Deepfake scams and payment channels have eroded trust in digital finance, especially for vulnerable groups.
Finyx allows banks and fintechs to use an AI risk-scoring SDK that flags suspect transactions and provides clear alerts, helping users know when to pause or seek help.
Digital finance has entered a technological arms race. Generative AI tools, originally designed to empower creativity, are now being weaponized by fraudsters. Scams that once took days to execute now occur in seconds, utilizing deepfakes, synthetic identities, and AI-driven social engineering.
Enhance trust in digital financial experiences.
Manage money safely, regardless of digital experience.
Predictive AI Protection
Anticipates and identifies scams in real time, explaining risks in clear, accessible language for all digital confidence levels.
Personal Safety Circle
Connects you instantly to the people and institutions you trust most when something feels off.
The research reveals an industry at a crossroads:
AI has amplified both risk and opportunity.
Fraud has become automated, eroding trust and leaving vulnerable users exposed.
But with explainable AI and inclusive design, we can transform that same technology into a guardian — restoring safety, confidence, and growth in digital finance.”
Inclusive Design = Competitive Edge
Clear language, accessible alerts, and trusted-contact safety features rebuild confidence among underserved and aging users.
AI Defense Works, If Explainable
Mastercard and Danske Bank improved detection by 300% while reducing false positives, showing that transparent AI builds confidence.
Erosion of Trust
Users struggle to tell real from fake; older adults lose 2–3× more than younger users, causing fear in digital finance.
AI Supercharges Fraud
Deepfake and synthetic-identity attacks surged 700–3 000 % in 2023, enabling industrial-scale scams that overwhelm legacy fraud systems.
Fear of irreversibility
Instant payment and crypto transactions cannot be undone
Alert fatigue
Generic security alerts desensitize users, so they ignore critical warning
Inability to get human help
During a crisis, users are forced to deal with chatbots and cannot reach a person
Trust & safety uncertainty
Users are overwhelmed by alerts and do not know who to trust
A plug‑and‑play SDK for banks and fintechs to embed real‑time AI risk scoring during payments or smart contracts. It features a traffic‑light indicator with explanations and “freeze/report” actions, inviting trusted contacts for high‑value transactions, ensuring user confidence. The integration simplifies complex models via a single API for rapid deployment.
Here are key cross-platform features and experience flows that balance security precision with Fynix’s hallmark clarity adapting naturally to both traditional finance (TradFi) and Web3 ecosystems.
🚦 Feature 1: Inline Risk Scoring
Real-time transaction analysis and risk scoring integrated into payment APIs.
🧡 Feature 2: Trusted Contact Co-Approval
SDK sends secure approval requests to pre-registered trusted contacts. Secure messaging, identity validation APIs, consent orchestration.
🔒 Feature 3: Unified Recovery & Freeze
SDK endpoints instantly freeze cards or accounts, notify backend fraud teams, and open dispute workflows.
🧬 4. Smart Contract & Address Analysis (Web3)
API orchestration across core banking, fraud detection, and customer service systems
The SDK prevents fraud, the UX ensures people understand and act on it. Together, they redefine how safety feels in digital finance.
🌐 Feature 5: Assisstant AI
Subtle contextual pop-ups on chat or message screens. Continuous education without disrupting use.
🟣 Feature 6: Contextual “Why” Cards
Tap-to-expand explanations using icons and plain language. Builds trust by making AI decisions understandable.
🛟 Feature 7. “Are You Safe?” Check
Soft verification overlay triggered by behavioural anomalies. Enables discreet help in potential coercion cases.
🧠 Feature 8. Adaptive Behavioural Authentication
Continuously verifies identity via typing rhythm, device tilt, touch force, and micro-motion. Behavioural biometrics engine + AI pattern recognition
All alerts and explanations can be read aloud via text‑to‑speech and displayed with high‑contrast themes and large fonts. Users can select their preferred language up front. This meets the inclusivity requirement, ensuring older users and those with disabilities can navigate risk‑mitigation steps confidently.
High-Contrast “Clarity Mode”
Uses the new Luminous Clarity palette for softer light and optimal contrast, WCAG 2.2 compliant, low eye strain.
The refined MVP defines Fynix AI as a transparent protection layer, a fusion of behavioural insight, real-time detection, and calm human communication.
By grounding the experience in explainable intelligence and a clear visual hierarchy, users gain confidence, not cognitive load.
1
Concept
Chat GPT
2
Foundational Research
Chat GPT Deep Research & LLM Notebook
3
Strategy and UX Planning
Agent Mode in LLM Notebook and Chat GPT
4
UX & Product Execution
Chat GPT, Lovable, Figma Make, Midjourney
6
Documentation
Figma Make, Chat GPT
5
AI Workflow Integration & Improve MVP
Chat GPT
While AI has exponentially improved speed and progress for product development, my hypothesis is that only emerging technologies and innovative patterns will come from human development
I reached my AI credit limits on Lovable and this was a bit of a downer, if that is the case, if we are reliant on AI, then it would probably more efficient and limit the amount of zero-shot prompts.
