Correspondence 0001829126-23-007901 from Fyntechnical Innovations Inc (FYNN)
Fyntechnical Innovations Inc
Date: Dec. 7, 2023 · CIK: 0001497230 · Accession: 0001829126-23-007901
AI Filing Summary & Sentiment
File numbers found in text: 000-56558
Letter
United States Securities and Exchange Commission Washington, DC 20549 Filed October 11, 2023 File No. 000-56558
Re: SMC Entertainment, Inc. Amendment No. 1 to Registration Statement on Form 10-12G
Dear Sir or Madam:
Please see our responses to the comments in your November 2, 2023 letter. (The Company filed Amendment No. 2 on November 1, 2023, which addressed some of the prior comments, but is responding here to the comments issued for Amendment No. 1 per your November 2, 2023 letter). To be clear, we just filed Amendment No. 3, and those comments below which indicate the information requested has been added refer to Amendment No. 3.
Form 10-12G/A filed on October 11, 2023
Business, page 1
Comment 1. Please revise your disclosure to clarify you have not identified any acquisition targets.
Response 1. The Registration Statement has been revised to clarify that we have not yet identified any specific acquisition targets.
Comment 2. We note your response to prior comment 4. Please revise to clarify how you obtain the datasets you utilize. For example, it is unclear whether you use only publicly available data or if you use API’s or have access to third-party proprietary datasets, and the costs and limitations associated with each. In addition, provide a more complete discussion regarding the type of artificial intelligence you utilize and specifically how it operates. Your disclosure suggests your AI models use a diverse set of inputs including news stories and sentiment analysis, market indicators, and company fundamentals, among others to inform the decision-making process. Clarify how these inputs are structured and utilized and how they are presented to customers to provide actionable data and how that data can be used by your customers.
Response 2. We use both public and paid sources for input. Most of the input is correlated by amassing the collective data points at the end of business everyday., Our AI/ML algorithms utilize a wide range of datasets to inform their decision-making processes. The AL/ML Algorithm captures between 20 and 30 thousand data points every day from different places. These data points comprise but are not limited to:
Market Data: Real-time and historical price data, trading volumes, bid-ask spreads, and order book information.
Economic Indicators: Macro-economic data such as GDP, inflation rates, and interest rates.
News and Sentiment Analysis: News articles, social media sentiment, and other textual data sources to gauge market sentiment.
Fundamental Data: Company financials, earnings reports, and analyst recommendations.
Alternative Data: Non-traditional data sources are also incorporated to enhance the capabilities. As an example, regarding the financial sector. Buy now pay later tracking, Credit card usage, M1distribution, Fed Data, Etc..
We obtain those datasets from paid data providers like financial data publishers as well as public sources like corporate SEC filings Edgar and Bloomberg etc. The nature of these datasets is both structured and unstructured data. Depending on the source of the dataset, the cost varies. Regarding the AI, we use 3 broader types of algorithms, supervised learning, unsupervised learning and reinforcement Learning.
The SaaS is used to create a projected weighting on each block. In essence creating a customized index basket that is actionable on by the RIA As an example there are 500 stocks in the SP 600 the AI/ML could customize a block minus oil and gas or minus banks. The institution would have access to alerts on a daily basis showing recommended adjustments within their customized block. The RIA or institution would have the decision to act or not act on the alert.
We use AI in various capacities including (but not limited to) the following use cases: RAG based Information retrieval from unstructured data like SEC filings, quarterly reports etc., Text summarization and classification, Predictive analytics using financial metrics, Automatic data enrichment and predictions, Autonomous agents to continuously analyze data, identify missing features, rank and assign based on metrics v Analyze and enhance news stories, structured inputs like analyst ratings etc. All these datasets, 3rd party inputs are internally used to predict various ratings and analysis, but those data are not shown directly to the end users.
The mix of data points is designed to provide actionable alerts to financial institutions the exact set of data points is proprietary to the SaaS platform and the company would like to not divulge it publicly.
Trends in our Addressable Market, page 5
Comment 3. We note your response to prior comment 5 and reissue in part. Please revise to further clarify why ETFs are included in your addressable markets, and to more clearly discuss how they relate to your planned product offerings. In that regard, we note that you appear to operate in the Software-as-a-Service market rather than in the ETF market. In addition, provide a detailed discussion of how your software will extrapolate data from the ETF markets and how this data will be utilized.
