MoM % Change in Total Members

#Insight:This chart tracks the monthly percentage growth or decline in the total member base. Positive values indicate member acquisition exceeding attrition. Peaks might suggest successful campaigns or seasonal influx.

Borrower Penetration Rate

#Insight: This shows the percentage of total members who are active borrowers each month. A higher, stable rate is generally desirable, indicating good engagement.

MFI Total Monthly Income

#Insight:This line chart displays the MFI’s total income generated each month. Look for seasonality, growth trends, or significant deviations.

Distribution of MFI Monthly Income

#Insight: The histogram shows the frequency of different income levels achieved per month, helping to understand the typical range and identify any unusually high or low income months.

Total MFI Deposit Balance

Insight: This chart illustrates the trend in the MFI’s total deposit portfolio, indicating success in deposit mobilization.

Average Reported Loan Amount

#Insight:Shows the trend of the average loan amount figure reported in the dataset’s records each month (e.g., average branch portfolio size or average disbursed amount per record).

Monthly Trend of Average Past Due Ratio

#Insight: This chart is critical for monitoring portfolio health. Increases in the Past Due Ratio signal potential repayment issues.

Monthly PAR Composition

#Insight: This stacked bar chart breaks down the total Portfolio at Risk into different aging categories, helping to understand the nature and severity of delinquencies.

Total Loan Amount by Region

#Insight: Compares loan disbursement trends across different regions, highlighting top performers and areas needing attention.

Average PAR by Region

#Insight: Shows how portfolio quality (average PAR amount) varies across regions over time.

Correlation: MFI Income vs. Loan Amount

#Insight: This scatter plot explores the relationship between reported monthly income and loan amounts at the observation level. A positive correlation might suggest that higher income generation is associated with larger loan portfolios or disbursements.

(Optional) Branch Locations Map

```{r leaflet_map_optional, eval=FALSE} # Set eval=TRUE if you have Latitude/Longitude if(exists(“sample_2024”) && all(c(“Latitude”, “Longitude”, “Branch_name”) %in% colnames(sample_2024))) {

# Ensure Latitude and Longitude are numeric sample_2024_map <- sample_2024 %>% mutate(Latitude = as.numeric(Latitude), Longitude = as.numeric(Longitude)) %>% filter(!is.na(Latitude) & !is.na(Longitude)) %>% # Take distinct branch locations for mapping to avoid overplotting if multiple entries per branch distinct(Branch_name, Latitude, Longitude, .keep_all = TRUE)

if(nrow(sample_2024_map) > 0) { leaflet(data = sample_2024_map) %>% addTiles() %>% addMarkers( lng = ~Longitude, lat = ~Latitude, popup = ~paste(“Branch:”, Branch_name, “
Region:”, ifelse(“region” %in% names(.), region, “N/A”), “
Total Members:”, ifelse(“Total_member” %in% names(.), Total_member, “N/A”)) ) } else { “No valid geographic data for mapping in the sample.” } } else { “Latitude/Longitude or Branch_name columns not found for mapping.” } ``` #Insight (if map is generated): The map visualizes the geographical distribution of branches included in the sample, potentially color-coded or sized by a KPI if desired in a more advanced version.