Core Functional Requirements
SFS Taxonomy & Categorisation
Must support mapping transactions to SFS (Standard Financial Statement) categories
Ability to tag or map items such as:
Mortgage, rent, council tax, utilities
Food, travel, housekeeping, subscriptions
Support mapping or re-mapping for less structured items such as:
Appearance, jewellery, personal electronics, entertainment, etc.
Granularity of benefit categories (e.g. Universal Credit, Child Benefit) must be confirmed
Response
TransUnion has partnered with Bud, an active member organisation of the SFS adhering the code of conduct and the guidelines of the Standard Financial Statement best practice principles.
This is directly reflected within the Assess solution as a key element to maintain flexibly and customisation within the platform is in how we have designed the core granular categorisation model to map to SFS buckets as well as other customisable mappings.
The typical categorisation service tags every transaction with three category levels (or tiers), to provide context and understanding to a customer’s income and expenditure. Depending on model version and region there are approximately 20 (l1) primary categories, 120 (l2) subcategories, and over 200 (l3) low level tags.
Regarding re-mapping, we are aware that every institution has its own taxonomy and requirements for labelling or ‘bucketing’ transactions into varying outputs. Our platform allows clients the flexibility to structure data however they want by combining any of 200+ transaction categories into a set of custom categories tailor-made for the use case required.
In addition, the underlying taxonomy has been designed with input from the SFS guidelines as well as many tier-1 financial institutions to ensure it facilitates a wide variety of client use cases. The service has been designed with flexibility and granularity in mind, for example when effectively mapping to pre-existing score cards and expense definitions used across the client base.
Please see below a very small example of categories based on the provided question samples:
mortgage (l1)
rent (l1)
utilities (l1)
utilities_energy (l2)
utilities_water_and_sewage (l2)
council_tax (l2)
food_and_drink (l1)
bars_and_pubs (l2)
coffee (l2)
groceries (l2)
eating_out_and_takeaways (l2)
transport (l1)
public_transport (l2)
taxi (l2)
petrol_and_vehicle_charging (l2)
flights_and_airport_expenses (l2)
holiday_and_travel_expenses (l2)
home (l1)
home_maintenance (l2)
media_and_telecoms (l1)
broadband (l2)
tv_streaming_services (l2)
health_and_personal_care (l1)
beauty (l2)
gym_and_fitness (l2)
shopping (l1)
clothing_and_accessories (l2)
electronics_appliances_and_technology (l2)
hobbies (l2)
gambling_and_lotteries (l1)
income (l1)
benefits (l2)
child_benefits (l3)
disability_and_sickness_benefits (l3)
housing_benefit (l3)
income_support_benefits (l3)
universal_credit (l3)
A full breakdown of our taxonomy is available upon request.
In addition to categorisation outputs, there are also specialised endpoint services incorporating additional model inputs or logic. These offer dedicated outputs tailored to specific use cases, including:
Income Finder - identifies the different types of income that a customer might receive (including regular and irregular income) to create affordability assessments and compare income over time.
Benefits Finder - Identifies all the various benefits that a customer may be claiming and receiving payments for.
Financial Products Finder - Helps to identify any financial products or services that the customer uses, the following product types can be detected; Loans, BNPL, Mortgages, Insurance Products, Credit Cards, Private Pensions, Savings and Investments.
Cash Flow Forecasting - Uses data that we have on a customer's regular transactions to forecast upcoming transactions. Clients can specify how many months into the future they would like to see transactions for. The regularities that we support are daily, weekly, monthly, quarterly, annually, unknown.
Loan & Debt Finders - Provides a list of a customers' outgoing loan transactions found within their connected accounts. Helps to understand vulnerable customers who have fallen out of the collections process and are currently repaying debt management agencies.
Subscription Finder - Helps to identify any subscriptions that a customer is currently paying. Subscriptions supported include Digital media streaming subscription, print media subscriptions, Grocery and specialty food/drink subscriptions, Technology subscriptions, including software and hardware, Health and fitness subscriptions, Recurring donations to charity.
Customer Characteristics - get customer level insights and attributes for understanding and segmenting customers based upon the context of the entire transactional "footprint" e.g. this customer is a retiree, parent, student, etc.
Affordability Insights - We offer a pre-set report that includes affordability flags , please see response "5.6" for more details on this service