Response 3. The Registration Statement has been revised to include a more detailed description of the business operations and plan of operations for the next 12 months, which is essentially to beta test its SaaS Platform with our addressable markets, which are Registered Investment Advisors, CPAs and financial institutions with the goal of selling its SaaS on a subscription basis as described in the Form 10. The Company realizes that the prior language regarding EFT’s has caused confusion, which is seen in several comments, seeking explanations of a very technical nature that a layman, who is not among our target customers, would not understand. Therefore, the Registration Statement has been revised to clarify this, as EFTs are just an example of a type of security that our SaaS can provide data on which can be used by our target customers, who are all financial industry professionals, in their work. Several prior references to EFTs and other securities have been eliminated to avoid this potential confusion. Exactly how our software will extrapolate data from the EFTs (or any other securities) markets is not information that the Company wants to make public in this comment response letter, as this information is part of our intellectual property and would require technical language that has been removed due to prior confusion.
Recent Sales of Unregistered Securities, page 35
Comment 4. We note your response to prior comment 7, and reissue the comment as we are unable to locate the facts relied upon to make the exemption available for all the transactions disclosed here. Please revise to furnish the complete disclosure required by Item 701 of Regulation S-K.
Response 4. The Company believes it has now added all the language requested in this Section. The Company has added language describing the terms of exercise for those convertible instruments referenced, and is not aware of any additional information expressly required in Item 701 of Regulation S-K. In each transaction named, there were no underwriters. None of the transactions qualify as an “offering”. Each transaction discloses the name of the party to whom unregistered securities were issued and reason for issuance (as compensation for services or from the conversion of a convertible promissory note). The use of proceeds referenced in Item 701 thus does not seem to apply here, as none of the sales were for cash, so there were no proceeds received by the Company.
Notes to Consolidated Unaudited Financial Statements Convertible notes payable, page F-8
Comment 5. We note your response to our prior comment 8; however, we note that the balance of convertible notes and accrued interest on the balance sheet as of June 30, 2023 is $1,193,424, but the correspondence shows $1,223,424. Please reconcile the difference. In addition, please revise the tables on page F-9 and F-23 to ensure the numbers are reconciled to the balance sheets numbers.
Response 5. The financial statements have been revised to address the issues raised in this comment.
Business Combinations, page F-12
Comment 6. We note your response to our prior comment 9, however, we cannot locate the information that can address to our comment, so we re-issue the comment. We note your disclosure that you completed the acquisition of Fyniti Global Equities EBT Inc. (“Fyniti”) for 2,500,000 shares of Series B $10.00 Preferred Stock, and you have accounted for the transaction as a business combination under ASC 805. As a result, you recorded goodwill in amount of $25,031,694. In this regard, please address the following: ● It appears you did not recognize any intangibles such as patents, copyrights, trading platforms, etc. in your purchase price allocation. In that regard, please explain how you consider any Fyniti’s existing intangible assets other than goodwill in your allocation. ● It appears you calculate the purchase price using the $10 par value when arriving at the fair value consideration of the series B preferred stock issued. Please explain how you determined $10 represent fair value amount for each series B preferred stock.
Response 6. The intangible assets were accounted for in our September financial statements and goodwill was adjusted and recalculated to reflect same. The purchase price was based on the valuation represented in the CBV pages 21 -28 a detailed breakdown is shown in the Registration Statement. The Preferred Stock was issued for a prior acquisition which was unwound. The Preferred Stock was on the books in Nevada and we reallocated it for use in the acquisition of Finiti. A copy of the issuance from Nevada has been included as an exhibit.
Subsequent events
Unaudited Pro Forma condensed combined financial information, page F-28
Comment 7. We note your response to prior comment 11, that you has provided the audited financial statements of Fyniti Global Equities EBT Inc. as of and for period ended June 30, 2023. However, it appears that you have filed an incorrect set of financial statements. Further, the financial statements are not consistent with the financial statement reporting periods provided in your pro forma financial statements. Please provide audited financial statements of Fyniti Global Equities EBT Inc. for the correct reporting periods as required by Rule 8-04 of Regulation S-X. In addition, please clarify whether Fyniti Global Equities’ date of inception is truly February 14, 2023. In this regard, we note that the pro forma information includes financial information for periods during and as of December 31, 2022.
