Image: AFP Jessica YANG

AI and machine learning are transforming every industry as we know it and the lending industry is no exception. In conversation with Experians Scott Brown, President, Consumer Information Services, we explore the trends and challenges in the lending business and how technology is making a positive impact in driving financial inclusion.

Digital Journal: What are the biggest challenges lenders are facing when it comes to driving financial inclusion, as well as speed and accuracy, in making credit decisions?

Scott Brown: A big challenge lenders face is reaching underserved consumers who need access to credit in order to attain their financial goals. Our research shows 106 million Americans, or 42 percent of the adult population, lack access to mainstream credit because they are credit invisible, unscoreable or have a subprime credit score. Communities of color are more likely to lack access to mainstream credit, with 28 percent of Black and 26 percent of Hispanic consumers unscoreable or invisible, which is perpetuating historic disadvantage.

The industry has made a lot of progress in recent years by incorporating new data into lending decisions. There continues to be opportunity with data assets, scores and models to ensure all consumers have access to fair and affordable credit. When advanced analytics and machine learning are combined with expanded data sets, lenders have the opportunity to bring more consumers into the credit ecosystem without taking on additional risk.

DJ: What are some of the notable trends you are seeing in the lending industry today?

Scott Brown: The push to make the credit and payments industry better, faster and smarter is more apparent than ever before. Consumer expectations are changing and its critical for our industry to adapt and meet consumers where they are. In todays rapidly changing environment, 95 percent of lenders are using advanced analytics and expanded data to stay ahead and best serve consumers. This is good news.

Consumers deserve models built on current and predictive behaviours. However, as models become more sophisticated, deployment timelines and costs can increase. In fact, our research shows it takes 15 months on average to build and deploy a model for credit decisioning and 55 percent of lenders have built models that have not made it to production, which is one of the biggest challenges for lenders. Because of this, many lenders rely on old models that leave consumers behind. By leveraging data and technology, lenders can streamline model deployment, cut costs and bring more consumers into the credit ecosystem.

DJ: How does A.I. and machine learning help address the challenges lenders are facing?

Scott Brown: The key to more predictive models is more data and technology that can deliver more meaningful insights. This is where machine learning and advanced analytics come into play. When advanced analytics and expanded data are used in credit decisions, more consumers can be scored and gain access to the financial services they need. There are platform solutions that exist today that can make leveraging this information in a compliant, explainable, and transparent way easier and more cost effective for lenders.

DJ: You recently launched Ascend Ops, can you tell me what that is and how it helps your clients?

Scott Brown: At Experian, we are continually innovating and using technology to find solutions to global issues. Our goal is to modernize the financial services industry and increase financial access for all. Ascend Ops is our most recent example of this in action. This first-of-its-kind solution empowers lenders to deploy new features and models in days or weeks instead of months. It is a game changer in operational efficiency and, most importantly, in helping our clients protect and better serve consumers without making significant investments in their infrastructure.

Ascend Ops is part of the Experian Ascend Technology Platform and helps lenders implement and manage models for key use cases across the customer lifecycle, including marketing, account management and more. This gives lenders the ability to deliver more relevant marketing offers to consumers and provide better insights to make lending decisions quickly and accurately. Were helping remove the challenges lenders face in deploying new models to market. The quicker more inclusive credit models can be deployed, the sooner businesses and consumers can benefit from their use.

DJ: How is technology like A.I. and machine learning poised to transform the landscape of the credit economy and expand the lending universe over the next 5-10 years?

Scott Brown: If you think back to the landscape 5 10 years ago, technology has made our current environment look nearly unrecognizable. Over the last decade, technology has fundamentally changed the financial services industry and weve played a large role in this disruption. As we look ahead, we will continue to see the ways technology and advancements in data can transform the financial services ecosystem, including consumer permissioned data. These advancements will enable us to include more consumers in mainstream lending and allow us to bring better, faster and smarter solutions to market.

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Q & A: How A.I. and machine learning are transforming the lending ... - Digital Journal