Feature Overview: Positive and negative areas

Area definition analysis

Dista’s artificial intelligence (AI) and machine learning (ML) engines, coupled with the power of location intelligence, helps businesses identify areas that have customers with high and low spending potential, increased chances of delinquencies, and more.

The data is fed into our sales engine, which helps identify high-risk (negative) areas of a city that a bank has identified where residents would not qualify for credit approval. This data is primarily acquired from the sales team and industry or government bureaus.

Area definition analysis

How does Dista help?

1) Create heatmaps for areas with potential

Our platform captures data, categorizes areas based on customer spending potential, areas favorable for business, and displays them via heatmap.

2) Identify positive and negative areas

Locate positive and negative areas with a map-based risk profiling of customers in terms of their credit approval. Our system also maps areas with high or low delinquencies. This data is leveraged from banks that have identified where residents would not qualify for credit approval. The solution also helps to understand customer credit profile, repayment history, and delinquency trends by location.

3) Area definition and analysis

Dista’s BFSI solution helps support loan approvals and rejection by considering existing delinquency levels, business establishments in close areas, and more.

4) AI-based recommendations and analytics

Our platform offers AI-based recommendations to help business leaders make quick informative decisions about lending and business expansion. It converts text addresses to a spatial database and geocodes high-risk areas corroborated with other risk indicators to build a comprehensive risk map indicator. The solution also adds data points around delinquency, missed EMIs, and more.

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