AI positivity, it really helped me quickly dive into a problem space I had no clue about, I felt more confident creating an MVP after conducting the deep research in the AI fraud domain and how it impacts banks, crypto, and web3 products.
Deepfake scams and payment channels have eroded trust in digital finance, especially for vulnerable groups.
Finyx allows banks and fintechs to use an AI risk-scoring SDK that flags suspect transactions and provides clear alerts, helping users know when to pause or seek help.
01 Challenge
02 Research Insights
03 Features
04 Process
05 Results
Digital finance has entered a technological arms race. Generative AI tools, originally designed to empower creativity, are now being weaponized by fraudsters. Scams that once took days to execute now occur in seconds, utilizing deepfakes, synthetic identities, and AI-driven social engineering.
Enhance trust in digital financial experiences.
Manage money safely, regardless of digital experience.
Predictive AI Protection
Anticipates and identifies scams in real time, explaining risks in clear, accessible language for all digital confidence levels.
Personal Safety Circle
Connects you instantly to the people and institutions you trust most when something feels off.
The research reveals an industry at a crossroads:
AI has amplified both risk and opportunity.
Fraud has become automated, eroding trust and leaving vulnerable users exposed.
But with explainable AI and inclusive design, we can transform that same technology into a guardian — restoring safety, confidence, and growth in digital finance.”
AI Supercharges Fraud
Deepfake and synthetic-identity attacks surged 700–3 000 % in 2023, enabling industrial-scale scams that overwhelm legacy fraud systems.
Erosion of Trust
Users struggle to tell real from fake; older adults lose 2–3× more than younger users, causing fear in digital finance.
AI Defense Works, If Explainable
Mastercard and Danske Bank improved detection by 300% while reducing false positives, showing that transparent AI builds confidence.
Inclusive Design = Competitive Edge
Clear language, accessible alerts, and trusted-contact safety features rebuild confidence among underserved and aging users.
Trust & safety uncertainty
Users are overwhelmed by alerts and do not know who to trust
Inability to get human help
During a crisis, users are forced to deal with chatbots and cannot reach a person
Alert fatigue
Generic security alerts desensitize users, so they ignore critical warning
Fear of irreversibility
Instant payment and crypto transactions cannot be undone
A plug‑and‑play SDK for banks and fintechs to embed real‑time AI risk scoring during payments or smart contracts. It features a traffic‑light indicator with explanations and “freeze/report” actions, inviting trusted contacts for high‑value transactions, ensuring user confidence. The integration simplifies complex models via a single API for rapid deployment.
Here are key cross-platform features and experience flows that balance security precision with Fynix’s hallmark clarity adapting naturally to both traditional finance (TradFi) and Web3 ecosystems.
🚦 Feature 1: Inline Risk Scoring
Real-time transaction analysis and risk scoring integrated into payment APIs.
🧡 Feature 2: Trusted Contact Co-Approval
SDK sends secure approval requests to pre-registered trusted contacts. Secure messaging, identity validation APIs, consent orchestration.
🔒 Feature 3: Unified Recovery & Freeze
SDK endpoints instantly freeze cards or accounts, notify backend fraud teams, and open dispute workflows.
🧬 4. Smart Contract & Address Analysis (Web3)
API orchestration across core banking, fraud detection, and customer service systems
The SDK prevents fraud, the UX ensures people understand and act on it. Together, they redefine how safety feels in digital finance.
🌐 Feature 5: Assisstant AI
Subtle contextual pop-ups on chat or message screens. Continuous education without disrupting use.
🟣 Feature 6: Contextual “Why” Cards
Tap-to-expand explanations using icons and plain language. Builds trust by making AI decisions understandable.
🛟 Feature 7. “Are You Safe?” Check
Soft verification overlay triggered by behavioural anomalies. Enables discreet help in potential coercion cases.
🧠 Feature 8. Adaptive Behavioural Authentication
Continuously verifies identity via typing rhythm, device tilt, touch force, and micro-motion. Behavioural biometrics engine + AI pattern recognition
All alerts and explanations can be read aloud via text‑to‑speech and displayed with high‑contrast themes and large fonts. Users can select their preferred language up front. This meets the inclusivity requirement, ensuring older users and those with disabilities can navigate risk‑mitigation steps confidently.
The refined MVP defines Fynix AI as a transparent protection layer, a fusion of behavioural insight, real-time detection, and calm human communication.
By grounding the experience in explainable intelligence and a clear visual hierarchy, users gain confidence, not cognitive load.
1
Concept
Chat GPT
4
UX & Product Execution
Chat GPT, Lovable, Figma Make, Midjourney
2
Foundational Research
Chat GPT Deep Research & LLM Notebook
5
AI Workflow Integration & Improve MVP
Chat GPT
3
Strategy and UX Planning
Agent Mode in LLM Notebook and Chat GPT
6
Documentation
Figma Make, Chat GPT
Deepfake scams and payment channels have eroded trust in digital finance, especially for vulnerable groups.
Finyx allows banks and fintechs to use an AI risk-scoring SDK that flags suspect transactions and provides clear alerts, helping users know when to pause or seek help.
