Use cases

Risk modelling

Predictive models built using limited data sources don't always give a holistic view of the applicant. This can be challenging when assessing credit risk. Robust models benefit from a comprehensive set of variables brought together to generate a single or suite scores.

Data from open banking can be used in a standalone or hybrid predictive model that brings together multiple data sources.

Bank transaction data adds significant uplift to predictive models due to its comprehensive and dynamic nature.

Origination & onboarding

To offer personalised products and services at the onboarding stage, businesses need to understand their customer's financial circumstances.

Typically this process starts by requesting a PDF statement from the customer. Bank transactions are then manually categorised to understand how and where the customer spends their money. Affordability and financial health are calculated to assess the risk of onboarding the customer.

This process can be costly, time consuming, and provides a window for the customer to consider competitor offerings.

When a customer connects their account through open banking, businesses get access to all the information they need to understand a customer. Instant access to a customer's categorised bank statement removes manual processing from the equation, taking the process from hours to minutes.

Within seconds businesses can view insights on predictive cashflow, income, expenditure, debt commitments, affordability, and more, to make an efficient and informed decision.

Bank account verification

Businesses need to ensure that the people, merchants, or companies that they are paying are the correct ones.

In industries where fraud presents a high risk to revenue, verifying a customer's account ownership has never been more important.

Open banking provides the perfect solution. When a consumer or business connects their bank account you can be confident that they are the owner of that account.

Any concerns around third party fraud are removed with bank account verification. AML & KYC requirements are also satisfied.

Credit risk decisioning

Historically credit risk decisions have been made on self-declared information provided by the customer combined with information from credit reference agencies.

While decisions can be made, underwriters often lack the comprehensive, real-time view they need to make confident decisions.

Using open banking, decisions are made based on rich insights from accurate, detailed, and real-time data, that comes directly from a customer’s bank account. Advanced insights on income, expenditure, predictive cashflow, affordability, and more, give decision makers all the answers they need to make confident credit risk decisions.

Portfolio risk management

Risk managers need the most accurate data to keep their portfolios healthy and provide a personalised service to their customer.

Understanding the customer's buying behaviours, financial health, and unique requirements, helps drive the lifetime value of each customer and reduces churn.

Open banking data gives risk managers and marketers real-time, accurate data, direct from their customers. With access to data that uniquely represents each customer, risk managers can offer a personalised products at the time to drive lifetime value.

Collection & recoveries

Collections & recoveries teams need to understand their customer's repayment potential to make informed decisions on when and how much to collect. Agents need data that is real-time and accurate to successfully rehabilitate a customer or to optimise recoveries.

This process is manually intensive and often requires each customer to submit PDF statements and self-declare data. Agents then have to judge the customer's affordability.

With access to open banking data, collections teams are able to access a real-time view on their customers' finances. After a customer connects their account agents are presented with the customer's bank transactions, with the option to categorise. The data can then be used to assess the customer's repayment potential.

The process takes a fraction of the time, reducing subjective judgement, the reliance on self-declared data, and drives operational efficiencies.

Specialist credit & risk insights

Affordability

Assess how much your customer can afford to repay. Use enriched data to identify income, and fixed vs flexibile spend.

Affordability

Assess how much your customer can afford to repay. Use enriched data to identify income, and fixed vs flexibile spend.

Income verification

Verify your customer's income across all income streams, whether it's salaried wages, freelance earnings or benefits.

Categorisation & classification

Cut through the noise of a bank statement and understand how and where your customers spend their money.

Emerging financial distress

Identify emerging financial distress to enable early intervention before your customer defaults.

Browse our platform

Our platform

The DirectID platform gives you all the tools you need to capture consent, access transaction data and view detailed insights on your customer's financial behaviours.

Connect

A guided user-interface to capture consent, verify and connect to bank accounts, and share transaction data.

Data APIs

The pipelines for transferring and accessing normalised bank data, from your customer's bank account into any platform.

Dashboard

An accurate, real-time view of your customer's financial data, enriched with intelligent credit & risk insights.

Get started using open banking data

Talk with one of our specialists to find out more about using open banking data.

  • Demo of the guided customer consent journey

  • Walk through of our real-time data & insights

  • Coverage check in your markets