Financial institutions are trying to navigate the economic downturn, adjusting loan and deposit pricing to align with market expectations, increasing credit spreads on loan offerings to protect against losses, and taking steps to guard against defaults.

They say, “necessity is the mother of all invention,” and we are indeed witnessing a period of reinvention with new innovations and lending products emerging.

Today’s ecosystem of data sources, infrastructure providers, and data science professionals are being presented with an incredible opportunity (and challenge) to demonstrate how best to operate in uncertain times.

FIs that can leverage additional data sources, and test and deploy new strategies to ensure the business is operating in a healthy manner will be the ones that can capture new market share during this downturn and reap the benefits of growth when others are pulling back from the market.

This includes the use of predictive analytics to understand which consumers have the best propensity to pay, and then develop strategies that will help them stay financially whole as debt ratios rise. Moving forward, financial institutions must emphasize that even when times get tough, they’re going to be there to help consumers and business clients weather the storm.

FIs that can deliver products that allow their customers to live a financially healthy life, even when there are bumps in the financial road, will reap the benefits associated with customer loyalty, product graduation and expansion. This will be especially relevant in the new-to-credit and immigrant populations, as well as the sub-prime segment -- sectors which have traditionally been poorly served by this industry.

Machine learning and AI will also be crucial in navigating these new uncharted waters. Lenders must aspire to capture the most market share they can in the least risky manner, and the right data and technology combination can help them do that.  

Machine learning and AI can help lenders understand not only a customer’s historical financial position, but also their current and, potentially, near-term position. Traditional data is not the most accurate predictor of future ability to pay. Leveraging alternative data is key to assessing risk more accurately and more dynamically as well as  detecting  and understanding the early warning indicators for those who might be headed for significant financial trouble and being ready to help them with payment options. 

As we face economic uncertainty, innovative technology such as AI and machine learning for real-time, data-driven risk decisioning can aid the financial services industry in delivering the right products and services to support customers in their time of need – and experience growth as a result.