Bandhan and Gruh Merger Valuation

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

Period10Y5Y3Y2Y1Y31/3 – 30/9
Outstanding Loans CAGR24%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, GRUH’s 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

FY15FY16FY17FY18FY19Jun-19
Outstanding borrowings82161024412018140461658418430
Banks/NHB67%77%67%55%63%69%
NCDs8%9%20%29%26%20%
Public Deposits16%14%13%10%9%9%
CPs9%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.

Regulatory Constraint and Equity Profile

 FY10FY11FY12FY13FY14FY15FY16FY17FY18FY19Jun’19
CAR16.6%13.2%14.0%14.6%16.4%15.4%17.8%18.3%18.9%20.3%20.3%

Recently, NHB has proposed a gradual increase in the capital adequacy ratio (CAR) from the current 12% to 15% by 2022. Since FY14, Gruh has maintained CAR of over 15% and it has consistently increased from 15.4% in FY15 to 20.3% in FY19.

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.

 FY10FY11FY12FY13FY14FY15FY16FY17FY18FY19Jun-19
D/E8.89.39.910.010.711.512.310.89.08.78.8

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.

 FY10FY11FY12FY13FY14FY15FY16FY17FY18FY19Jun’19
NPA1.11%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

2. Valuation of the merger

We have valued Bandhan Bank separately just before it acquired Gruh Finance. The analysis and valuation is presented here.

Gruh was priced at Rs. 23,599 Cr [= 565.92 * (73.4 Cr Gruh shares * 568/100)] as per the terms of deal with Gruh shareholders receiving 568 Bandhan shares per 1000 Gruh shares. The merger came into effect on 17th Oct, 19.

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 Sep’19 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 – 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 Valuation (just prior to merger with Gruh)

In this blog post, we have assessed the key fundamentals of Bandhan Bank just prior to its merger with Gruh Finance. Using Discounted Cash Flow valuation with latest reported numbers from Sep’19, we have estimated an intrinsic value of Rs. 495 per share, making the Bank slightly overvalued before the impending merger. We have also posted our analysis and valuation of Gruh Finance. We have estimated the value of synergy arising out of its merger into Bandhan and assessed if the deal was priced to be a bargain.

Loan Asset Profile

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
FY17FY18FY19Jun’19Sep’19 (as per investor presentation) CAGR
(FY17-19)
Outstanding Advances (including IBPC)₹23,642₹32,389₹44,776₹45,420₹45,927 37.6%
Microcredit %69.6%87.1%84.6%86.0% 
Microcredit₹16,457₹28,211₹37,889₹39,061 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.

 FY17FY18FY19Jun’19
CASA29%34%41%36%
D/E5.53.63.9

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 Quality and 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

  1. Increase in loans to NBFCs / MFIs and 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%
  2. Business has grown with heavy concentration in 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.
  3. 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.

 FY17FY18FY19Jun’19Sept’ 19
Tier 1 Cap24.8%31.5%27.9%25.8% 
Tier 2 Cap1.6%1.2%1.3%1.3% 
CAR26.4%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 BFSL’s 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 RBI’s New Bank Licensing Guidelines, a bank is required to reduce its promoter’s stake to 40% within three years of the commencement of its business (August 23, 2015). Subsequently, BBL’s IPO in March 2018 helped pare the promoter’s 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 – 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 themselves alone.

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 business’s key economic characteristics 5–10 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 🙂 ) 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 Bandhan’s 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 – 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.

TCS Stock Valuation

The objective of this blog is to analyze TCS fundamentals and estimate a fair value per share. Please note that this valuation was done on 4/29/2019.

Just as a manufacturing company invests in building new products/plants, a service company such as TCS invests in up-skilling (learning and development) its existing employees and recruiting new talent. Point being CapEx in service companies is primarily done on learning and development / recruiting employees. It is important to keep a track on such expenses because of two reasons –
A. <Quantitative> Expected growth is a function of re-investments back into the firm (how much the firm re-invests) and return on capital (quality of investment).
B. <Qualitative> Spend on L&D denotes that the firm is serious about remaining relevant in the dynamic technology landscape and a comparison of such spends across different firms could be done to evaluate competitive advantage / future growth potential (which ties in with (a.))
We will estimate expected growth later in this blog post.

