Tavant Logo

Closing the Lending Gap with AI and ML- Adjusting to the Neo-Normal

Share to

Prior to the Covid-19 pandemic, the financial industry was already evolving at a rapid pace, mainly driven by evolving customer expectations, advancement in technology, and heightened competition from incumbents and new entrants.

However, in just a few months, the crisis brought about years of change in the way companies in various sectors perform business.

According to a recent McKinsey Global Survey of executives, most companies have accelerated their supply-chain digitation by 3-4 years.

The cumbersome and time-consuming Loan origination process

Many lenders still use manual and paper-based procedures, which is often a time-consuming process, making it extremely difficult for lending companies to meet their customers’ demands for ever-shorter response times.

According to November 2020 Ellie Mae Origination Insight Report Data, the time to close loans has increased to 55 days, up from 54 days in October, which is the biggest concern for companies to satisfy consumers’ evolving demand of expecting much quicker turnaround times in the digital era.

Fragmented lending Supply-chain: An age-old need for Digitization

Furthermore, financial institutions have many potentials to increase their efficiency and streamline complex processes by digitizing the lending supply chain. Embedding Artificial Intelligence in the ecosystem can subsequently help companies to enhance their overall supply chain performance. It can also help lenders with possible implications across various scenarios regarding time, cost, and ROI.

Tackling fragmentation with Digitization 

Digitization resolves issues arising from fragmentation of delivery as well as sluggishness caused due to legacy loan origination. Moreover, COVID-19 has forced “a change of mindset” from the historically slow pace in digitizing supply-chain activities. Lenders are forced to develop truly end-to-end digital capabilities, from onboarding and application through approval and execution to improve servicing, capacity, and ability to automate underwriting and risk management.

AI can be used in various ways in the credit process to make it more agile and efficient. Right from legitimizing a new customer who applies for credit to choosing a suitable credit product or optimizing the credit check, the credit sector’s scope of intelligent data analytics is wide. Not only that, by leveraging AI and ML applications, lending companies can tap into customer experience at the right time with the right offer and can deliver a delightful customer experience.

The Road to Business Value – Digital Lending

It takes advanced next-gen technology to successfully process mountains of applications to ensure same-day approvals come to fruition. Automation and AI can reduce the time and cost of closing a mortgage and can effectively speed up the time-consuming tasks of gathering, reviewing, and verifying mortgage documents.

As a result, AI-backed automation can cut out the mundanity of manual tasks but augment processing with Machine learning can further reduce human interaction. This subsequently reduces time to process and cuts down the probability of errors.

AI has moved beyond experimentation to become a competitive differentiator in financial services — delivering a hyper-personalized customer experience, improving decision-making, and boosting operational efficiency.

As a result, Financial services companies have no choice but to implement AI and automate the credit value chains.

Act now – Change is here!

AI has begun to create a tangible impact on the mortgage industry. However, looking beyond the mortgage industry offers a glimpse into the actual magnitude of the AI-enabled disruption still to come. AI technology holds the potential to fundamentally redefine the industry on all levels – challenging traditional cost structures, enabling novel relationships with end customers, and much more. For those, who are yet to embark on their journey towards an artificially intelligent future, the time to act is now.

What Next?

Tavant recently sponsored Chief Data and Analytics Officers, Financial Services 2021 virtually. Tavant’s leaders Dr. Atul Varshneya, VP – AI, and Vaibhav Sharma, Head – Banktech, discussed ‘Adjusting To The Neo-Normal: Evolving the Art of Credit Decisioning with AI and ML.’

Watch the video here to gain more insights.

Reach out to us at [email protected] or visit us here

Tags :

Related insights

  • All Posts
  • Article
  • Awards & Recognition
  • Blog
  • Brochures
  • Case Studies
  • Fintech
  • Insights
  • News
  • Stories
  • Testimonials
  • Uncategorized
  • Whitepaper
  • All Posts
  • Article
  • Awards & Recognition
  • Blog
  • Brochures
  • Case Studies
  • Fintech
  • Insights
  • News
  • Stories
  • Testimonials
  • Uncategorized
  • Whitepaper

Let’s create new possibilities with technology