From 79bb6dc290daa6585ffc63fa5ab97a1beb7c73a7 Mon Sep 17 00:00:00 2001 From: Jorge Garcia Hospital <129095857+jgarciahospital@users.noreply.github.com> Date: Wed, 9 Oct 2024 19:36:17 +0200 Subject: [PATCH] Aligning API name --- documentation/API proposals/API_Proposal_Telco Index.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/documentation/API proposals/API_Proposal_Telco Index.md b/documentation/API proposals/API_Proposal_Telco Index.md index 87ba808..0a7f834 100644 --- a/documentation/API proposals/API_Proposal_Telco Index.md +++ b/documentation/API proposals/API_Proposal_Telco Index.md @@ -1,8 +1,8 @@ | **Field** | Description | | ---- | ----- | -| API family name | Telco Index | +| API family name | Customer Insights | | API family owner | Telefonica | -| API summary | (part of OGW DROP4) The service provides a scoring related to the user's credit profile, calculated based on the information that the operator has about the owner of the associated line. Certain applications or services, like bank accounts, insurers or credit agencies, employ complex risk analysis for their operation. Telcos can calculate a credit scoring for those applications employing owned useful information, including profiling of young people or informal workers, people who do not have much commercial history or market information about who have consumption and credit potential. The service will consider as input a user identifier, like MSISDN, and the document ID or identity Card number, while the output will be the calculated credit scoring for such user. | +| API summary | (part of OGW DROP4) The service provides a index or scoring related to the user's credit profile, calculated based on the information that the operator has about the owner of the associated line. Certain applications or services, like bank accounts, insurers or credit agencies, employ complex risk analysis for their operation. Telcos can calculate a credit scoring for those applications employing owned useful information, including profiling of young people or informal workers, people who do not have much commercial history or market information about who have consumption and credit potential. The service will consider as input a user identifier, like MSISDN, and the document ID or identity Card number, while the output will be the calculated credit scoring for such user. | | Technical viability | The service employs historical and processed information around the customer to calculate a standard scoring indicating the level of creditworthiness. This scoring is determined based on various data points that provide insights into the customer's financial behavior and stability.
**Inputs Explained:**
- **MSISDN**: Mobile Station International Subscriber Directory Number. It is used to identify the mobile number of the user. Example: "+5566912345678".
- **nationalIdDoc**: National identity document number of the user. Example: "123.456.789-09".
- **documentType**: Type of the national identity document, such as CPF (Cadastro de Pessoas Físicas) in Brazil, indicating it is a personal taxpayer registry identification.
**Output:**
- **Calculated Scoring**: The credit score calculated based on the inputs provided, reflecting the user's credit risk and potential financial reliability.| | Commercial viability | **Current use cases validating the service:**
1. **Credit Application Evaluation**: Utilizes credit scoring models to assess credit applications from individuals with limited banking history. Especially relevant in areas with many unbanked individuals, leveraging data from mobile payments and service usage to generate reliable credit scores, enabling financial services for previously uncovered segments.
2. **Customer Profile-Based Service Personalization**: Employs credit scores to offer personalized financial products. Financial institutions use telecom credit scores to tailor services, adjusting interest rates on loans and credit limits on cards to align with the risk and potential profitability of each client, utilizing data analytics to assess risk and predict financial behavior.
3. **Client Base Expansion and Onboarding Eligibility**: Focuses on expanding the client base and refining eligibility criteria for onboarding new customers in premium sectors, such as gyms. Utilizes telco credit scores to identify potential high-value customers based on their spending habits, lifestyle choices, and preferences, facilitating a tailored onboarding process that attracts and retains premium clients.
4. **Personalization of Advertising Campaigns**: Integrates the Telco Credit Score API into e-commerce strategies, enabling businesses to personalize advertising campaigns and minimize risks. Specifically, an e-commerce platform specializing in luxury fashion can use this integration to optimize marketing efforts and prevent fraudulent transactions by tailoring product promotions to customer profiles identified by the Telco Credit Score.
5. **Insurance Underwriting and Risk Assessment**: Enhances traditional insurance underwriting by incorporating credit scoring data, providing a deeper insight into potential policyholders' financial behavior and stability. This integration helps in accurately pricing policies and managing overall risk exposure, utilizing indicators of financial stability as predictors for the likelihood of filing insurance claims.
6. **Telco Score in Onboarding of New Clients**: Utilizes credit scores to streamline the onboarding process for new clients, integrating credit scoring as a reliable tool to assess creditworthiness and risk efficiently. This approach speeds up client intake, reduces the need for additional verifications, improves conversion rates, and helps maintain a balance between efficient client processing and risk management.| | YAML code available? | NO
To be provided |