A prominent challenge facing by our mortgage firms involves the intricate task of categorizing loan data according to varying loan amounts, subsequently grouping them based on distinct loan types and purposes for diverse loan owners. The huge volume and diversity of loan data make this classification process complex, making the reporting and analysis of data a tedious task. The challenge extends to ensuring accuracy in delineating loan types, such as fixed-rate mortgages, adjustable-rate mortgages, or government-backed loans, and discerning diverse loan purposes, ranging from home purchases to refinancing. Moreover, the necessity to tailor these categorizations to different loan owners, such as individual borrowers, real estate investors, or institutional entities, adds an additional layer of complexity. Addressing this challenge effectively is crucial for optimizing decision-making processes, risk assessment, and providing personalized financial solutions to a diverse clientele.
We can create bucket columns in salesforce reports to categorize data without creating a formula. When we create a bucket column, we should define multiple categories (buckets) used to group report values. Like any other column in a report, we can sort, filter, and group by bucket columns.
In a mortgage firm, Salesforce uses the custom ‘Loan’ object to store the details of loans. Loan types are categorized as FHA, VA, Conventional, HELOC etc. We need to create a report which shows the number of loans under each of these categories owned by each loan officer. Also, a bucket named ‘Size’ is created in which each loan will be categorized into ‘Small’, ‘Medium’ and ‘Large’ buckets based on the range of values defined in the ‘Loan Amount’ field.