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	Bank User
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	User has connected their accounts via finAPI Account and transaction data is up to date
Flow	Bank’s application triggers creation of a Low Balance Segment Define parameters such as: threshold (e.g. -100 €) duration (e.g. last 3 months) 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	Bank User
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	User has connected their accounts via finAPI Account balances are up to date
Flow	Bank’s application triggers creation of a Low Balance Segment Bank creates a High Balance Segment `POST /segments/highBalance` Define parameters such as: account type (e.g. checking, savings) threshold (e.g. 10,000 €) Receive `jobId` Retrieve results: `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	Bank User
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	User has connected their accounts via finAPI Account and transaction data is up to date
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: total and average spending monthly trends variability (standard deviation) 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	Financial Service Provider User
Systems	Provider’s application finAPI Data Intelligence
Goals	Identify customers with existing insurance contracts Offer complementary or optimized insurance products
Preconditions	User has connected their accounts via finAPI data is up to date
Flow	Provider creates an Insurance Segment `POST /segments/insurance` Receive `jobId` Retrieve results: `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)