01 Challenge
02 Research Insights
03 Features
04 Process
05 Results
Digital finance has entered a technological arms race. Generative AI tools, originally designed to empower creativity, are now being weaponized by fraudsters. Scams that once took days to execute now occur in seconds, utilizing deepfakes, synthetic identities, and AI-driven social engineering.
Enhance trust in digital financial experiences.
Manage money safely, regardless of digital experience.
Predictive AI Protection
Anticipates and identifies scams in real time, explaining risks in clear, accessible language for all digital confidence levels.
Personal Safety Circle
Connects you instantly to the people and institutions you trust most when something feels off.
The research reveals an industry at a crossroads:
AI has amplified both risk and opportunity.
Fraud has become automated, eroding trust and leaving vulnerable users exposed.
But with explainable AI and inclusive design, we can transform that same technology into a guardian — restoring safety, confidence, and growth in digital finance.”
AI Supercharges Fraud
Deepfake and synthetic-identity attacks surged 700–3 000 % in 2023, enabling industrial-scale scams that overwhelm legacy fraud systems.
Erosion of Trust
Users struggle to tell real from fake; older adults lose 2–3× more than younger users, causing fear in digital finance.
AI Defense Works, If Explainable
Mastercard and Danske Bank improved detection by 300% while reducing false positives, showing that transparent AI builds confidence.
Inclusive Design = Competitive Edge
Clear language, accessible alerts, and trusted-contact safety features rebuild confidence among underserved and aging users.
Trust & safety uncertainty
Users are overwhelmed by alerts and do not know who to trust
Inability to get human help
During a crisis, users are forced to deal with chatbots and cannot reach a person
Alert fatigue
Generic security alerts desensitize users, so they ignore critical warning
Fear of irreversibility
Instant payment and crypto transactions cannot be undone
A plug‑and‑play SDK for banks and fintechs to embed real‑time AI risk scoring during payments or smart contracts. It features a traffic‑light indicator with explanations and “freeze/report” actions, inviting trusted contacts for high‑value transactions, ensuring user confidence. The integration simplifies complex models via a single API for rapid deployment.
Here are key cross-platform features and experience flows that balance security precision with Fynix’s hallmark clarity adapting naturally to both traditional finance (TradFi) and Web3 ecosystems.
🚦 Feature 1: Inline Risk Scoring
Real-time transaction analysis and risk scoring integrated into payment APIs.
🧡 Feature 2: Trusted Contact Co-Approval
SDK sends secure approval requests to pre-registered trusted contacts. Secure messaging, identity validation APIs, consent orchestration.
🔒 Feature 3: Unified Recovery & Freeze
SDK endpoints instantly freeze cards or accounts, notify backend fraud teams, and open dispute workflows.
🧬 4. Smart Contract & Address Analysis (Web3)
API orchestration across core banking, fraud detection, and customer service systems
The SDK prevents fraud, the UX ensures people understand and act on it. Together, they redefine how safety feels in digital finance.
🌐 Feature 5: Assisstant AI
Subtle contextual pop-ups on chat or message screens. Continuous education without disrupting use.
🟣 Feature 6: Contextual “Why” Cards
Tap-to-expand explanations using icons and plain language. Builds trust by making AI decisions understandable.
🛟 Feature 7. “Are You Safe?” Check
Soft verification overlay triggered by behavioural anomalies. Enables discreet help in potential coercion cases.
🧠 Feature 8. Adaptive Behavioural Authentication
Continuously verifies identity via typing rhythm, device tilt, touch force, and micro-motion. Behavioural biometrics engine + AI pattern recognition
All alerts and explanations can be read aloud via text‑to‑speech and displayed with high‑contrast themes and large fonts. Users can select their preferred language up front. This meets the inclusivity requirement, ensuring older users and those with disabilities can navigate risk‑mitigation steps confidently.
High-Contrast “Clarity Mode”
Uses the new Luminous Clarity palette for softer light and optimal contrast, WCAG 2.2 compliant, low eye strain.
The refined MVP defines Fynix AI as a transparent protection layer, a fusion of behavioural insight, real-time detection, and calm human communication.
By grounding the experience in explainable intelligence and a clear visual hierarchy, users gain confidence, not cognitive load.
1
Concept
Chat GPT
4
UX & Product Execution
Chat GPT, Lovable, Figma Make, Midjourney
2
Foundational Research
Chat GPT Deep Research & LLM Notebook
5
AI Workflow Integration & Improve MVP
Chat GPT
3
Strategy and UX Planning
Agent Mode in LLM Notebook and Chat GPT
6
Documentation
Figma Make, Chat GPT
While AI has exponentially improved speed and progress for product development, my hypothesis is that only emerging technologies and innovative patterns will come from human development
I reached my AI credit limits on Lovable and this was a bit of a downer, if that is the case, if we are reliant on AI, then it would probably more efficient and limit the amount of zero-shot prompts.
AI positivity, it really helped me quickly dive into a problem space I had no clue about, I felt more confident creating an MVP after conducting the deep research in the AI fraud domain and how it impacts banks, crypto, and web3 products.