You may want to further scratch the surface on L&D spend to see how much of it is going towards upskilling vis-a-vis compliance etc. You may also want to look at the number of patents (IP) or any products developed and use it a a proxy for additional growth

Capital efficiency and operating margin together dictate the return on capital, which gives a view on the quality of investment back into the firm. Detailed voice over presented in the embedded video URL https://www.youtube.com/watch?v=1DXfkGT2d_A

Detailed voice over presented in the embedded video URL https://www.youtube.com/watch?v=1DXfkGT2d_A
Detailed voice over presented in the embedded video URL https://www.youtube.com/watch?v=1DXfkGT2d_A
Detailed voice over presented in the embedded video URL https://www.youtube.com/watch?v=1DXfkGT2d_A

Based on last year’s re-investments and the quality of those re-investments, fundamentally TCS could grow at 10.34%. We could also take the average of the past expected growth rates to smooth the perceived slight outlier effect of last year. (the average expected growth rate over the last 4 years is lower)

The voice over the above slide snapshots is present in the video embedded below

Disclaimer – Any opinion expressed in this blog post is solely my own and does not represent views of my employer. Moreover, this stock valuation should not be misconstrued as a buy / sell recommendation

Virinchi Stock Valuation

The objective of this blog post is to analyze the fundamentals and value the 3 lines of businesses of Virinchi separately and estimate a consolidated Fair Value Per Share.

Virinchi was trading at Rs. 75 per share as of 10/5/19. It looks undervalued as per my analysis.

Any opinion expressed in this blog post is solely my own and does not represent views of my employer. Moreover, this stock valuation should not be misconstrued as a buy / sell recommendation

Lyft IPO 2019 Valuation

Ride sharing companies have revolutionized the way we commute. 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. Lyft just filed for a much awaited IPO and should get listed by the end of this month.

I had earlier valued lyft at around $5 bn in November last year. The data and assumptions were based on the limited statistics that were available on the internet. Although, I did expect annual revenue of ~$2 bn and loss of ~$900 mn and had baked these numbers in my valuation, but I was too far off in the number of active users / riders (my source of info led me take 32 mn and 23 mn users in 2018 and 2017 respectively). This statistic is key to valuing companies such as Lyft and Uber, which are making shared economy mainstream. Now since Lyft’s financials are public, we know the active number of users is 18.6 mn (as of Q4 2018 up from 12.6 mn in Q4 2017). I plugged the actual user based statistics in my model and the valuation that I get is $17 billion.

As earlier, the valuation framework that I have used has been pioneered by the renowned NYU Stern Prof. Aswath Damodaran. In his paper, Prof. Damodaran has explained how to incorporate user economics in a DCF Valuation. 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 expenses

Value of existing users (or customer lifetime value)

Each valuation needs to have a fact based story, which is essentially what we think of the company, its growth potential and the risk associated with its users/riders (i.e. would users stick or ditch).

Revenue per active user

Fact: Lyft reported a revenue of ~$130 per active user in 2018, up from ~$100 and ~$67 in 2017 and 2016 respectively. This translates to 30% revenue per user growth in 2018 and 50% growth in 2017. Moroever, Lyft’s share of revenue from gross billings is 26.7% ($2.15 bn revenue/$8.1 bn worth bookings).

Story: I believe Lyft’s wallet share would continue to grow, but the growth rate would continue to decrease from 50% (2017), 30% (2018) to 25% (2019) and 3% (Risk Free Rate in 2028).

Cost of Revenue & Operating Profit

Fact: After removing cost of revenue (which includes insurance, payment processing charges, technology costs and amortization), operating profit per active user is ~$55 in 2018, up from ~$38 and ~$13 in 2017 and 2016 respectively. This translates to a cost of revenue of 57.7% in 2018

Story: I believe the cost of revenue would be more or less the same in the near term, but would decrease in the long term as the company optimizes its operations

User Stickiness

Fact and Story: 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. With Lyft using loyalty programs and with its focused narrative on ride sharing, I go on to assume that 90% of riders would stick every year.

