FinDaS Tokenomics Philosophy

The concepts behind FinDaS existed before the company did. The three words in the tagline (bespoke, data-driven, sustainable) are not a marketing exercise. Each one is a reaction to a specific failure mode I watched play out at a different point in the early tokenomics market, and I structured the firm around not repeating those failures.

Before FinDaS: customer behaviour modeling at scale

For two years before crypto, I worked as analytics director at one of the largest consumer finance companies in China. The work was customer behaviour modeling, P&L projections, and analytics on lending portfolios at a scale that does not really exist in crypto: tens of millions of customers, billions of yuan in originations, real cohort analysis with multi-year retention windows. None of that maps directly onto tokenomics. The underlying skill, building financial models that survive contact with messy real-world data, is the same skill the median tokenomics document is missing.

2018, Bulgaria, and a job called "tokenomics" before the word existed

I came back to Bulgaria in early 2018 and went full-time in crypto. Most of my work for the next two years came through Upwork, working with whatever projects were figuring out how to ship a token. Almost by accident, I ended up doing what would later be called tokenomics for several of them. The word was not really in use yet, but the work fit my skill set: financial modeling, customer behaviour analysis, and the kind of cohort thinking that crypto projects almost universally were not doing.

Those two years were experimentation. I tested supply schedules, distribution models, vesting structures, incentive loops, and reward sinks against actual project goals rather than against whatever the previous launch had done. Some of those experiments held up. Most did not. By the end of that period the pattern was obvious enough that I could state it: most projects had no idea what they were doing with their token economy, and a worrying number were just copy-pasting from whichever launch had recently looked successful.

That was where the data-driven pillar came from. Absent any real financial modeling, every claim about how a token would behave was someone's intuition with extra steps. Two years of evidence said intuition with extra steps does not survive a cycle.

Founding FinDaS and the DeFi summer scaling lesson

Demand grew faster than I expected through 2019 and into 2020. By that point I could not meet it on my own. I founded FinDaS in 2020, started hiring, and walked straight into DeFi summer. The team grew to six token economists. We were running six to seven projects per month with a six-month waiting list, and most months we were turning more work away than we were taking on. By the volume metrics, that period looks like the success story you put on a marketing page.

It was not. The output quality was not what I wanted it to be. Tokenomics turns out to be hard to teach. It is a load-bearing combination of finance, behavioural modeling, mechanism design, and pattern recognition built from seeing dozens of projects fail in specific ways, and most of those skills are individually slow to develop. Hiring fast and hoping the team would converge on quality through volume was the wrong bet. By the end of that period the work going out the door was inconsistent enough that I made the call to drastically reduce the team.

I shrunk it to two: myself and Diana Ilieva. Every FinDaS engagement since runs with both of us directly involved, not as reviewers or escalation paths, but as the people doing the modeling, talking to founders, and writing the actual recommendations. That is not scalable in the conventional sense. It is the point. We turn work away every month and our pipeline runs longer than most clients want, but the marginal cost of getting tokenomics wrong is high enough to justify senior-level attention on every engagement. Those are the right trade-offs to make. They are also not costless, and I would not pretend otherwise.

Sustainable: tokenomics for the project, not the exit

The same two years that taught me what hiring fast does to quality also showed me, from the outside, what most of the market was actually building. Across hundreds of engagements a pattern became visible. A lot of tokenomics in that period was not built for the project. It was built for the venture investors backing the round, or for founders trying to time a quick exit. The mechanics that produce those outcomes are well-known: aggressive emissions to support TGE liquidity, unlock schedules tuned for cap-table holders rather than ecosystem health, value capture funneled to the token rather than the operating business, and high enough float at launch to make the early secondary print look real.

That is not tokenomics design. It is the financial structuring of an exit, dressed up as token economics. The project gets handed a token economy that breaks under any sustained pressure, and the people who designed it have already been paid out. Sustainable, the third pillar, is the response. We design tokenomics that the project can run for multiple cycles. That sometimes means saying no to founders who want a more aggressive launch, and it consistently means producing a less marketable narrative for the round. The output survives the cycle. Most of the alternative does not.

