Press Release
PayYoda analyzing the Blockchain payment characteristics and putting forward the Blockchain payment security reference
The industrial circle and academic circle have begun to realize the importance and value of Blockchain payment security, and have carried out active exploration now. However, the current Blockchain payment is still in the early stage of industrial development with systematic study lacked. PayYoda analyzes the Blockchain payment security demand characteristics and defines the Blockchain payment security boundary, laying the foundation of Blockchain payment security reference frame.
Blockchain payment problem: Serious security privacy problem and lack of trust between both parties of the transaction
The traditional payment way is always of high risk, poor efficiency and many restrictions. Especially for the international trade, the buyer shall transfer money to the supplier’s account which needs to be confirmed by many international banks midway with complicated formalities and a long time taken (varying from several days to ten days and a half months) after a deal is closed. More importantly, the account is often frozen for no reason and the high service charge needs to be paid in the whole process because all countries have strict regulations on the amount and types of transactions when international payment. Furthermore, the centralized settlement system is with non-transparent data and unsafe hidden dangers, so the personal information may be disclosed.

Based on the problem, PayYoda puts forward the solution:
I. Credit-driven ecosystem
PayYoda constructs the credit-driven ecosystem by the credit scoring system to solve the security payment problem. Various payment security accidents (including merchant fraud, malicious user attack, phishing site and privacy disclosure) happen to the online payment and offline payment. How to create a safe payment environment becomes the high-priority tasks of all the payment networks.
The PayYoda ecosphere is credit-driven. To achieve the goal, related measures (including credit-driven ecology, merchant caution money, safety fund, privacy protection, credit score, and decentralized risk control anti-fraud) shall be taken to ensure the user asset security in many fields thoroughly.
II. Publicity, transparency and traceability
In addition to this, PayYoda’s strategy is solving the data source and data trust problems by its hardware equipment with machine language, and ensuring the data authenticity of the whole chain based on Blockchain characteristics-decentralization and immutability. The PayYoda’s design ensures the payment transaction data security in the process of acquisition, transmission, storage and computation with stable and reliable technology platform provided for data transmission and value circulation on the digital asset trading.
III. Decentralizing the payment on the Blockchain
After PayYoda implements the actual scenario of digital currency and realizes the integration with payment transactions via Blockchain, it won’t rely on the system in the central position for fund clearing and trading information storage any longer, but can transfer the value directly based on consensus mechanism which doesn’t need any trust coordination. The mechanism transformation result is as follows: On one hand, the huge service cost and maintenance costs of the third party of the third party institution are saved, the business process is simplified and the business costs for banks and customers are lowered; On the other hand, the flattening of the process increases the transfer speed and realizes the real-time transfer, and the security of the whole system can be ensured even though multiple nodes are attacked because a complete set of data copies is stored at each node of the system.
IV. Secure trading system based on artificial intelligence
The PayYoda secure trading protection system is based on multi-core concurrent technology, integrated safety engine technology, zero-copy technique, and other high performance architectures. It integrates ten layers of fine filtering function based on data header and data content (including DOS defense, user authentication, application control, intrusion prevention, site classification and filtering, virus filtration, web application defense and data leak prevention), forms the integrated security defense system from the network layer to the application layer, and realizes the clean flow delivery.
On the basis of artificial intelligence, PayYoda provides such abilities as data analysis, knowledge extraction, independent study, intelligent decision and automatic control which can create the innovative applications in the fields of network information security (such as network protection, data management, message audit, intelligent security and financial risk control).
V. Construction of sustainable payment ecosystem
The sustainable evolution of the platform (as the basic payment network) is of great importance. And the continuous evolution of the platform happens due to sustainable innovation ability in the premise of abiding by common rules. The common rules of the platform are ensured by the governance mechanism and consensus mechanism. As for the innovation, the development history of e-payment in these decades clearly shows: As long as the power is given to the innovators closest to the market, there will always be an endless supply of ideas. In terms of governance mechanism, PayYoda adopts the fully open ecological model so that the ecosphere participants can focus on the tasks they are best at and maximize their respective profits by the corresponding incentive mechanism with innovation driven via the market end.
PayYoda will continue to be rooted in the Blockchain-fertile soil and cooperate with various financial institutions and entity industries to build the decentralized payment ecology together based on Blockchain in the future!