Using the assumptions, I go onto project after tax profit (i.e. by projecting revenue and cost) per user into the future. I take the present value of these future cash flows using a 10% cost of capital (75th percentile of global companies) and then adjust this present value for user stickiness. I get a customer lifetime value or value per existing user/rider of $450. With 18.6 million active riders, the total value for all existing customers is $8.4 billion

Value added by new users

Number of new users/riders added every year

Fact: Lyft reported a 18.6 mn active riders at the end of 2018, up from 12.6 mn and 6.6 mn in 2017 and 2016 respectively. This translates to 48% user growth in 2018 and 91% growth in 2017.

Story: With more and more people ditching their cars (and lease rentals) and opting for on demand ride sharing, I believe Lyft would be able to tap new users every year, but the growth rate would continue to decrease from 91% (2017), 48% (2018) to 25% (2019) and 3% (Risk Free Rate in 2028). The total users added each year is adjusted for user stickiness

User/rider acquisition cost

Of the entire amount Lyft spent (Revenue + Loss), it spent $1.24 bn of it in servicing existing users (reported as Cost of Revenue in the P&L) and ~$0.45 bn in general & admin expenses. The rest of the spend (~$1.14 bn), which includes sales, marketing and operations can be attributed to acquiring new customers (18.6 – 12.6 = 6 mn). The cost of acquiring a customer that I get is ~$190

Total value added by new users

Netting off user acquisition cost ($190) from the user lifetime value ($450), I get the value added by each new user to be ~$260.

I go on to project the value added by new acquired users/riders each year by multiplying the calculated new users each year with the value added by a new user each year compounded with the inflation rate. I then take the present value using a cost of capital to arrive at the total value added by new users to be $11.5 bn (Cost of capital is taken as 12%, which is higher than the cost of capital used for existing users. A cost of capital of 12% occurs at the 90th percentile for US companies )

Value eroded by corporate expenses (G&A)

Quoting from the S-1 prospectus – “General and administrative expenses primarily consist of certain insurance costs that are generally not required under TNC or city regulations, personnel-related compensation costs, professional services fees, certain loss contingency expenses including legal accruals and settlements, claims administrative fees and other corporate costs. Following the completion of this offering, it is expected to incur additional general and administrative expenses as a result of operating as a public company.” Corporate expenses are assumed to grow at 4% every year. Discounting the future cash outflows, I get the present value of corporate expenses of close to $5 bn

Putting it all together

Value of Lyft $14.9 bn = Value of existing users $8.4 bn + Value added by new users $11.5 bn – Value eroded by corporate expenses $5 bn

We also need to account for employee stock options ($609 mn), cash ($517.7 mn) and IPO proceeds ($2000 mn)

Removing employee stock options, and adding cash and IPO proceeds, I get the value of equity to be $16.8 billion

Since, the number of shares outstanding is 279 mn, I get a share price of $60.25 per share

Valuation is very sensitive to my assumptions on growth and user stickiness, which in turn depend upon Lyft’s ability to acquire and retain customers. The assumptions I have taken, although reasonable in my view, might be high or low. I do not claim any certitude to these numbers. As Prof. Damodaran says your story should drive numbers. Your story can very well be different from mine. Any higher values of these metrics would result in a higher valuation.

Please do let me know what you think in the comment section.

Lyft – User Based Valuation

Image Credits: grist.org, lyft

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 : 

  1. 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)
  2. 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. )
  3. 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)
  4. 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)
  5. 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)
  6. 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 2018 could 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 :  

  1. Growth Rate (in # Users): Assumed 25% for the first 5 years and 10% for the next 5 years
  2. 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.
  3. 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:

  1. 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
  2. Median i.e. the 50th percentile occurs at a valuation of ~$6 bn
  3. 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
  4. 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

Upwork (UPWK) IPO Valuation

UP1.9.png
Image Credits: Learn to Earn and Upwork

The objective of this article is to estimate the intrinsic share value for freenlancing platform Upwork, which went public on Oct 3rd. The estimate is arrived at using a DCF valuation based on the company fundamentals given in its S-1 prospectus and my own views/forecasts on the company

Disclaimer: The intent is certainly not to give buy/sell recommendations and also I do not own any stock of the company

I have come up with a point estimate share value of $15.1. The IPO issue price of $15 looks fairly valued. The IPO listed at $23 i.e ~53% premium. The stock now trades at $21 per share and looks overpriced as of this writing (10/5/18)

