Data Analytics in Business Process Version 1.2-Business Analytics Tool

Example

For the mortgage services process, the framework might involve analyzing the stages of application and approval, processing and underwriting, closing and customer onboarding, and servicing and portfolio management.

Scenario

A bank uses the framework to refine its loan approval process, leading to improved risk assessment, optimized approval rates, and enhanced customer satisfaction.

Example

Generating hypotheses for improving the debt collection process by analyzing customer payment behaviors and segmenting customers based on risk.

Scenario

A financial institution develops targeted strategies for high-risk customer segments, significantly reducing delinquencies.

Example

Creating mock data for roll rates to simulate how customers move through various stages of delinquency over time.

Scenario

A credit company tests different collection strategies in a simulated environment to identify the most effective approaches before implementation.

Example

Designing a dashboard with mock-up visualizations, such as bar charts or heat maps, to display key metrics like call response rates and promise-to-pay adherence.

Scenario

A collection agency visualizes agent performance and customer engagement levels, helping managers to quickly identify and address inefficiencies.

Example

Developing a workload forecasting model to predict future collection efforts based on current customer behavior trends.

Scenario

A bank uses the model to allocate resources efficiently, ensuring that high-risk accounts receive appropriate attention without overburdening collection teams.