Financial Segments Use Cases
Introduction
Financial Segments provides the possibility to segment your customers.
The following use cases are examples to make them more “plastic”.
Banks
UC-01: Identify customers with recurring overdraft usage
Actors | |
|---|
Systems | Bank’s application finAPI Data Intelligence
|
|---|
Goals | Identify customers with recurring negative balances Reduce risk and offer financial support products (e.g. overdraft extension, budgeting tools)
|
|---|
Preconditions | |
|---|
Flow | Bank’s application triggers creation of a Low Balance Segment Define parameters such as: Receive jobId Poll or wait for result: GET /segments/lowBalance/{jobId} Retrieve list of users who were below the threshold at least once per month Use insights to detect financially stressed users trigger alerts or personalized offers (e.g. credit products, financial coaching) for users
|
|---|
UC-02: Identify high liquidity customers for premium offerings
Actors | |
|---|
Systems | Bank’s application finAPI Data Intelligence
|
|---|
Goals | Identify customers with high available balances Offer premium products (e.g. wealth management, premium accounts, investment services)
|
|---|
Preconditions | |
|---|
Flow | Bank’s application triggers creation of a Low Balance Segment Bank creates a High Balance Segment
CODE
POST /segments/highBalance
Define parameters such as: account type (e.g. checking, savings) threshold (e.g. 10,000 €)
Receive jobId Retrieve results:
CODE
GET /segments/highBalance/{jobId}
Get list of users with balances above the threshold Bank uses results to: identify high-value customers trigger personalized premium offers (e.g. investment advisory, portfolio management) prioritize customers for relationship management
|
|---|
Financial services providers in general
UC-03: Analyze customer spending behavior for targeted campaigns
Actors | |
|---|
Systems | Provider’s application finAPI Data Intelligence
|
|---|
Goals | Understand customer spending patterns Create targeted campaigns based on transaction categories (e.g. insurance, income, lifestyle)
|
|---|
Preconditions | |
|---|
Flow | Bank’s application triggers creation of a Financial Breakdown Segment Define parameters such as: time range (e.g. last 6 months) relevant label groups (e.g. INSURANCE, INCOME, RENTANDLIVING)
Receive jobId Retrieve results: GET /segments/financialBreakdown/{jobId} Analyze aggregated metrics such as: Use insights to: identify high-spending customer groups create targeted offers (e.g. insurance upgrades, savings plans)
|
|---|
UC-04: Cross-selling insurance products based on existing expenses
Actors | |
|---|
Systems | Provider’s application finAPI Data Intelligence
|
|---|
Goals | |
|---|
Preconditions | |
|---|
Flow |
CODE
POST /segments/insurance
Receive jobId Retrieve results:
CODE
GET /segments/insurance/{jobId}
Analyze returned data: insurance provider insurance type (e.g. health, car, life) payment amounts and frequency
Use insights to: detect missing or underrepresented insurance types offer complementary products (e.g. add liability insurance) suggest optimization (e.g. cheaper provider, bundle offers)
|
|---|