Response 7. The Proforma now shows the correct September numbers. The Proforma period is from February 12, 2023 until March 31, 2023, after which the audited financials are shown on a consolidated basis going forward.
Comment 8. We noted your disclosure that Mr. Jayakumar Gopalan, co-founded and president of Fyniti, has contributed intangible assets, valued at $14,550,000 during the period ended June 30, 2023. In this regard, please address the following: ● Please explain the reason these intangible assets contribution transaction was not disclosed as related party transaction. ● Please provide us an analysis to show how you valued and accounted for these intangible assets were contributed by Mr. Gopalan, valued at $14,550,000. Please include reference to the specific accounting literature relied upon. In this regard, tell us what consideration you gave to recording this transfer of technology between entities under common control based on its carryover basis. Refer to ASC 805-30.
Response 8. Please see the and the analysis is outlined in a Certified Business Valuation that has been added as an Exhibit.
Additionally, Jay Gopalan had no prior involvement with SMC before the acquisition of Fyniti by SMC. Jay Gopalan had a relationship with the previous company in Texas. SMC did not have a relationship with the Texas company. SMC only wanted to acquire the SaaS portion of the Platform from the Texas company. Jay Gopalan was involved with the company in Texas and was the owner of the assets acquired. As part of the SaaS acquisition team Jay Gopalan agreed to run the division for SMC. Prior to the acquisition going into effect. Jay was not affiliated, held no position at SMC and he was not an employee nor consultant. There was no arm’s length negotiation with Jay and SMC Jay negotiated with the Texas company and SMC negotiated with only Jay Gopalan.
The company has had a CBV (Certified Business Valuation) performed and it has been attached as an exhibit. Please see pages 21 through 24 of the CBV for corresponding valuation information.
Startup companies can review several methods and calculations to determine value. The Discounted Cash Flow (DCF) estimates several years of cash flows and is useful when the forecast has a reasonable confidence level. The Terminal Value applies the last forecasted year of earnings to an industry selling multiple which is useful when the cash flow expectations has a reasonable confidence level and the cash flow comes in the latter forecasted years. The Net Asset Value is the market value of the assets less the market value of the liabilities and is useful when companies are in the early stages and value is best represented by the assets and liabilities. If companies are in the early stages and have raised capital at an agreed upon valuation, the Prior Transaction Method (Market Approach) can be useful. The Funding Method is a general rule that capitalizes the company based on a multiple of funds being raised. The DCF was weighted 0.00%; the Terminal Value was weighted 0.00%; the Net Asset Value was weighted 100.00%; the Prior Transaction Method was weighted 0.00% and the Funding Method was weighted 0.00%. This allocation best represents the Fair Market Value.
ALLOCATION CONCLUSION SMC Entertainment Fyniti Global EBT is valued at approximately $20,298,635 for the enterprise value. Because the company is a startup, the Terminal Value Method was reviewed rather than the Selling Multiples Method that applies the latest income stream to an industry multiple. As a company that resembles a startup business (larger expected ramp up in revenues, margins or intangible assets) the Terminal Value Method, the Discounted Cash Flow Method, the Net Asset Value, and if available, the Prior Transaction Method have been reviewed to estimate enterprise value.
Comment 9. Please provide a detailed analysis of whether Fyniti Global Equities EBT Inc. qualifies as a business under Rule 11-01(d) of Regulation S-X and as defined by ASC 805-10. This analysis should support your conclusion that the assets acquired and liabilities assumed constitute a business. If the assets acquired are not a business, the reporting entity shall account for the transaction as an asset acquisition. Please advise. General 10. Please refile your exhibits in the proper text-searchable format. For guidance, refer to Section 5.2.3.6 of the EDGAR File Manual (Volume II) EDGAR Filing (Version 60, December 2021) and Item 301 of Regulation S-T.
Response 9. The Company evaluated whether the purchase was a “business” under ASC 805-10-55 based on the following criteria: The FASB issued new guidance, ASU 2017-01, Business Combinations (Topic 815): Clarifying the Definition of a Business, in January 2017 that changes the definition of a business. The new definition is expected to reduce the number of transactions that are accounted for as a business combination across all industries. Broadly speaking, when determining if an integrated set is a business (i.e., the set of activities and/or assets being evaluated when assessing whether that “set” is a busine
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SMC ENTERTAINMENT, INC.
