to value user based companies born in the gig economy
The fundamental equation to value such companies that Prof. Damodaran gives is simple and intuitive:
Value of a user based company = Value of existing users + Value added by new users – Value eroded by corporate drag
Lyft’s being priced at $15.1 bn (as of this writing). Using a user based valuation, I have valued Lyft at just under $5 bn by taking certain base case assumptions. The assumption values could be high or low. I do not claim any certitude to these numbers. To accommodate for different cases (or different values of assumption variables), I go on to use monte carlo to get a distribution of Lyft’s valuation across simulation trials. I find that ~80% of the distribution falls below Lyft’s current pricing of ~15 bn
In Lyft’s valuation below, I estimate values for Lyft’s existing users, new users and the value eroded by corporate drag
User Based Lyft’s Valuation
Since Lyft is yet to go public, so financials are hard to come by. I have used the 2018 Q1, Q2 & Q3 financials reported in the information to make estimates for Q4 and then used the base estimates for 2018 to forecast cashflows into the future
Exhibit 1: Estimates based on 2018 Q1, Q2 & Q3 as reported by The Information
a. Value of Existing Users
Simply put, the value of existing users is arrived at by estimating after tax operating profit per existing user for the base year and then forecasting it into the future, followed by taking the present value (PV) of the future cash flows. The PV per user is scaled by the number of existing users to arrive at the PV of after tax operating profit of all existing users. This PV is then slashed using the assumed probability of user lifetime
Base Year 2018 Estimates: (Data from Exhibit 1)
Base Year Operating Profit = 44.8% of Base Year Net Revenue per Existing User (this operating profit has been reported after deducting the cost of revenue only from the net revenue. Cost of revenue consists of insurance, credit card fees and technical infrastructure. It does not include sales & marketing, R&D and employee expenses)
Base Year Net Revenue per Existing User ($67.4 mn)= Estimated Net Revenue ($2129 mn) / Number of Users (Estimated *32 mn)
Assumption Variables for making Forecasts :
User Lifetime: For the base case, User Lifetime is assumed to be 15 years (This is an assumption. I do not have data backing user lifetime. I go on simulate this parameter to take on different values ranging from 4 to 20 years using a discrete triangular distribution)
Probability of User Full Life: Annual Renewal Probability assumed at 95% ^ User Lifetime. Considering that ride sharing businesses have disrupted the market with many users preferring it over their own cars (I certainly do!), I reckon that a major chunk of the existing ride sharing users would stick, although their loyalty to one company is uncertain. A subscription business model would have more user stickiness as opposed to a transaction based. I have attempted to accommodate the uncertainty/variability in user stickiness, by inducing the probability of user full life take on different values in my simulation. (Since user lifetime is simulated to take on different values, hence probability of user full life becomes a variable as well. )
Growth Rate (of Net Revenue): For the base case, Net Revenue per User is assumed to grow at 15% for the first 5 years, at 10% for the next 5 years and then at the risk free rate. Again, these values could be high or low! I reckon that the company would mature after 10 years and hence, grow at the risk free rate. (To accommodate for the uncertainty on growth rate, I simulate this parameter over a range of 8% to 20% using an asymmetric positively skewed continuous distribution)
Growth Rate (of Cost of Servicing Existing Users): [x% * growth rate (of net revenue) ] + [(1-x%) * inflation rate], where x is assumed to be 80% for the base case (x is simulated to take on different values ranging from 70% to 100% using an asymmetric negatively skewed continuous distribution)
Discounting Factors – Cost of Capital reflecting CashFlow uncertainty or User Risk: For the base case, cost of capital is taken as 10%, which is the 75th percentile for US companies. I just need to ensure that the cost of capital for existing users is lower than that of acquiring new users since the cash flows from new users would be more uncertain/risky. (Cost of capital is made to take on values ranging from 8% to 12% on a normal distribution. No skewness assumed since existing users would have relatively low risk vis-a-vis new users)
Number of Users: As per Forbes, the number of users in 2017 were 23 mn. I couldn’t find the number of users in 2018, so I had to estimate it. Here is how –
Lyft achieved 1 billion rides in Sept 2018. It was at 500 mn rides around the same time frame last year. This translates into a compounded monthly growth of just under 6%
Extrapolating this growth till December of this base year 2018, I get an additional ~200 mn rides i.e. 1200 mn rides totally.