Devil is in the details (the not so good part) :

  1. As per the S-1 prospectus, Upwork does not calculate or track freelancer retention metrics. I believe that tracking talent retention (just as tracking customer retention) and taking steps to plug any attrition is essential to any talent platform
  2.  Although, in 2017 and the six months ended June 30, 2018, almost 50% of client spend was from clients that had used the platform for longer than three years, however, the absolute spend by these clients have shown a marginally declining trend from the time they first spent on the platform
  3. Accounting evils –
    1. Employee stock options have not been expensed i.e. they are not used to arrive at Net Income in the P&L and are hence present in the Cash Flow (CF) statement and the equity section of the Balance Sheet (BS)
    2. Net losses by using derivative instruments have not been expensed and are hence present in both the CF statement and the BS.

The Impact due to the above is an illusory positive impact on the Cash Flow statement and low expenses resulting in less negative Net Income

3. R&D has been expensed instead of being capitalized

4. Operating Leases have been expensed instead of being treated as a lease asset

I have fixed 3.1, 3.3 and 3.4 in my valuation. I couldn’t fix 3.2 since the extent of net losses is not mentioned in S-1

I treated Stock based compensation as an expense and added back R&D compensation to reported EBIT to arrive at adjusted EBIT

UP1.1.png

Exhibit 1 – Adjusting EBIT by treating stock based compensation as an expense and R&D compensation as capital

 

Then I went on to use Black Scholes to value the outstanding 22.93 mn options at *$285.7 mn and eventually deducted it from my estimated value of equity to arrive at equity in common stock and subsequently got a reduced value per share. This might seem like double dipping (i.e treating stock based compensation as an expense and then deducting stock options from value of equity), but its not. Dean of Valuation and renowned NYU Stern Prof. Aswath Damodaran has brilliantly explained the treatment of stock based compensation in valuation  

*I used the IPO issue price of $15 as the stock price, 3% Risk Free Rate, weighted expiration of 7.2 years and standard deviation of 38.4% (as mentioned in the prospectus) in the Black Scholes forumla to arrive at Options value

Next, I capitalize R&D which has a positive effect on reported EBIT and also gives a tax benefit on resulting the amortization of the last year

Lastly, I take find the present value of future lease commitments and this value ($3.37 mn) to total debt. This is our operating lease asset. I depreciate this and deduct the depreciation ($0.67 mn) from the current year’s lease commitment ($3.6 mn) to determine the adjustment to be made operating income – i.e. I add $2.93 mn to EBIT

Fixing 3.3 and 3.4 have a positive effect on EBIT with the result that I get an overall positive value of EBIT $24.89 mn from -$15.62 mn

UP1.2.png

Exhibit 2 – Before fixing 3.3 and 3.4

 

UP1.3.png

Exhibit 3 – After fixing 3.3 and 3.4 : Operating Income increases due to the effect of adding back current year R&D (less amortization) and Operating lease (less depreciation). Also note Adjusted Operating Margin Pre Tax = 24.89/228 = 10.92%

 

Absolute Valuation

Free Cash Flow to Firm or FCFF is used to estimate Free Cash available to both debt and equity holders. It is arrived at by estimating cash flow generated from operations or the Net Operating Profit After Tax EBIT(1-T), some of which is re-invested back in the firm. Any cash over and above the re-investments is available to both debt and equity holders. This is called Free Cash Flow to Firm (FCFF). Present Value of future FCFF is the Enterprise Value (EV). Additionally, removing present debt from EV and adjusting for stock options leaves us with equity in common stock

Facts->Stories->Numbers

Before jumping into the valuation we need to have a story spun around facts, which is essentially what we think of the company, the industry, market size, growth potential, margin, investments needed to drive and sustain growth, capital nature of business – intensive/light/efficient, period of high growth and the transition to stable growth, business risk and the interplay of competition among other things

Now, lets take a look at the above objectively and attempt to tie certain facts it to our story

 