9170 GLADES ROAD, SUITE 150
BOCA RATON, FL 33434
December 7, 2023
United States Securities and
Exchange Commission
Washington, DC 20549
Re:
SMC Entertainment, Inc.
Amendment No. 1 to Registration Statement on Form 10-12G
Filed October 11, 2023
File No. 000-56558
Dear Sir or Madam:
Please see our responses to the comments in your November 2, 2023 letter. (The Company filed Amendment No. 2 on November 1, 2023, which addressed some of the prior comments, but is responding here to the comments issued for Amendment No. 1 per your November 2, 2023 letter). To be clear, we just filed Amendment No. 3, and those comments below which indicate the information requested has been added refer to Amendment No. 3.
Form 10-12G/A filed on October 11, 2023
Business, page 1
Comment 1. Please revise your disclosure to clarify you have not identified any acquisition targets.
Response 1. The Registration Statement has been revised to clarify that we have not yet identified any specific acquisition targets.
Comment 2. We note your response to prior comment 4. Please revise to clarify how you obtain the datasets you utilize. For example, it is unclear whether you use only publicly available data or if you use API’s or have access to third-party proprietary datasets, and the costs and limitations associated with each. In addition, provide a more complete discussion regarding the type of artificial intelligence you utilize and specifically how it operates. Your disclosure suggests your AI models use a diverse set of inputs including news stories and sentiment analysis, market indicators, and company fundamentals, among others to inform the decision-making process. Clarify how these inputs are structured and utilized and how they are presented to customers to provide actionable data and how that data can be used by your customers.
Response 2. We use both public and paid sources for input. Most of the input is correlated by amassing the collective data points at the end of business everyday., Our AI/ML algorithms utilize a wide range of datasets to inform their decision-making processes. The AL/ML Algorithm captures between 20 and 30 thousand data points every day from different places. These data points comprise but are not limited to:
Market Data: Real-time and historical price data, trading volumes, bid-ask spreads, and order book information.
Economic Indicators: Macro-economic data such as GDP, inflation rates, and interest rates.
News and Sentiment Analysis: News articles, social media sentiment, and other textual data sources to gauge market sentiment.
Fundamental Data: Company financials, earnings reports, and analyst recommendations.
Alternative Data: Non-traditional data sources are also incorporated to enhance the capabilities. As an example, regarding the financial sector. Buy now pay later tracking, Credit card usage, M1distribution, Fed Data, Etc..
We obtain those datasets from paid data providers like financial data publishers as well as public sources like corporate SEC filings Edgar and Bloomberg etc. The nature of these datasets is both structured and unstructured data. Depending on the source of the dataset, the cost varies. Regarding the AI, we use 3 broader types of algorithms, supervised learning, unsupervised learning and reinforcement Learning.
The SaaS is used to create a projected weighting on each block. In essence creating a customized index basket that is actionable on by the RIA As an example there are 500 stocks in the SP 600 the AI/ML could customize a block minus oil and gas or minus banks. The institution would have access to alerts on a daily basis showing recommended adjustments within their customized block. The RIA or institution would have the decision to act or not act on the alert.
We use AI in various capacities including (but
not limited to) the following use cases: RAG based Information retrieval from unstructured data like SEC filings, quarterly reports
etc., Text summarization and classification, Predictive analytics using financial metrics, Automatic data enrichment and
predictions, Autonomous agents to continuously analyze data, identify missing features, rank and assign based on metrics v Analyze
and enhance news stories, structured inputs like analyst ratings etc. All these datasets, 3rd party inputs are internally used to
predict various ratings and analysis, but those data are not shown directly to the end users.
The mix of data points is designed to provide actionable alerts to financial institutions the exact set of data points is proprietary to the SaaS platform and the company would like to not divulge it publicly.
Trends in our Addressable Market, page 5
Comment 3. We note your response to prior comment 5 and reissue in part. Please revise to further clarify why ETFs are included in your addressable markets, and to more clearly discuss how they relate to your planned product offerings. In that regard, we note that you appear to operate in the Software-as-a-Service market rather than in the ETF market. In addition, provide a detailed discussion of how your software will extrapolate data from the ETF markets and how this data will be utilized.
