(product designer)
Makar Kovtunov —
I’m a product designer with 5+ years of experience, working on complex, high-load digital products. I’ve spent the last few years designing systems in fintech and other data-heavy environments, where decisions directly impact user behavior, business processes, and real-world outcomes
Experience
2021——2026
I work end-to-end — from early structuring and defining flows to implementation with development. My focus is on making complex things clear and usable, whether it’s user-facing products or internal tools. Over time, i’ve become comfortable working with ambiguity and complexity, balancing user needs, business goals, and technical constraints. I also actively use AI tools in my workflow to move faster, test ideas, and focus more on product thinking
2023–2026
Mind Money
2022–2023
MoonPay (Contract)
2021–2022
WIXI Ltd OÜ
Cases
Reframing KYC document workflows as an operational system— from fragmented lists to queues, lifecycle and role-based processing
2026
From lists to queues
close ↵
Scaling KYC operations in a fintech platform
Redesigned document workflows for clients, back-office, and compliance teams — from fragmented handling to a structured processing system.
Role
Led design of document processing experience
Scope
— how documents are prioritized and processed by back-office
— how managers review, update, and approve documents
— how clients understand status and what to do next
— reducing manual work and errors in document handling
— how managers review, update, and approve documents
— how clients understand status and what to do next
— reducing manual work and errors in document handling
Platform
Web
CONTEXT
Brokerage platform
Users: Clients / Back-office / Compliance
Documents are processed daily and are part of core product workflows
Brokerage platform
Users: Clients / Back-office / Compliance
Documents are processed daily and are part of core product workflows
PROBLEM (BACK-OFFICCE)
— No queues
— Manual navigation
— No prioritization
— Mixed document types
— No queues
— Manual navigation
— No prioritization
— Mixed document types
PROBLEM (CLIENT)
— Unclear status
— No understanding of next steps
— Unclear status
— No understanding of next steps
SOLUTION (Back-office)
— Introduced processing queues → improved prioritization
— Extended status system → more control over document states
— Table-based workflow → faster high-volume processing
— Introduced processing queues → improved prioritization
— Extended status system → more control over document states
— Table-based workflow → faster high-volume processing
WHY THIS APPROACH
The core issue wasn’t UI inefficiency, but a mismatch between interface and real workflows.
Document processing behaves like an operational system:
— continuous inflow of tasks
— need for prioritisation (deadlines, compliance risk)
— dependency on document states
List-based UI treats items as equal and static → breaks prioritisation and increases cognitive load.
Shifted the model to queue-based processing with a defined lifecycle → aligns interface with actual operational behaviour.
The core issue wasn’t UI inefficiency, but a mismatch between interface and real workflows.
Document processing behaves like an operational system:
— continuous inflow of tasks
— need for prioritisation (deadlines, compliance risk)
— dependency on document states
List-based UI treats items as equal and static → breaks prioritisation and increases cognitive load.
Shifted the model to queue-based processing with a defined lifecycle → aligns interface with actual operational behaviour.
SOLUTION (Clients)
— Simplified statuses → reduced confusion
— Clear next actions → better guidance
— Separated document types (mobile) → easier navigation
— Simplified statuses → reduced confusion
— Clear next actions → better guidance
— Separated document types (mobile) → easier navigation
WHY THIS APPROACH
Clients interact with documents episodically, not operationally
Exposing full lifecycle created unnecessary complexity:
— unclear statuses
— repeated uploads
— support requests
Abstracted internal logic into a simple interaction model: current status + required action → reduces cognitive load while preserving system control internally
Clients interact with documents episodically, not operationally
Exposing full lifecycle created unnecessary complexity:
— unclear statuses
— repeated uploads
— support requests
Abstracted internal logic into a simple interaction model: current status + required action → reduces cognitive load while preserving system control internally
IMPACT (BACK-OFFICE)
— Better visibility of document states
— Improved prioritization and speed workflow
— Reduced time to process documents
— Fewer manual actions per task
— Better visibility of document states
— Improved prioritization and speed workflow
— Reduced time to process documents
— Fewer manual actions per task
IMPACT (CLIENT)
— Less support requests
— Fewer incorrect or repeated uploads
— Better understanding of next steps
— Less support requests
— Fewer incorrect or repeated uploads
— Better understanding of next steps
REFLECTION
— Lifecycle adds control but increases complexity→ next step: simplify without losing structure
— Add document-level prioritization (e.g. urgent / blocking)
— Lifecycle adds control but increases complexity→ next step: simplify without losing structure
— Add document-level prioritization (e.g. urgent / blocking)
Reframed the trading interface from a data-heavy tool into a decision-support system.
