How data aggregation has enabled financial automation

Access to user data will enable automation in the financial industry’s future, which will help satisfy customer demands.

New improvements in technology have banks moving to online and mobile solutions in response to an increasingly digital world. 60% of individuals in Great Britain now use online banking (up from 30% in 2007) while 70% of Americans use it. Today’s tech-savvy consumers expect instant access to their finances at any moment and on any device.

Consumers’ need for instant information has given way to the rise of digital banking and the enablement of automated financial services, such as lending and advising.

>See also: Automating the finance function to unlock the value of your accountants

The technology that makes automated financial services possible? Data aggregation. By digitally accessing customer financial information, financial institutions are able to satisfy their demands faster than traditional methods and help them improve their financial health. Here are three ways automation is changing consumer experiences in the financial industry.


Data aggregation enables lenders to review up-to-date transaction histories and verify an applicant’s income and assets for credit decisioning within minutes. Digitizing this process increases accuracy and prevents fraud.

For the consumer, it eliminates the need for paperwork and speeds up the process. In the past, borrowers had to track down financial statements and pay stubs to verify assets and income.

With digital assessment, applicants simply have to give permission for the data aggregator to access their accounts to gather data and generate a credit decisioning report for the lender. Now, with data aggregation, the loan approval process is rapidly moving from a multi-month process to one that can take days.


Data aggregation compiles all of a customer’s financial data to easily determine assets, liabilities, income and expenses. This enables financial advisors to spend more time giving advice instead of clarifying their clients’ finances and gathering data.

>See also: How automation can take the pressure off the financial close

The automation of data gathering and categorisation has also accelerated the rise of robo advisors, which utilise this user-permissioned data and machine learning to solve common problems, give investment advice and recommend bank services. For example, robo advisors can suggest a credit card with rewards based on a consumer’s interests and spending habits, or even give advice about retirement planning.


A proper budget requires consumers to have a full picture of their financial health including, income, expenses and debts. Data aggregation compiles this data into one location. PFM apps such as YNAB or Mvelopes, for example, use data aggregation to help consumers view their financial transactions from income to expenses all in one place, and furthermore make a plan for future spending. This helps develop better financial habits and skills while improving overall financial awareness.

Automation saves time for both banks and busy consumers. Bank representatives are freed up to focus on more complex problems, and consumers no longer have extensive waits to be serviced. Automation means time is no longer spent on data collection for lenders and advisors but on analysis and action.

>See also: 2018 will be the year of automation in enterprise

Right now, automating lending and budgeting is just the tip of the iceberg for what data aggregation can do for the financial industry. In the future, we will see a greater number of apps and services that help individuals and organisations improve their financial wellness.

Every process will be automated or partially automated in a manner that makes for a more effective and satisfying outcome. Machine learning will enable the services to support customers better than customer service representatives and give them unrestricted access to their data.

In short, automation in banking gives customers access to their finances at their fingertips wherever they are and whenever they need it, with the intelligent insight that will lead to better financial decisions.

Sourced by Nick Thomas is the EVP and co-founder of Finicity, a leading financial data aggregator

Avatar photo

Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...

Related Topics

Machine Learning