Everyone deserves the opportunity to enjoy financial freedom and stability.
Our client is a government-backed organisation focused on supporting economic participation and financial independence across underrepresented communities. By offering home loans, business loans and portfolio management services, the organisation creates pathways for individuals and businesses to achieve financial security and actively participate in the broader Australian economy.
The client sought to introduce artificial intelligence (AI) and machine learning (ML) technologies to enhance and streamline its business processes as it supports the community. However, the transition uncovered several challenges, including inconsistent application of policies, gaps in AI model reliability, and an evolving infrastructure for data and analytics. Many business users also faced a learning curve with the new interface and data tools.
Escient was engaged to investigate the accuracy and reliability of the new AI models, establish data pipelines, mitigate risks, and improve data governance.
Our aim was to provide the client with practical, scalable analytics pipelines and AI solutions that would resolve immediate concerns and enhance the confidence of their team as they navigated a significant digital transformation.
We focused on reviewing and testing candidate models, addressing data quality issues, standardising policies, and establishing comprehensive AI governance frameworks aligned with regulatory standards and best practices in financial services. This followed a three-phase approach.
To support our understanding of the team’s aims, experiences, and challenges, we interviewed key stakeholders and explored the existing technologies, policies, and data management systems. This included assessing user needs and information flows, as well as identifying gaps in data quality and biases in the AI and ML models.
Using these findings, we designed an interim solution to address immediate concerns around data quality and ensure accurate eligibility assessment for loan applications. This involved creating data workflows supported by an integration plan and infrastructure blueprint, and scripting in Python and R to automate reporting and identify data gaps.
In addition, we developed an AI policy aligned with government standards, focused on ensuring responsible use and mitigating risks associated with privacy and security. The final step in this phase was to conduct rigorous usability testing to ensure the new platform was accessible and user friendly, and outputs were reliable and consistent.
Finally, we delivered an autonomous, fit-for-purpose platform and analytics pipeline with robust error handling, collaborating with stakeholders to validate the AI models and policy recommendations, and ensure these aligned with the client’s strategic goals and regulatory requirements.
This created a foundation for reliable and resilient processes and frameworks that will support the organisation to further streamline its operations and achieve its goals into the future.
This project has enabled the client to unlock the potential of AI in financial services, improving their capacity to serve clients and communities. Through close collaboration and creative problem-solving, we addressed immediate data challenges and equipped the client with a solid, scalable framework for sustainable, data-driven decision-making.
Escient played a key role in securing executive buy-in for the project. Their technical expertise and clear communication were far beyond what I have experienced from other specialists.
— Business Intelligence Analyst