A. Fact: Market Size & Growth

  • As per McKinsey, the total global Gross Service Value (GSV) opportunity for freelancing platforms was approximately $560 billion in 2017. By 2025, online talent platforms could add $2.7 trillion annually. This represents a 21% increase Y-o-Y.
  • Upwork GSV grew by 30% period-over-period (for the 6 months period ending June 30, 2017 and June 30, 2018), primarily driven by a 22% increase in the number of core clients
  • Upwork revenue grew 23% annually in 2017 to $202.6 mn and also revenue grew 28% period-over-period

A. Story: Coupling the above with increased investments in R&D and Marketing & Sales in the last 2 years makes me believe that revenue could grow at 25% Y-o-Y

B. Fact: Growth Period

  • Typically, the revenue growth rate of a newly public company outpaces its industry average for only 5 years

B. Story: Since we have only one other publicly traded freelancing platform i.e. freelancer.com, I am wary of using it as my guiding light. I reckon that the 25% growth could last 5 years (Stage 1), which is followed by another 5 year period of slightly declining growth (Stage 2) which then gives way to lower stable growth (Stage 3) equivalent to the risk free rate of 3% (yield on the US 10 year T Bond) in perpetuity

 

C. Fact: Operating Margin 

  • The Adjusted Operating Margin Pre-Tax estimated in Exhibit – 3 above is 10.92%. Typically, Pre Tax Operating Margins in mature software companies is around 20%

C. Story:  I know it would be to broad to assume a target pre-tax operating margin of 20%. The firm is currently at 10.92% (after making adjustments) and hence it seems reasonable to make 20% as a targeted margin. I go on to make this parameter configurable towards the end to see what kind of effect it has on my valuation

 

D. Fact and Story: Re-investments

  • This is perhaps the most important and most difficult parameter to forecast specially when we do not have a lot of financial history available. There are multiple ways to estimate re-investments
    1. Top-down: We need to forecast the invested capital turns or the sales to capital ratio. Re-investment is sales to capital multiple times the incremental revenue
    2. Bottom-up: Forecast the Net CapEx (i.e. CapEx – Dep) and Working Capital changes. The sum is the re-investment.

Bottom-up can be put to use when there is some financial history available, but for growth firms I prefer the top-down method, which essentially requires us to have a view of the capital nature (intensive/light/efficient) of the business and then use the corresponding industry benchmark sales to capital ratios depending upon the nature. Moreover, we could also use the sales to capital ratio of the current base year and extrapolate it to future years (Nothing is incorrect! it all depends on our view of the company)

Sales to Capital ratio in the current base year = Sales / (Book Value of debt + Present Value of Future Lease commitments + Equity + Value of R&D asset (current + past un-amortized) – Cash equivalents)

Sales to Capital in current year= $228 mn / ($33.88 mn + $3.37 mn + – $30.60 mn + $77.54 mn) = 4.31

This ratio translates to a close to minimal capital need business as per industry benchmark. But, I reckon extrapolating just one year’s ratio to generalize the nature of the business and take a call on future re-investment needs is a stretch!

Prof. Aswath Damodaran gives the following benchmark ratios depending upon the capital nature –

Minimal capital needs, no acquisitions (10.00)
Minimal capital needs, small acquisitions (5.00)
Service company median (3.00)
Technology company median (2.50)
US company median (2.00)
Capital intensive company median (1.50)

In my valuation, I have used Technology company median (2.50) for Stage 1 and then used US company median (2.00) for Stage 2. I have done so since I reckon the company is neither capital intensive nor capital light. I do not claim to have any certitude about these numbers. The reduced sales to capital ratio in Stage 2 implies increased re-investments as the company transitions to stable growth

For Stage 3, we do not have to forecast this ratio.

During stable growth, Re-investment Rate = Growth Rate / ROIC

ROIC again is tricky. The adjusted base year ROIC is calculated in Exhibit – 4. Adjusted ROIC base year = 32.96%

UP1.4.png

Exhibit – 4

During stable growth, I have taken a 75th percentile ROIC benchmark, which is 20%. Transitioning from the current adjusted ROIC of 32.96% to 20% in stable growth seems reasonable (again I do not claim to have any certitude about these numbers)

 

E. Cost of Capital

I have used the cost of capital from the S-1 prospectus directly which is 7.2 %

 

The above **Facts->Stories->Numbers (well, from A through to D) helped me forecast the following main parameters we need for this valuation –

**I know we had limited factual data.
  1. Revenue Growth (during high growth, transitioning and stable growth period)
  2. Periods of Growth
  3. Operating Margin (during stability)
  4. Re-investment
  5. Cost of Capital

On plugging these parameters into the valuation, I get a per fair share value which is very close to the IPO share issue price of $15. On reducing the Sales to Capital ratio to 2 for both Stage 1 & 2 and also toning down my ROIC expectations to 12.5% (which is the US industry median), I get a share value of $13.1 (which again is not too far off from the IPO share issue price). However, post the public issue the stock has become overpriced.  

