Algorithmic Bias in Financial Services

Unconscious bias in algorithms, AI, and machine learning could be the world’s biggest drivers to inequality in our lifetime.

Join the discussion and the movement to challenge bias in the financial industry. Hear what Finastra and KPMG leaders have to say.

Financial Services, We Have a problem

In the past decade, the financial world has been digitalized through the introduction of artificial intelligence (AI) and machine learning. Many parts of banking, lending and insurance decision-making processes are now being made by algorithms. The pandemic has accelerated this use of technology and while it has delivered many positive outcomes, these vital algorithms can only be as ‘fair’ and unbiased as the data sets that are used to build them. The industry must check if the biases that exist in society are being repeated through the design of these technologies.

Finastra is taking a stand against algorithmic bias and is asking the financial services ecosystem to join us in this movement to deliver fairness and equality to individuals, businesses and global communities.

Algorithmic Bias and Financial Services

A KPMG report commissioned by Finastra

To explore algorithmic bias in financial services, Finastra commissioned a report from global consultants KPMG. It comprehensively covers the various types of bias and how they can impact financial services lending. Explore the report here.

Algorithmic bias and financial services: A KPMG report prepared for Finastra

Why We’re Taking Action

A few key reasons why Finastra is taking a stand and leading the charge to tackle bias found in fintech.

We Pledge to Ensure That We Continuously Work to Challenge Bias in Fintech and Financial Services

Reforming Finastra’s Developer Agreement

Finastra has updated its developer terms and conditions for, its open platform and marketplace for developers. This means developers and partners will be expected to account for algorithmic bias and Finastra has the right to inspect for this bias within any new application.

Woman looking at data on tv wall

Hacking for Good

Finastra commits to all future hacks having a focus on inclusion. To support this, Finastra will be launching a global hacking competition as part of its Hack to the Future series to shine a light on female talent in the industry by finding and celebrating balanced, female-led teams pushing the boundaries of AI and machine learning.

group office

Workplace Equality

Within the organization, Finastra is continuing its journey to 50:50 male to female ratios across all its teams. This includes increasing women amongst our top 200 leaders and engineers from 30% to 40% by 2025 and to 50% by 2030.

people in office gathered around laptop talking

Creating New Proof of Concept Technologies

Such as FinEqual, a digital tool that enables bias-free lending, to give users the technology to empower them to tackle algorithmic bias within their own businesses. Currently at proof-of-concept stage, Finastra aims to make FinEqual available to customers in the next 18 months.

group office dark

Work With Regulators

Finastra is fully committed to tackling AI bias. The company is working closely with regulators in multiple markets and, as a technology leader, is calling upon the financial services industry to take note of the threat algorithmic bias poses to society.

Couple buying food at stand

Hack to the Future Winners

Together we accelerated the transformation to redefine finance for good.

Bloinx: A decentralized application using blockchain technology to help build savings communities by operating as a ROSCA administrator through smart contracts. Rotating credit and savings associations (ROSCA) e.g. tandas in Mexico, enable people with lack of financial knowledge and access to credit cards and bank loans to obtain money quickly through a money-pooling fund.

tinch.: An agri-fintech initiative to tackle bias against women in the agriculture sector when it comes to market price, access to agricultural loans and land availability. 

Qualify - Growth Simplified: A peer-to-peer lending platform to help low-income communities generate credit scores and gain access to formal credit.