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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
New Report Reveals Significant Gap Between Corporate AI Effectiveness and Expectations
The State of AI at Work, published by Kristian Kabashi and The Blank Collar, shows that adoption is widespread, but 87% of users are still beginners
Switzerland, 24th Jun 2026 — Kristian Kabashi, the technology executive and analyst who developed The Blank Collar transformation practice for the intelligence age, today announced the publication of a new field report, The State of AI at Work. The report reveals a significant gap between corporate expectations of artificial intelligence (AI) in the workplace versus actual results. The report shows that while AI adoption is widespread, 87% of workers use AI at the beginner level. Just 13% use AI for meaningful work.
According to Kabashi, “Your company bought AI, but nobody changed. At some level, we’ve seen this with every major technology shift over the years, but in the case of AI, these results are quite disappointing. The technology has such vast promise, but, in my view, it’s not being used the right way.”
The Zurich-based Kabashi comes to his perspective on AI after spending two decades as a creative, a builder, and a transformer. He served in senior executive roles in global enterprises such as Dentsu and the Havas agency, as well as being the founder of Cybee.ai and the AI company Numarics, which was acquired in 2024.
The Blank Collar has been Kabashi’s philosophical home since 2018. The Blank Collar’s slogan is, “Work is for bots. Life is for humans.” It is the successor to the idea of white-collar employment. While blue collars built the industrial age, and white collars led the way in the information age, blank collars will build the intelligence age—directing AI agents instead of doing the routine work themselves.
The problem, as Kabashi sees it, is that so few workers move past the experimenter line into work that pays for itself. What blocks proficiency is not prompting. “People can learn to in an afternoon,” Kabashi said. “They get stuck one step earlier, on a blank question, which is ‘What do I even point this at?’ They open the tool, summarize one email, and bounce, because nothing in the actual job comes pre-labeled, give this to AI.”
Kabashi calls this the “use case desert.” The real issue, in his view, however, is a lack of leadership. “I don’t want to point fingers. This is all so new, it’s not surprising that senior executives aren’t quite plugged into what’s going to work. But, everyone better get busy pretty soon, because the companies that figure this out—who can rise above 13% meaningful AI use—are going to be strong competitive performers.”
To learn more, visit https://www.theblankcollar.com/
To download the report, visit https://www.theblankcollar.com/reports/the-state-of-ai-at-work.pdf
About The Blank Collar
The Blank Collar is a philosophy, a framework, and an engine, a transformation practice for the intelligence age. The term was coined in 2016. The practice was founded in 2018. By the time the world had a vocabulary for what was coming, The Blank Collar already had a thesis, a method, and a name. The term “Blank Collar” refers to a new kind of professional who works alongside AI agents, directing, orchestrating, framing, and keeping what no machine can take.
Media Contact
Organization: The Blank Collar
Contact Person: Kristian Kabashi
Website: https://www.theblankcollar.com
Email: Send Email
Country:Switzerland
Release id:46443
The post New Report Reveals Significant Gap Between Corporate AI Effectiveness and Expectations appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Dental Pitch Releases 2026 Dental Practice Valuation Guidance
Dental Pitch Advisory & Brokerage has released its 2026 dental practice valuation guidance to help practice owners better understand the financial and operational factors buyers evaluate before a sale. The guidance explains why modern dental practice valuation is no longer based on collections alone, but on EBITDA, Quality of Earnings, expense benchmarks, valuation multiples, clean financial documentation, provider dependence, hygiene performance, growth potential, and transferability after closing. Dental Pitch emphasizes that stronger sale outcomes are created through preparation, not guesswork, and that practice value is built, documented, defended, and positioned before going to market.
Atlanta, GA, United States, 24th Jun 2026- Dental Pitch Advisory & Brokerage, a seller-side dental practice advisory and brokerage firm, has released new 2026 dental practice valuation guidance to help dentists understand what their practice is worth — and how to protect that value before going to market.

The guidance addresses the most common questions dentists ask when preparing for a sale: how much is my dental practice worth, what drives dental practice valuation multiples, how dental office expense percentages affect EBITDA, and what it takes to earn a defensible number buyers will not renegotiate in due diligence.
“Revenue still matters, but it is no longer enough to simply show strong collections,” said Dental Pitch Advisory & Brokerage. “The practices that sell for the strongest outcomes have clean financials, healthy EBITDA margins, documented systems, stable teams, strong hygiene production, and a clear story that gives buyers confidence.”
