Day 1: Introduction to the Challenge
📢 Day 1/100: The Journey Begins!
I'm embarking on a 100-day challenge to share insights, progress, and lessons learned as I build a data-driven credit scoring model tailored for Buy-Now-Pay-Later (BNPL) services in Ethiopia's fintech space. 🚀
Why this topic? BNPL is reshaping financial inclusion, and robust credit scoring is the backbone of sustainable lending. Follow along as I explore data, algorithms, and strategies to make this happen!
hashtag#Fintech hashtag#DataScience hashtag#CreditScoring hashtag#BNPL hashtag#FinancialInclusion hashtag#Ethiopia hashtag#100DaysChallenge
📢 Day 1/100: The Journey Begins!
I'm embarking on a 100-day challenge to share insights, progress, and lessons learned as I build a data-driven credit scoring model tailored for Buy-Now-Pay-Later (BNPL) services in Ethiopia's fintech space. 🚀
Why this topic? BNPL is reshaping financial inclusion, and robust credit scoring is the backbone of sustainable lending. Follow along as I explore data, algorithms, and strategies to make this happen!
hashtag#Fintech hashtag#DataScience hashtag#CreditScoring hashtag#BNPL hashtag#FinancialInclusion hashtag#Ethiopia hashtag#100DaysChallenge
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📢 Day 2/100: Why BNPL in Ethiopia?
BNPL services have huge potential in Ethiopia, a country with growing digital adoption but limited formal credit access. 🛒💳
Key points I'll focus on:
1️⃣ Addressing financial inclusion.
2️⃣ Navigating unique local challenges (e.g., data availability).
3️⃣ Leveraging tech for scalability.
What do you think are the biggest opportunities for BNPL in emerging markets?
#BNPL #EmergingMarkets #FintechInnovation #DigitalFinance #Ethiopia #FinancialInclusion
BNPL services have huge potential in Ethiopia, a country with growing digital adoption but limited formal credit access. 🛒💳
Key points I'll focus on:
1️⃣ Addressing financial inclusion.
2️⃣ Navigating unique local challenges (e.g., data availability).
3️⃣ Leveraging tech for scalability.
What do you think are the biggest opportunities for BNPL in emerging markets?
#BNPL #EmergingMarkets #FintechInnovation #DigitalFinance #Ethiopia #FinancialInclusion
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📢Day 5/100: Understanding Ethiopian Fintech
Ethiopia's fintech ecosystem is a mix of challenges and opportunities. 📈🌍
From low formal banking penetration to an increasingly digital population, it’s clear that innovation in financial services is critical.
Key insights from my research today:
1️⃣ Low banking penetration but high mobile adoption: Over 75% of transactions are cash-based, yet mobile payment systems like Telebirr are gaining traction.
2️⃣ Regulatory frameworks: Ethiopia’s regulatory approach emphasizes financial inclusion but poses innovation challenges, especially for BNPL services.
3️⃣ Unique consumer behaviors: Ethiopians' dominance of informal financial systems and cash reliance shape their engagement with digital financial services.
💡 Question of the day: How can fintech drive financial literacy in Ethiopia to accelerate digital adoption?
#FintechAfrica #Ethiopia #BNPL #FinancialLiteracy #DigitalTransformation
Ethiopia's fintech ecosystem is a mix of challenges and opportunities. 📈🌍
From low formal banking penetration to an increasingly digital population, it’s clear that innovation in financial services is critical.
Key insights from my research today:
1️⃣ Low banking penetration but high mobile adoption: Over 75% of transactions are cash-based, yet mobile payment systems like Telebirr are gaining traction.
2️⃣ Regulatory frameworks: Ethiopia’s regulatory approach emphasizes financial inclusion but poses innovation challenges, especially for BNPL services.
3️⃣ Unique consumer behaviors: Ethiopians' dominance of informal financial systems and cash reliance shape their engagement with digital financial services.
💡 Question of the day: How can fintech drive financial literacy in Ethiopia to accelerate digital adoption?
#FintechAfrica #Ethiopia #BNPL #FinancialLiteracy #DigitalTransformation
📢Day 6/100: BNPL Risks in Emerging Markets
While Buy-Now-Pay-Later (BNPL) services are revolutionizing access to credit, they come with risks—particularly in emerging markets like Ethiopia. ⚠️
Key risks I’m addressing in my project:
1️⃣ Credit risk: Developing a robust scoring system to predict default probabilities.
2️⃣ Behavioral risk: Educating users to avoid overspending, especially first-time borrowers.
3️⃣ Operational challenges: Adapting BNPL models to Ethiopia’s infrastructure and regulatory environment.
💡 Discussion point: How can BNPL providers balance convenience with responsible lending practices?
#RiskManagement #BNPL #CreditScoring #FinancialInclusion #EthiopiaFintech
While Buy-Now-Pay-Later (BNPL) services are revolutionizing access to credit, they come with risks—particularly in emerging markets like Ethiopia. ⚠️
Key risks I’m addressing in my project:
1️⃣ Credit risk: Developing a robust scoring system to predict default probabilities.
2️⃣ Behavioral risk: Educating users to avoid overspending, especially first-time borrowers.
3️⃣ Operational challenges: Adapting BNPL models to Ethiopia’s infrastructure and regulatory environment.
💡 Discussion point: How can BNPL providers balance convenience with responsible lending practices?
#RiskManagement #BNPL #CreditScoring #FinancialInclusion #EthiopiaFintech
📢Day 8/100: Sketching My Credit Scoring Workflow
Today, I outlined the workflow for my credit scoring model. Here’s what it looks like:
1️⃣ Data collection: Leveraging transaction histories, behavioral metrics, and alternative data sources.
2️⃣ Feature engineering: Creating features like transaction recency, frequency, and value tailored to BNPL behavior.
3️⃣ Model selection: Comparing Gradient Boosting, Random Forest, and Logistic Regression.
4️⃣ Evaluation: Balancing precision, recall, and ROC-AUC to ensure the model is reliable in the Ethiopian context.
💡 Tips needed: What’s your go-to feature engineering strategy for financial datasets?
#AI #CreditScoring #ModelDevelopment #BNPL #DataScienceEthiopia
Today, I outlined the workflow for my credit scoring model. Here’s what it looks like:
1️⃣ Data collection: Leveraging transaction histories, behavioral metrics, and alternative data sources.
2️⃣ Feature engineering: Creating features like transaction recency, frequency, and value tailored to BNPL behavior.
3️⃣ Model selection: Comparing Gradient Boosting, Random Forest, and Logistic Regression.
4️⃣ Evaluation: Balancing precision, recall, and ROC-AUC to ensure the model is reliable in the Ethiopian context.
💡 Tips needed: What’s your go-to feature engineering strategy for financial datasets?
#AI #CreditScoring #ModelDevelopment #BNPL #DataScienceEthiopia