# Products [MOGOPLUS](https://www.mogoplus.ai/) offers a range of products to help enterprises make informed, data led lending decisions. ### **GoCat** *Fast, Accurate, and Secure Data Categorisation for Credit Decisioning* In order to understand the key behavioural patterns in customer data, enterprises require an intelligent approach to categorisation. Our GoCat product turns the unstructured descriptions within the bank transaction data into usable and meaningful industry standard categories as the first step to straight through processing and instant decisioning outcomes in the lending process. #### Response Response data will contain Category Group Summary and Category Summary data objects both at application level (i.e if there is more than one applicant or more than one institution) as well as applicant level (i.e per individual customer). ### **GoVerify** *Comprehensive Financial Profiling and Employer Income Verification* Reviewing bank statements and payslips manually to verify applicants' financial position and income can be highly time-consuming for credit assessment teams. It is also prone to human error, inaccuracies, or potential fraud. Our GoVerify product uses several unique algorithms and data analytical models to understand critical patterns and relationships across different data points. GoVerify enables credit assessment and underwriting teams to instantly determine the financial behaviour and affordability of the applicants by analysing the recent and historical customer data. #### Response The response data will contain Category Group Summary and Category Summary data objects both at application level (i.e if there is more than one applicant or more than one institution) as well as applicant level (i.e per individual customer). Along with categorisation details, this product contains income details (Employer Income, Rental Income, etc grouped as Main or Secondary income) detailing the recency and regularity of income. ### **GoLend** *Streamlining Serviceability Assessments with Meaningful Analytics for Lending* With close to 90% of all transactions now captured in digital format, there is more data available to credit providers than ever before. The challenge is to utilise the right data in the right context for the right purpose in the lending journey. Our GoLend product makes sense of raw unstructured data with a focus on serving lending journeys and improving serviceability assessments. Building on our accurate Data Categorisation and Verification solution, GoLend adds further sophistication and utilises additional key analytics and assessment metrics to assist the lender in making more informed and accurate credit decisioning. Using a low touch, configurable solution, unique algorithms and analytical modules focused on statistical calculations, our GoLend product creates a consistent, coherent, and intuitive financial report with decision-ready metrics to help accelerate lending decisioning and enable straight-through processing. #### Response The response data will contain Category Group Summary and Category Summary data objects both at application level (i.e if there is more than one applicant or more than one institution) as well as applicant level (i.e per individual customer). Along with categorisation details, this product will also contain Income Insights at both application level and applicant level. The Income Summary is provided as a distinct entity, which includes incomeInsights. This is further broken down into basicIncomeInsights and inferentialIncomeInsights. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.mogoplus.ai/sandbox/basics/products.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.