Taking out the number of rides till December 2017 (i.e 1200mn – (500+1.059^4)), I get ~600 mn rides in 2018
One of the other statistic that I found is that on an average each user took 19 rides. So, the *number of users in 2018could be estimated as 600mn rides/19 rides per user ~ 32 mn users.
*This is a crude method to estimate users and I would want to replace this estimate with the actual number of users as when that statistic becomes public*
Operating Profit (for each year in the future) = Net Revenue forecast – Cost of Servicing Existing Users forecast
The future operating profit is discounted using cost of capital and then slashed using the probability of user full life
Exhibit 2: Value of Existing Lyft Users $6.1 bn (base case)
b. Value Added by New Users
New users in the base year is the increase in users in base year 2018 over 2017. Base year value added by each new user is the amount by which value per existing user exceeds cost of adding a new user
Base Year 2018 Estimates:
Cost of Adding New Users is the amount spent over and above the spend on servicing Existing Users (and also excluding Corporate Expenses)
Amount spent over and above the spend on servicing Existing Users = Operating Profit (on servicing existing users) + Net Loss Amount – Corporate Expenses
Therefore, Cost of Adding a New User = (Net Revenue + Net Loss – Cost of Servicing all Existing Users – Corporate Expenses) / (Users in 2018 – Users in 2017)
Base Year Value Added by New User = Value per Existing User – Cost of Adding a New User
Assumption Variables for making Forecasts :
Growth Rate (in # Users): Assumed 25% for the first 5 years and 10% for the next 5 years
Annual Renewal Probability: Assumed at 95%. I have attempted to accommodate the uncertainty/variability in user stickiness, by inducing the probability of user full life take on different values in my simulation.
Discounting Factors – Cost of Capital reflecting CashFlow uncertainty or User Risk: For the base case, cost of capital is taken as 12%, which is higher than the cost of capital for existing users. A cost of capital of 12% occurs at the 90th percentile for US companies. (Cost of capital is made to take on values ranging from 9% to 18% using an asymmetric negatively skewed continuous distribution. I have assumed a negatively or left skewed distribution since existing new users would have relatively high risk vis-a-vis existing users)
New Users are estimated to increase at an assumed growth rate and decrease with the assumed annual renewal probability each year. Value per New User is forecast to increase each year with the inflation rate
Exhibit 3: Value added by New User $3.1 bn (base case)
c. Corporate Drag
Corporate Drag of $400 mn in the base year is an assumed base case value. (It has been simulated to take different values ranging from $200 mn to $600 mn using a normal distribution)
Moreover, Corporate Drag is assumed to grow at 4% every year
Exhibit 4: Corporate Drag estimated at $4.4 bn (base case)
Exhibit 5: (base case) Value of Lyft $4.8 bn = Value of existing users $6.1 bn + Value added by new users $3.1 bn – Value eroded by corporate drag $4.4 bn
On running a monte carlo simulation, I get the following distribution for Lyft’s valuation (Exhibit 6)
Exhibit 6: Distribution of Lyft’s valuation across simulation trials
Key statistics/observations from the distribution above:
My base case valuation of $4.8 bn falls at the 44th percentile i. e. 44% of the distribution values are below $4.8 bn
Median i.e. the 50th percentile occurs at a valuation of ~$6 bn
Lyft’s “pricing” of $15.1 bn occurs near the 80th percentile, which means that ~80% of the values that I get are lower than this price
Another interesting observation is that ~26% of values of the distribution are negative. This could be interpreted as Lyft’s probability of default
Valuation is very sensitive to the number of users. The above is just a snapshot in time valuation based on a lot of assumptions. Closer to its IPO in 2019, when Lyft makes its financials public, then I would replace the assumptions with actuals to arrive at its fair valuation