UP1.6.png

Exhibit – 5: Present Value of Forecast(ed) Future Cash Flows. Cells in Orange are configurable

UP1.8.png

Exhibit – 6: Implied Variables with the exception of the Cells in Orange, which are input and can be configured

 

UP1.7.png

Exhibit – 7: Estimated value/share arrived at after removing debt and value of options

 

Bandhan Bank IPO Valuation

Credits: businessnewsdaily

Image Credits: businessnewsdaily

The objective is to give a range of fair values to Bandhan Bank’s IPO to help the reader make an informed decision before investing (and the idea is certainly not to predict listing/short-term gains). Relative valuation alone does not really help us when the firm does not have a close second.  In our daily life, we like to pay for and invest in tangible things that are priced at fair value, right? And hence the same thing holds true for stocks. In this article, I have tried not to repeat the details about this IPO that are all over the internet. Of course, I have used a lot of data from their Red Herring Prospectus (RHP) and attempted to use some of that key data in making assumptions for the valuation.

I have used the straight forward Excess Return Model (as opposed to FCF methods – reasons presented in the absolute valuation section) to value the stock of this Financial Services firm BFSL. This method is simple yet very robust for stock valuation Financial Services firms, especially when operational history is limited.

The stock is available at an upper band issue price of Rs. 375.  The issue is overpriced if we assume that the past ROE of 25.55% would be achieved consistently in the future.  However, on using excel goal seek functionality which forces the issue price to 375 per share, we arrive at an ROE of 33.80% i.e. if the bank experiences a consistent ROE of 33.80% in the future, it would make the issue fully priced

The below sections shed light on the some of the important qualitative and quantitative factors and then I go on to use those factors in arriving at a range of fair values. You might want to skim straight to the last section on absolute valuation.

 

The Business model of the entity has transitioned over the years, operating as an NGO in 2001 and then a non-bank finance company (NBFC) before becoming a bank (operations started in Aug 2015), the provision of micro loans to woman has remained a core focus

Competitive advantage

  • Bandhan Financial Services Limited (BFSL) reaches micro loan customers largely through an extensive network of low cost doorstep service centers (DSC). Low-cost model is demonstrated by our operating cost-to- income ratio was 35.38%
  • The Bank boasts of a differentiated model since on one end they have a stable source of low-cost funding through Current Account and Savings Account (CASA) deposits, which forms 33.22% of their total deposits. On the other end, ~90% of their lending is to microfinance customers which earns them relatively high yields of 18.40% (as of December, 2017)
  • Focus on underbanked and underpenetrated markets allows to meet certain regulatory requirements
  • RBI requires that
    1. Banks locate at least 25% of their banking outlets in what it calls “unbanked rural” areas. Bandhan Bank has 29.15% of their banking outlets located in unbanked rural areas
    2. Minimum 40% of all lending to be made to Priority Sectors, which includes micro loans. Bandhan has 96.49% of their Gross Advances as Priority Sector Lending (PSL) compliant as of December 31, 2017
  • As per the RHP, “while traditional established commercial banks may not be well suited to targeting unbanked rural areas or providing PSL-compliant lending, and thus see a drag on their profitability and yields. Rather, Bandhan Bank targets unbanked rural area segments by choice, operating a low-cost network designed to cost-effectively and profitably reach these segments”
  • According to CRISIL Research, Eastern and Northeastern India, which are Bandhan’s strongest markets, have the lowest presence of bank branches per capita of any regions in India
  • As of December 31, 2017, percentage of Gross NPAs to Gross Advances (NPAs) was 1.67% of their portfolio. Strong NPA position is largely driven by group-based individual lending model, with focus on income generating loans made to women and lending progressively higher amounts only to members who have built up a track record of good repayment, which taken together have led to low rates of default. Bandhan claims that all micro loan customers are insured so that if they pass away, their loan balance is paid off in full without their family needing or feeling pressured to repay the loans
  • As at December 31, 2017, capital adequacy ratio was at 24.85% RBI requires a minimum capital adequacy ratio of 13.0% of total risk-weighted assets
  • The Parent entity grew from India’s fourth largest microloan portfolio as of March 31, 2010 to India’s largest microloan portfolio as of March 31, 2012. As of now, over 90% of lending falls under Microfinance, which is a high yielding category