2
Response 3. The Registration Statement has been revised to include a more detailed description of the business operations and plan of operations for the next 12 months, which is essentially to beta test its SaaS Platform with our addressable markets, which are Registered Investment Advisors, CPAs and financial institutions with the goal of selling its SaaS on a subscription basis as described in the Form 10. The Company realizes that the prior language regarding EFT’s has caused confusion, which is seen in several comments, seeking explanations of a very technical nature that a layman, who is not among our target customers, would not understand. Therefore, the Registration Statement has been revised to clarify this, as EFTs are just an example of a type of security that our SaaS can provide data on which can be used by our target customers, who are all financial industry professionals, in their work. Several prior references to EFTs and other securities have been eliminated to avoid this potential confusion. Exactly how our software will extrapolate data from the EFTs (or any other securities) markets is not information that the Company wants to make public in this comment response letter, as this information is part of our intellectual property and would require technical language that has been removed due to prior confusion.
Recent Sales of Unregistered Securities, page 35
Comment 4. We note your response to prior comment 7, and reissue the comment as we are unable to locate the facts relied upon to make the exemption available for all the transactions disclosed here. Please revise to furnish the complete disclosure required by Item 701 of Regulation S-K.
Response 4. The Company believes it has now added all the language requested in this Section. The Company has added language describing the terms of exercise for those convertible instruments referenced, and is not aware of any additional information expressly required in Item 701 of Regulation S-K. In each transaction named, there were no underwriters. None of the transactions qualify as an “offering”. Each transaction discloses the name of the party to whom unregistered securities were issued and reason for issuance (as compensation for services or from the conversion of a convertible promissory note). The use of proceeds referenced in Item 701 thus does not seem to apply here, as none of the sales were for cash, so there were no proceeds received by the Company.
Notes to Consolidated Unaudited Financial Statements Convertible notes payable, page F-8
Comment 5. We note your response to our prior comment 8; however, we note that the balance of convertible notes and accrued interest on the balance sheet as of June 30, 2023 is $1,193,424, but the correspondence shows $1,223,424. Please reconcile the difference. In addition, please revise the tables on page F-9 and F-23 to ensure the numbers are reconciled to the balance sheets numbers.
Response 5. The financial statements have been revised to address the issues raised in this comment.
3
Business Combinations, page F-12
Comment 6. We note your response to our prior comment 9, however, we cannot locate the information that can address to our comment, so we re-issue the comment. We note your disclosure that you completed the acquisition of Fyniti Global Equities EBT Inc. (“Fyniti”) for 2,500,000 shares of Series B $10.00 Preferred Stock, and you have accounted for the transaction as a business combination under ASC 805. As a result, you recorded goodwill in amount of $25,031,694. In this regard, please address the following: ● It appears you did not recognize any intangibles such as patents, copyrights, trading platforms, etc. in your purchase price allocation. In that regard, please explain how you consider any Fyniti’s existing intangible assets other than goodwill in your allocation. ● It appears you calculate the purchase price using the $10 par value when arriving at the fair value consideration of the series B preferred stock issued. Please explain how you determined $10 represent fair value amount for each series B preferred stock.
Response 6. The intangible assets were accounted for in our September financial statements and goodwill was adjusted and recalculated to reflect same. The purchase price was based on the valuation represented in the CBV pages 21 -28 a detailed breakdown is shown in the Registration Statement. The Preferred Stock was issued for a prior acquisition which was unwound. The Preferred Stock was on the books in Nevada and we reallocated it for use in the acquisition of Finiti. A copy of the issuance from Nevada has been included as an exhibit.
Subsequent events
Unaudited Pro Forma condensed combined financial information, page F-28
Comment 7. We note your response to prior comment 11, that you has provided the audited financial statements of Fyniti Global Equities EBT Inc. as of and for period ended June 30, 2023. However, it appears that you have filed an incorrect set of financial statements. Further, the financial statements are not consistent with the financial statement reporting periods provided in your pro forma financial statements. Please provide audited financial statements of Fyniti Global Equities EBT Inc. for the correct reporting periods as required by Rule 8-04 of Regulation S-X. In addition, please clarify whether Fyniti Global Equities’ date of inception is truly February 14, 2023. In this regard, we note that the pro forma information includes financial information for periods during and as of December 31, 2022.