EBITDA Is the Primary Driver of Dental Practice Valuation in 2026
According to Dental Pitch, EBITDA dental practice valuation has become the standard methodology used by DSOs, private equity-backed groups, and sophisticated private buyers. EBITDA — earnings before interest, taxes, depreciation, and amortization — measures how efficiently a practice converts revenue into operating profit, independent of how the owner is compensated or how the practice is financed.
A well-run general dental practice typically generates an EBITDA margin of 18% to 22% of net collections. Practices pushing 20% or higher may attract stronger buyer interest and more favorable dental practice valuation multiples. In cases where doctor compensation is properly normalized and overhead is controlled, normalized EBITDA margins can reach 25% to 29%.
Dental Pitch advises sellers that EBITDA must be clean, documented, and defensible — supported by organized financials, properly categorized add-backs, and a compensation structure buyers can understand and validate.
Dental Office Expense Percentages Are a Direct Signal of Practice Health
As part of its 2026 valuation guidance, Dental Pitch has published updated dental office expense percentage benchmarks to help sellers compare their cost structure against what healthy, well-run practices typically spend. Buyers use these benchmarks to evaluate efficiency, flag risk, and stress-test EBITDA before making offers.
Healthy 2026 ranges as a percentage of net collections include: doctor compensation at 22% to 25%, total team labor at 30% to 33%, dental supplies and lab combined at 11% to 13%, occupancy at 6% to 7%, marketing at 2% to 4%, and G&A at 6% to 8%.
“When expenses fall outside these ranges, buyers ask harder questions,” said Dental Pitch Advisory & Brokerage. “When expense performance is clean and well-documented, it reinforces EBITDA and supports the valuation — rather than creating room for buyers to push back.”
Dental Pitch works with sellers to identify where overhead improvements can meaningfully increase EBITDA before a practice goes to market. At current multiples, every dollar of overhead reduction that flows through to EBITDA can add $5 to $8 of practice value. Full benchmark guide: Dental Office Expense Percentages — 2026 Guide.
2026 Dental Practice Valuation Multiples Reward Earnings Quality
Dental Pitch’s 2026 guidance outlines the following general dental practice valuation multiples based on normalized EBITDA size:
- $200K–$500K EBITDA: 4x to 6x
- $500K–$1M EBITDA: 5x to 7x
- $1M–$2M EBITDA: 6.5x to 8x
- $2M+ EBITDA: 8x and above
Dental Pitch emphasizes that these multiples are not automatic. They are earned through earnings quality, consistency, provider diversity, hygiene strength, operational documentation, and buyer competition. Practices below $200,000 in EBITDA are often evaluated differently, with value more closely tied to collections, location, and buyer fit. Complete breakdown: Dental Practice Valuation Multiples 2026.
Quality of Earnings Protects Valuation Through Due Diligence
Beyond the valuation number, Dental Pitch advises sellers on Quality of Earnings — the process of determining whether EBITDA is accurate, recurring, and defensible under buyer scrutiny. A strong Quality of Earnings story reduces the risk of valuation renegotiation after a letter of intent is signed.
Quality of Earnings reviews may examine revenue consistency, collections trends, hygiene performance, add-back documentation, payer mix, payroll structure, and operational risks. Dental Pitch’s QoE Lite process is designed specifically for dental transactions — lighter and faster than a full third-party engagement, and focused on the variables buyers actually scrutinize. Dental Practice Valuation: Why Sellers Need a QOE Lite Before Buyers Do.
“A valuation gives a number. A Quality of Earnings review explains and defends that number,” said Dental Pitch Advisory & Brokerage. “Sellers who go to market with both are in a fundamentally stronger position than sellers who have only one.” Read more https://dentalpitchbrokerage.com/dental-practice-valuation-qoe-lite/
About Dental Pitch Advisory & Brokerage
Dental Pitch Advisory & Brokerage is a seller-side dental practice advisory and brokerage firm helping dentists understand dental practice valuation, improve EBITDA, prepare for sale, evaluate buyer options, and transition with confidence. The firm supports single private practices, specialty practices, multi-location groups, and larger dental organizations preparing for sale to private buyers, DSOs, private equity-backed groups, or strategic partners.