Credit potential in rural India –

  • Although rural India contributes 47% of India’s GDP, its share in total credit outstanding is just 10%, in comparison with 90% for urban India as of fiscal year 2016. This extreme divergence in the share of rural areas in India’s GDP and banking credit is an indicator of the very low penetration of banking in rural areas
  • Buoyed by the Government’s sustained efforts to bolster financial inclusion, the number of credit accounts in rural India grew at a 7% CAGR, with the number of deposit accounts rising at an 18% CAGR in fiscal year 2016 from fiscal year 2011. This growth was higher than the 5-years CAGR of 5% in the number of credit accounts, and 14% in the number of deposit accounts in urban India. Notwithstanding, the number of credit and deposit accounts in rural India was almost half that of urban India as of fiscal year 2016
  • 2/3rd of total households are in rural India and the region wise region-wise asymmetry further bolsters the potential for credit growth. Northern and eastern regions have a lower share in total bank credit and deposits. Banking retail credit per capita in the eastern region is the lowest, and is five times lower than the southern region

As per latest RBI data, y-o-y credit growth as of February 2, 2018 was 11.0%

Microcredit sector potential and Bandhan Bank’s current standing –

  • Industry size is pegged to reach ~ INR 1 trillion in next two years driven by rising penetration
  • As per Bharat Micro-finance 2016, MFIN, CRISIL Research (November 2017), the gross loan portfolio (GLP) of MFIs grew at 51% CAGR from fiscal year 2013 to fiscal year 2017. This growth was fuelled largely by the growth in GLP of some large players, such as Janalakshmi Micro-finance, Bharat Financial Inclusion Ltd, Ujjivan Financial Services and Satin Creditcare Network Ltd
  • CRISIL Research expects the MFI loan portfolio growth to be at around 16-18% annually in the next two years, much lower compared with the past four years, as rural areas in well-penetrated states mature and the focus of some top players converting into SFBs shifts towards selling other banking products
  • Banks (including direct and indirect bank lending) account for approximately 60% share of the overall micro-finance credit in India
  • As per he RHP, Bandhan Bank has the largest overall gross micro-banking asset portfolio, with ₹213.8 billion as of March 2017, (also counting gross advances, which includes IBPC/Assignment, in the microfinance segment). Amongst the banks (private as well as public), the outstanding loans given by Bandhan Bank is more than three times higher than its closest competitor, the State Bank of India
  • Bandhan Bank’s loan book grew 35% in fiscal year 2017. Highest loan book growth has been registered by Bajaj Finance. Bank’s deposit growth was second only to IDFC Bank. The deposit growth for these two banks was the highest amongst their peers on account of their lower base, as they began to accept deposits only from fiscal year 2016

 

Cost of funds – 

  • Average cost of deposits decreased from 7.72% to 7.09% (annualized) due to an improvement in CASA ratio from 27.22% to 33.22% for the nine months ended December 31, 2016 to the nine months ended December 31, 2017.
  • Increase in CASA i.e. number of deposits led to lesser RBI/inter-bank borrowings (deposits are cheaper than borrowings from RBI/inter-banks), which in turn let to a decrease in overall cost of debt from 7.9% (in FY2017) to 7.24% (annualized) as of December 31, 2017
  • ICICI Bank has a CASA ratio of ~50%, which makes it overall cost of funding to be the lowest (5.3%) in the industry. HDFC and Axis too have a similar CASA and a marginally higher cost of funding. Banks or financial entities which are not into deposits (i.e. “0” CASA ) typically have higher cost of funding
  • Small Finance Banks with no CASA- AU Small Finance Bank and Janlakshmi Financial Services have high cost of funds of 10.3% and 10.4% respectively. MFIs – Satin CreditCare and Grameen Koota Financial Services cannot have deposits and hence have highest cost of funds @ 13.2%