Response 7. The Proforma now shows the correct September numbers. The Proforma period is from February 12, 2023 until March 31, 2023, after which the audited financials are shown on a consolidated basis going forward.
Comment 8. We noted your disclosure that Mr. Jayakumar Gopalan, co-founded and president of Fyniti, has contributed intangible assets, valued at $14,550,000 during the period ended June 30, 2023. In this regard, please address the following: ● Please explain the reason these intangible assets contribution transaction was not disclosed as related party transaction. ● Please provide us an analysis to show how you valued and accounted for these intangible assets were contributed by Mr. Gopalan, valued at $14,550,000. Please include reference to the specific accounting literature relied upon. In this regard, tell us what consideration you gave to recording this transfer of technology between entities under common control based on its carryover basis. Refer to ASC 805-30.
4
Response 8. Please see the and the analysis is outlined in a Certified Business Valuation that has been added as an Exhibit.
Additionally, Jay Gopalan had no prior involvement with SMC before the acquisition of Fyniti by SMC. Jay Gopalan had a relationship with the previous company in Texas. SMC did not have a relationship with the Texas company. SMC only wanted to acquire the SaaS portion of the Platform from the Texas company. Jay Gopalan was involved with the company in Texas and was the owner of the assets acquired. As part of the SaaS acquisition team Jay Gopalan agreed to run the division for SMC. Prior to the acquisition going into effect. Jay was not affiliated, held no position at SMC and he was not an employee nor consultant. There was no arm’s length negotiation with Jay and SMC Jay negotiated with the Texas company and SMC negotiated with only Jay Gopalan.
The company has had a CBV (Certified Business Valuation) performed and it has been attached as an exhibit. Please see pages 21 through 24 of the CBV for corresponding valuation information.
Startup companies can review several methods and calculations to determine value. The Discounted Cash Flow (DCF) estimates several years of cash flows and is useful when the forecast has a reasonable confidence level. The Terminal Value applies the last forecasted year of earnings to an industry selling multiple which is useful when the cash flow expectations has a reasonable confidence level and the cash flow comes in the latter forecasted years. The Net Asset Value is the market value of the assets less the market value of the liabilities and is useful when companies are in the early stages and value is best represented by the assets and liabilities. If companies are in the early stages and have raised capital at an agreed upon valuation, the Prior Transaction Method (Market Approach) can be useful. The Funding Method is a general rule that capitalizes the company based on a multiple of funds being raised. The DCF was weighted 0.00%; the Terminal Value was weighted 0.00%; the Net Asset Value was weighted 100.00%; the Prior Transaction Method was weighted 0.00% and the Funding Method was weighted 0.00%. This allocation best represents the Fair Market Value.
ALLOCATION CONCLUSION SMC Entertainment Fyniti Global EBT is valued at approximately $20,298,635 for the enterprise value. Because the company is a startup, the Terminal Value Method was reviewed rather than the Selling Multiples Method that applies the latest income stream to an industry multiple. As a company that resembles a startup business (larger expected ramp up in revenues, margins or intangible assets) the Terminal Value Method, the Discounted Cash Flow Method, the Net Asset Value, and if available, the Prior Transaction Method have been reviewed to estimate enterprise value.
Comment 9. Please provide a detailed analysis of whether Fyniti Global Equities EBT Inc. qualifies as a business under Rule 11-01(d) of Regulation S-X and as defined by ASC 805-10. This analysis should support your conclusion that the assets acquired and liabilities assumed constitute a business. If the assets acquired are not a business, the reporting entity shall account for the transaction as an asset acquisition. Please advise. General 10. Please refile your exhibits in the proper text-searchable format. For guidance, refer to Section 5.2.3.6 of the EDGAR File Manual (Volume II) EDGAR Filing (Version 60, December 2021) and Item 301 of Regulation S-T.
5
Response 9. The Company evaluated whether the purchase was a “business” under ASC 805-10-55 based on the following criteria: The FASB issued new guidance, ASU 2017-01, Business Combinations (Topic 815): Clarifying the Definition of a Business, in January 2017 that changes the definition of a business. The new definition is expected to reduce the number of transactions that are accounted for as a business combination across all industries. Broadly speaking, when determining if an integrated set is a business (i.e., the set of activities and/or assets being evaluated when assessing whether that “set” is a busine