For more information, visit dentalpitchbrokerage.com
Media Contact
Organization: Dental Pitch Advisory & Brokerage
Contact Person: Dental Pitch Advisory & Brokerage
Website: https://dentalpitchbrokerage.com/
Email: Send Email
Contact Number: +18336580118
Address:3290 Northside Parkway NW, Suite 825 Atlanta, GA 30327
City: Atlanta
State: GA
Country:United States
Release id:46417
The post Dental Pitch Releases 2026 Dental Practice Valuation Guidance appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Kevin D. Oden & Associates: New Federal Model Risk Guidance (SR 26-2) Leaves Generative and Agentic AI Outside Scope, Shifting the Burden to Institutions
San Francisco, CA, 24th June 2026, ZEX PR WIRE — Kevin D. Oden & Associates (KDOA), a model risk management and quantitative advisory firm, today shared its perspective on SR 26-2, the revised interagency guidance on model risk management issued jointly by the Federal Reserve, the Office of the Comptroller of the Currency, and the FDIC on April 17, 2026.

The revised guidance (SR 26-2, OCC Bulletin 2026-13, and FDIC FIL-15-2026) supersedes the 2011 guidance widely known as SR 11-7, which had governed how banking organizations identify, validate, monitor, and govern quantitative models for fifteen years. The update moves toward a more flexible, principles-based approach that is tailored to an institution’s model risk profile and the size and complexity of its operations. It is expected to be most relevant to banking organizations with more than $30 billion in total assets, though smaller institutions with significant model-risk exposure may also fall within its expectations.
KDOA’s central observation is what the guidance leaves out. SR 26-2 expressly places generative AI and agentic AI models outside its scope, describing them as novel and rapidly evolving. The revised principles apply to traditional statistical and quantitative models. For institutions already deploying AI-driven tools across credit, fraud, BSA/AML, and customer-facing functions, this means there is no regulatory floor specific to those systems. The responsibility to define proportionate governance and controls sits with the institution.
“The agencies modernized the baseline and were deliberate about not extending it to generative and agentic AI,” said Kevin Oden, Managing Partner of Kevin D. Oden & Associates. “That is a reasonable call given how fast the technology is moving, but it does not reduce the risk these systems carry. It relocates the burden. Boards and model risk teams now have to build credible governance for AI without a prescriptive standard to point to, while also re-grounding their traditional model programs in the revised guidance.”
KDOA notes three practical implications for institutions reassessing their programs against SR 26-2:
- Re-baselining is not optional. Policies, validation standards, and inventory taxonomies written against SR 11-7 reference a superseded standard. Programs should be re-mapped to the revised principles, with particular attention to how materiality and a risk-based, tailored approach are documented.
- The AI gap is now an institutional decision. Because generative and agentic AI sit outside the guidance, institutions must decide, document, and defend how those systems are governed under their own risk frameworks. Examiners can still act on unsafe or unsound practices regardless of scope. Separate AI-specific guidance is widely anticipated.
- Proportionality cuts both ways. A principles-based standard gives institutions room to right-size their programs, but it also removes the cover of a checklist. The reasoning behind each control choice has to hold up.
A final point on scope: the exclusion is narrower than it first appears. Only generative and agentic AI fall outside SR 26-2. Traditional statistical and quantitative models remain fully in scope, as do non-generative, non-agentic AI and machine learning models. For most institutions, that means the bulk of their AI/ML footprint, including the conventional machine learning used in credit, fraud, and BSA/AML, is still governed by the revised guidance and has to be re-mapped to it. The open question sits only with the newest generative and agentic systems, which is exactly where the institution, not the regulator, now sets the standard.
KDOA’s validation and governance teams, whose members have held senior model risk roles at institutions including the Federal Reserve, Fannie Mae, Wells Fargo, Bank of America, Lloyds Banking Group, and Varo Bank, are advising clients on re-baselining their programs to the revised guidance.
The firm’s technology platform, Model IQ, supports this work by managing the full model lifecycle in one system, from registration and risk tiering through validation, monitoring, and board reporting. Its program-assessment tooling is being updated to evaluate institutions against the revised guidance, helping teams identify gaps and track remediation as they transition off the 2011 standard.
About Kevin D. Oden & Associates
Kevin D. Oden & Associates provides quantitative analysis, model risk management, and risk advisory services to the financial industry and beyond. The firm’s team includes more than ten PhDs and senior quantitative analysts with experience across credit, market, BSA/AML, fraud, CECL, stress testing, and AI/ML models. KDOA is SOC 2 Type II certified and an NMSDC-certified Minority Business Enterprise. Its Model IQ platform was designed by practicing model risk managers for the teams that run MRM programs day to day.
For more Information, You can Visit: https://kdoden.com
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
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