The Human Blueprint of a Winning Scorecard

Overview

Have you ever encountered a situation where a very scorecard which is fully developed, is rejected by an organization due to one or two variables are not usable due to incompatibility with their current systems?

In order to ensure that there is smooth development and implementation of a scorecard, the collaboration between IT, risk management(strategy and policy), modeling, validation, and operational staff is crucial.

This collaboration not only creates better scorecards, it also ensures that the solutions are consistent with business direction, prevent surprises, and enable education and knowledge transfer during the development process.

Development of scorecards in isolation can lead to problems such as inclusion of characteristics that are no longer collected, legally suspect, or difficult to collect operational, exclusion of operationally critical variables, and devising of strategies that result that are unimplementable.

Different personas are involved in a scorecard development and implementation and their level of involvement varies and different staff members are required at various key stages of the process

Scorecard Development Roles

The following participants are required:

1. Scorecard Developer - This is a person who performs the statistical analysis needed to develop scorecards.

Requirements

• Some business knowledge of the product/tasks for which models are being developed
• An in-depth kwoledge of various databases in the company and the data sets being used.
• An in-depth understanding of statistical principles, in particular those related to predictive modeling. E.g, knowledge of logistic regression, fit statistics, multicollinearity, decision trees and so on.
• A good understanding of the legal and regulatory requirements of models and of the model development process. This includes documentation requirements, transparency, and any laws that control the usage of certain information.
• Business experience in the implementation and usage of risk models. This is related to the business knowledge of the product.

2. Data Scientist - This is a person who helps source and extract the required records and field of information in order to populate the scorecard development database.

Requirements

• An in-depth knowledge of the various databases in the company , and the data sets being used.
• Proficiency in the tools and systems to determine and document data lineage, to perform field-specific code mappings to common values and definitions from a variety of internal legacy transaction systems and external data reporters.
• Ability to merge information from disparate sources and perform necessary preprocessing to deal with data issues, such as undefined codes, missing information or extreme values.
• Familiarity with file formats and fields of information available from the different credit bureaus, rating agencies, and other third-party data providers.

3. Product or Portfolio Risk Manager/Credit Scoring Manager - Risk managers are responsible for management of the company's portfolio and usage of scorecards. They are usually responsible for creation policies and strategies for approvals, credit limit setting, collections statement and pricing

Requirements

• Subject matter expertise in the development and implementation of the risk strategies using scores.
• An in-depth understanding of corporate risk policies and procedures.
• An in-depth understanding of the risk profile of the company's customers and applicants for the products/services.
• A good understanding of the various implementation platforms for risk scoring and strategy implementation in the company.
• Knowledge of legal issues surrounding usage of particular characteristics/processes and adjudicate credit applications.
• Knowledge of credit application processing and customer management processes in the company.
• Knowledge of roll rate models; delinquency trends by product, region and channel; and reports and the average time to change-off.

4. Product Manager(s) - Is responsible for the management of the company's product(s) from marketing or customer retention perspective

Requirements

• Subject matter expertise in the development and implementation of product-marketing strategies.
• An in-depth knowledge of the company's typical client base and target markets, including its best/most valued customers.
• Knowledge of future product development and marketing direction.

5. Operational Manager(s) - Is responsible for the management of departments such as Collection, Application Processing, Adjudication (when separate from Risk Management), and Claims. Any strategy developed using scorecards, such as changes to cutoff levels, will impact these departments.

Requirements

• Subject matter expertise in the implementation and execution of corporate strategies and procedures.
• An in-depth knowledge of customer-related issues.
• Experience in lending money.

6. Model Validation/Vetting Staff

Requirements

• A good understanding of the mathematical and statistical principles employed in scorecard development
• In-depth knowledge of corporate model validation policies, all relevant regulations, and the expectations of banking regulation agencies.
• Real-life experience in developing risk models and scorecards in financial institutions.
• A good understanding of the banking business.
• A good understanding of the data within the bank.

Dysfunctional Scorecard Development Process Usually have:

• Model developers who work in isolation , employ black box processes, and don't share their knowledge with others.
• Risk management business staff who refuse to participate or are not invited to participate in the scorecard development process, nor share knowledge of how they use the scorecard and downstream decisions.
• Risk managements staff don't have even the most basic idea of how scorecards are developed.
• People afraid to make decisions because of vague accountabilities.
• Model validation staff who have never built a scorecard themselves. Model validation staff who ask the wrong questions and treat the development process as an academic exercise enable the production of statistically perfect but ultimately useless models.
• Model validation staff with no banking experience
• vague model validation processes and policies.

7. Project Manager - Is responsible for the overall management of the project, including creation of the project plan and timelines, integration of the development and implementation processes, and management of other project resources.

Requirements

Subject matter expertise in the management of projects.
An in-depth understanding of the relevant corporate areas involved in the project.

8. IT Managers - They are responsible for management of various software and hardware products used in the company.

Requirements

Subject matter expertise in the software and hardware products involved in risk management and risk scoring implementation.
In-depth knowledge of corporate data, data governance policies and internal procedures to introduce changes to data processing.
knowledge of processing data from external data providers.

9. Enterprise Risk/Corporate Risk Management Staff (Where Applicable) Enterprise risk departments are responsible for the management of both financial and operational risks at a corporate level (as opposed to the product level). They are also involved in capital allocation and oversight of the risk function

Requirements

• Subject matter expertise on corporate policies on risk management and risk tolerance levels.
• In-depth knowledge of impacts on capital allocation/hedging, and so forth, of introductions to changes in risk adjudication.
• In-depth knowledge of actuarial practices.

10. Legal Staff/ Compliance Manager - Their work is to ensure that any proposed segmentation and scorecard characteristics is in contravention of existing laws and regulations.