Simplified order flows, clarified complex order types, and exposed risk directly in the interface — reducing errors and improving decision quality, especially in margin trading.
Simplified order flows, clarified complex order types, and exposed risk directly in the interface — reducing errors and improving decision quality, especially in margin trading.
2025-2026
Reducing trading errors and risk through terminal redesign
close ↵
Reducing trading errors and risk through terminal redesign
Reframed the trading interface from a data-heavy tool into a decision-support system.
Simplified order flows, clarified complex order types, and exposed risk directly in the interface — reducing errors and improving decision quality, especially in margin trading.
Simplified order flows, clarified complex order types, and exposed risk directly in the interface — reducing errors and improving decision quality, especially in margin trading.
Role
Led design of trading terminal experience
Scope
— how users place and manage trades (order form)
— how risk is communicated in margin trading
— how users choose between simple and advanced orders
— reducing errors in trade execution
— how risk is communicated in margin trading
— how users choose between simple and advanced orders
— reducing errors in trade execution
Platform
Web
CONTEXT
Brokerage platform with trading terminal
Users trade across spot and margin markets (US, EU, Asia)
Brokerage platform with trading terminal
Users trade across spot and margin markets (US, EU, Asia)
PROBLEM (TRADERS)
— complex interface and overload
— confusion in order types (TP/SL)
— lack of risk visibility in margin trading
— complex interface and overload
— confusion in order types (TP/SL)
— lack of risk visibility in margin trading
PROBLEM (BUSINESS / SYSTEM)
— third-party backend limitations
— incomplete APIs and constraints
— legacy-driven interface decisions
— third-party backend limitations
— incomplete APIs and constraints
— legacy-driven interface decisions
WHY
Trading interfaces directly impact financial risk
Users don’t need more data→ they need clarity in actions and consequences
Especially in margin trading, unclear interactions can lead to losses→ required simplified flows and explicit risk communication
Trading interfaces directly impact financial risk
Users don’t need more data→ they need clarity in actions and consequences
Especially in margin trading, unclear interactions can lead to losses→ required simplified flows and explicit risk communication
SOLUTION (SYSTEM)
— rebuilt terminal structure from scratch
— introduced dedicated trading UI system
— adapted interface to high-density data
— rebuilt terminal structure from scratch
— introduced dedicated trading UI system
— adapted interface to high-density data
SOLUTION (TRADER)
— separated basic and advanced order flows
— clarified order types (TP/SL)
— added risk indicators
— separated basic and advanced order flows
— clarified order types (TP/SL)
— added risk indicators
TRADE-OFF
Kept some legacy table structures → avoided backend conflicts and ensured delivery speed
Kept some legacy table structures → avoided backend conflicts and ensured delivery speed
IMPACT (TRADER)
— fewer order mistakes
— better understanding of risk
— faster execution
— fewer order mistakes
— better understanding of risk
— faster execution
IMPACT (PRODUCT)
— fewer liquidation cases
— improved onboarding
— more consistent trading behavior
— fewer liquidation cases
— improved onboarding
— more consistent trading behavior
PROTOTYPES AND FIRST DRAFTS
REFLECTION
— Risk indicators and additional context improved decision clarity → but added cognitive load
— The challenge was balancing speed vs safety → especially for margin trading, where mistakes are costly
— If continuing, I would focus on adaptive interfaces→ simplifying UI for beginners while preserving depth for advanced users
— Risk indicators and additional context improved decision clarity → but added cognitive load
— The challenge was balancing speed vs safety → especially for margin trading, where mistakes are costly
— If continuing, I would focus on adaptive interfaces→ simplifying UI for beginners while preserving depth for advanced users
Designed a B2B AI workspace from scratch — from research to system architecture and implementation. A unified environment combining documents, communication, and AI agents executing workflows. Focused on embedding AI into core product behavior, not treating it as an add-on.
2025
AI Workspace for Business Operations