Bridge Mutual and what bespoke actually means

Bespoke is the easiest pillar to claim and the hardest to demonstrate. Most consulting firms will tell you they do not use templates. The honest test is whether the output would look meaningfully different across two engagements with genuinely different mechanics. The consulting seat shows you what mechanics need to do. Operating inside a protocol shows you what those mechanics actually do under live conditions. Bridge Mutual was the engagement where I had both seats.

Bridge Mutual was DeFi's first fully decentralized insurance protocol. After designing the tokenomics, I joined as CPO and stayed embedded for nine months post-launch. The design problems were specific enough that nothing off any shelf would have worked.

A two-sided risk marketplace where coverage providers underwrote permissionless policies needed three different kinds of token holder behaviour: passive holders providing baseline liquidity, active stakers earning premium yield, and reputation-weighted governance voters adjudicating contested claims. A single staking layer would have collapsed those incentives into each other. The answer was sequential commitment: BMI to stkBMI to vBMI, with a longer cooldown at each step and stronger protocol rights at each layer. That structure exists in the Bridge Mutual contracts because the protocol's economics required it. It would be the wrong answer for a lending market, a DEX, or almost any other protocol category.

Premium pricing was the same kind of problem. A coverage pool's risk rises with utilization. Letting governance set premiums by vote would have been slow and exploitable. Letting a fixed price persist would have priced risk wrong on both ends. The utilization-ratio curve was the answer, and it was calibrated specifically for Bridge Mutual's pool dynamics: premiums scaled linearly below a risk threshold, steeply above it, with a floor preventing zero-cost coverage. Reputation-weighted claims voting followed the same logic: voting power tied to historical accuracy, with stake penalties for outlier votes, designed for the specific governance decision claims voters had to make.

Bridge Mutual peaked at roughly $150M TVL against a business-model threshold of about $500M. The case study covers why, in detail. The short version is that the architecture worked, and the market for decentralized insurance in 2021 was smaller than the TVL needed to make the model self-sustaining. What the engagement demonstrated about bespoke design is not that it guarantees commercial success. It is that the same design problems do not have the same answers across protocols, and consulting firms running on templates ship work that looks broadly similar to whatever they delivered last quarter. FinDaS does not.

Why we stay focused while web3 shops consolidate

In 2026 the visible trend is consolidation. Web3 service shops are stacking offerings: tokenomics plus marketing plus development plus market making, sometimes plus token launch infrastructure on top of that. The pitch is simplicity for the founder. The reality is that every additional service introduces a conflict of interest with the tokenomics output.

One worked example covers most of the space. Take a project using the same firm for tokenomics and market making. Market makers are usually paid in a token loan with a buy-side option at a strike near launch. Their incentive is for the token to land in a tight, predictable range during the loan period: too volatile and delta-hedging gets expensive, too high and the call option is deep in the money but the loan is now worth more than they can return at expiry. The tokenomics that serves that incentive has a specific shape: tight initial float, scheduled token sinks the MM can model in advance, no surprise unlock cliffs during the loan window, and a utility narrative that does not draw fresh buy-side pressure they would have to absorb. None of those design choices are wrong for a project in isolation. They are wrong as a package, because the package is shaped by the MM's payoff curve rather than by the project's growth path. The same logic applies to a marketing firm pulling tokenomics toward whatever narrative is easiest to sell, or a launch services firm tuning the supply schedule to whatever makes the listing print well.

None of those incentive distortions are illegal, and most of them are not visible to the founder while they are happening. They show up two cycles later, in the part of the project's life nobody photographs.

FinDaS has had several opportunities to expand into adjacent services. Adding marketing, development, or market making to the scope would have been straightforward and revenue-positive. We chose not to. The result is a smaller business than it could have been, and the work that goes out the door is built for the project rather than for whichever adjacent margin we could have captured around it.

Hristo Piyankov

Lead token economist

Hristo is one of the best-known tokenomics designers in the industry. He is a top Web3 LinkedIn voice and a mentor in several high-profile accelerators such as Brinc and HyperNest. Hristo teaches a university masters degree in Cryptoeconomics and Decentralised Finance (DeFi). Having worked on over 300 tokenomics projects, he knows the ins and outs of token economies, what works and what does not.

Prior to working in crypto, Hristo was an Analytics Director and a Data Scientist for 12+ years in TradFi.