Tailored credit risk data acquisition solutions

Many sources of credit risk data are available to a lender with new alternative credit risk data providers coming to the market each year. Once the lender has decided which are the most cost-effective to use then Zoot provides the technology that makes the integration of those sources easy.

Solution Brochure
credit risk analysis

Data acquisition solution: benefits

  • Access timely and accurate data with ease
  • Discover actionable data
  • Gain insights of performance and predictive insights to winning strategies
  • Minimise risk by identifying exposures
  • Decrease costs and increase access
  • Use the access to hundreds of “live” connections

Having tools that allow banks the flexibility to easily incorporate third-party data into their operations, without coding, eliminates barriers such as increasing costs and IT limitations.

David Albertazzi
Senior Analyst, Aite Group

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    Data acquisition solution technology

    As an integrated part of our tools we configure tailored data acquisition solutions to meet specific client requirements. We can either choose from hundreds of existing interfaces or we will build new interfaces, often quicker than the time taken to specify them in the first place. Simple interfaces can take a day. More complex ones can take up to a week, but that includes testing where the client is ready to do so.

    Once that is done, the fully integrated nature of our platform means the data is immediately available to surface in any other part of the decisioning process from the credit risk data model, to pricing calculations, to underwriting screens.

    The benefit to our clients is the ability to focus on optimising credit risk strategy and not on system implementation.

    What is credit risk data?

    Arguably, credit risk data is any data that is used in making a credit decision for a customer, either consumer or commercial, but they come in different categories. Traditional credit risk data comes from data providers who summarise a customer’s performance on other credit accounts to feed into the basic credit risk data model.

    Others deal with fraud, identity or anti-money laundering checks. More recent developments in Open Banking, primarily in the UK and Europe and now in the US, allow access to bank account details providing very accurate and up-to-date assessments of a customer’s income and outgoings and general financial health.

    And the use of credit risk data is not just driven by profitability. Regulators are placing increasing emphasis on good outcomes for customers, as part of Consumer Duty in the UK, for example, and part of demonstrating good practice is the appropriate use of data available on the customer.

    Whatever the source and purpose of the data, Zoot will provide the data acquisition solution.

    Consumer and commercial data

    While the list of providers of consumer credit risk data continues to evolve it is very mature meaning many sources of data are available. For commercial data (to feed into data acquisition solutions for B2B lending, for example) the evolution is at an earlier stage. Data has gaps and it is often out of date.

    Using personal data of business owners provides a proxy to some extent, however, better data is gradually becoming more widely available through Open Banking and its close relative Open Accounting. Irrespective of how commercial data does evolve, Zoot is ready to allow rapid exploitation to make better and quicker decisions for business loans that traditionally take hours or even days.

    Credit risk data strategy

    Data acquisition from third parties comes with a cost. Single source data provider relationships make it difficult to negotiate better pricing and IT costs can present significant hurdles to switching suppliers, or even using them in parallel, once a risk team has validated the data.

    Through its integrated data acquisition solution, in combination with decisioning tools, Zoot addresses these issues by enabling rapid interfacing and deployment of alternative data sources.

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