Absolute Valuation

It is challenging to value BFSL using FCF methods since reinvestment composed of Net CapEx and Working Capital is hard to forecast for financial firms. Moreover, for BFSL it becomes all the more challenging due to the lack of operational history. I was wary of using the Dividend Discount Model (DDM), which again is very similar to FCF, but heavily depends on assumptions around payouts i.e. dividends. BFSL has not obviously paid out any dividends and it does not mention any proposed payout ratios explicitly in the Red Herring Prospectus.

For this valuation, I have used the Excess Return Model, which NYU Stern Prof. Aswath Damodaran has explained brilliantly in his book “Investment Valuation”. This method is relatively straight forward and cuts through layers of complexity. This method is quite intuitive with the idea that it takes the value of both current equity and forecasts of future excess equity returns

Value of Equity = Equity Capital invested currently (including Fresh Issue through IPO) + Present Value of Excess Equity Returns to equity investors; 

where Excess Equity Returns = (Return on Equity – Cost of Equity) * Equity Capital invested

This model requires us to estimate 4 important parameters –

  1. Return on Equity (ROE): BFSL has an annualized ROE of 25.55% as of December 2017
  2. Cost of Equity (COE): Hard to ascertain using CAPM since Beta is not available for an unlisted firm. Moreover, BFSL’s business model is different from a typical listed bank and MFI, which makes it problematic for us to consider the Beta of a peer firm. Nonetheless, we would assume a range of Beta value from 1 to 1.2 to estimate COE

CAPM:  COE = Risk Free Rate + (Beta of Stock * Equity Risk Premium)

When Beta = 1: COE = 6.9% +  1*5% = 11.9%

When Beta = 1.2: COE = 6.9% + 1.2*5% = 12.9%

Risk Free Rate (RFR) is given to be between 6.7% to 7.1% in the RHP, hence we assume RFR to be 6.9%

  1. Beginning value of Equity: 4446.4 Crores in the beginning of FY2018 as available in the Balance Sheet
  2. Dividend Payout Ratio: No dividends yet obviously. No explicit payout ratio mentioned in the RHP. Payout ratio assumption does not have a significant impact on the valuation using excess return model as it has in DDM. We assume a payout ratio of 5%

To get started, we need to make the judgement as to when BFSL would become a stable growth firm. Because of the under-penetrated microcredit sector and differentiated business model, we can assume a high growth period of 10 years (stage 1) wherein BFSL sustains its current ROE of 25.55% with a COE) between 11.9 to 12.9%. High growth period is followed by a period of stable growth (stage 2) wherein both return on equity and cost of equity fall and converge to let’s assume 10% i.e. there is no value gained or lost after 10 years, rather excess return generated in stable growth period is 0

The net income each year is computed as the product of ROE and beginning value of equity each year as indicated in the exhibit. Book value of equity each year is estimated each year by adding previous year’s equity to the retained earnings of the current year

 

Exhibit – Excess Return Model

Projected fair value of Rs. 206 per Share on a consistent ROE of 25.55% during the high growth period with Cost of Equity of 11.9%
The fair value reduces to Rs. 190 per Share on increasing Beta to 1.2 (i.e. Cost of Equity of 12.9%)

As we increase Beta, risk increases, and hence value per share further decreases.
Similarly, we can have a range of projected fair values, on changing our estimates of ROE. A 30% ROE throughout the high growth period bumps up the projected fair value to ~ Rs. 287 per share

Using Goal Seek to force the projected fair value to the issue price of Rs. 375 per share revere calculates the ROE to be 33.8% during the high growth period

What this means is that any ROE assumption above 33.8% would make the issue under-priced

No doubt, this method is very simple when compared to the full-blown financial modelling we did in using FCF method of valuation we saw in the valuation of LT Foods . Limited financial history (as presented in the RHP) constrains our ability to work with past data and project it into the future. This again makes the use of other valuation models perhaps untenable since they require a lot of assumptions to be taken. Hence, this makes the straight forward Excess Return Model very powerful to use for Financial Services firms specially when operational history is limited.

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