Credit-Insight Analytics provides Insights & Solutions for Credit Institutions using Analytics, Statistics and Practical Experience.
Data & Analytics
Your data is considered a resource and holds great value. Data can help your business to understand your customers better, to understand your performance, to make better decisions, to solve problems and to improve your processes. Data Analytics enables us to extract valuable knowledge from data.
The skill to accurately manipulate data (combine from different sources, clean and transform) is often times preventing companies from using data optimally.
Data does not always have to be perfect, key data points can be identified and used to create accurate trends and datasets suitable for modelling a specific outcome.
A comprehensive understanding of statistics is required to build real-world Predictive Statistical Models.
With the advancements in analytical and statistical software today, anyone can produce a model, however the accuracy, stability and applicability of the model will highly depend on the expertise and experience of the developer. We can explain complex methods in simple terms and we prefer a ‘clear box’ system (opposite to a ‘black box’ system) where the inner components and logic is available for inspection.
Theoretical knowledge will give you a strong foundation, but it will benefit no one if the solution can’t be implemented. Practical intelligence (practical know-how) is often the differentiating factor to successfully solving problems.
We have the necessary experience of delivering credit solutions and credit scoring models in different type of credit institutions across the world.
Using Data Analytics, Statistics and Practical Experience, we can support companies to become Insight-Driven Organizations. We follow a holistic approach to evaluate the entire credit lifecycle with all it’s components: Data, Technology, Process, People & Strategy.
Services provided by Credit-Insight Analytics
We have the necessary expertise to assist in the following areas:
- Review and Development of end-to-end Credit Strategy: Credit Underwriting Process, Underwriters Analysis, Policy Rules, Business Analysis, Affordability Calculations, Loan Limit Calculations
- Incorporating Technology Solutions into Credit Underwriting processes to improve efficiency and lowering cost to serve
- Predictive Credit Scoring: Development, Monitoring & Implementation of Application, Behavioral or Transactional models
- Collections: Prioritization & Target Setting
- Retention: Retain low risk clients, Pre-approval strategies and customer segmentation
- Recoveries: Recovery Strategies after write-off, Management of External Debt Collectors
- Portfolio Analysis: Identify high-risk segments, evaluate portfolio trends and generating customer insights