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Powering the Complete Lending Value Chain with AI

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Mortgage lending is a data-intensive business. The volume of available data grows drastically in a mortgage company, with more added every day from calls and payment systems. Needless to say, the success of any lender is built on thoroughly understanding its borrower data, the speed at which it can leverage such data, the degree to which it can meet evolving customer expectations, and the technology it adopts to process it.

Challenges faced by lending companies in changing times

As the COVID-19 pandemic continues to create changes, many Fintech companies are under stress on many fronts. The pandemic has also exposed modernization needs for critical systems.

At the same time, lenders also need to address the challenges such as fluctuating origination volumes, increasing costs, higher expectations from borrowers, and rising competition from new, technology-savvy entrants amid changing times.

To compete in this environment — to even expect to stay in business — legacy lenders have started showing their willingness to abandon multiple disparate systems with fragmented data, rigid and inefficient legacy systems & processes, and embrace cutting-edge automation and digitization.

How can Fintech fuel innovation amidst changing times?

Fintech companies tend to have unique advantages that allow many to create new ways of delivering real value in the current environment and position themselves to thrive in the longer term. Fintech companies have several attributes that give them the agility needed to create and deliver new solutions rapidly. Generally speaking, they are

  1. Adept at analyzing and harnessing various types of data, such as credit and underwriting data
  2. Exceptionally focused on a seamless and delightful digital customer experience

 

Unlocking the real potential of Artificial Intelligence and Machine Learning to power the complete lending value chain

The Fintech space has always been about disruption and driven by innovation, whether it is investments, payments, lending, capital markets, wealth management, or personal finance. From growing revenues, reducing churn, expanding customer bases, or managing risk and efficiencies, AI and machine learning can provide powerful tools for the top fintech companies in the world.

Fintech’s traditional tech stacks were not designed to anticipate and act quickly on real-time market indicators and data; they are optimized for transaction speed and scale. What is needed is a new tech stack that can flex and adapt to changing market and customer requirements in real-time. AI and ML have proven to be very powerful at interpreting and recommending actions based on real-time data streams.

Machine learning has become ubiquitous, but organizations are struggling to turn data into value. The stakes are high. Those who advance furthest fastest will have a significant competitive advantage; those who fall behind risk becoming irrelevant.

It is time for a change

Because of rising loan costs, improving operational efficiency has become just as important to lenders as enhancing the borrower experience, maybe even more so. Undoubtedly, why a growing number of lenders have begun embracing artificial intelligence (AI) and machine learning, which remains the two most talked-about next-gen technologies in the mortgage industry today.

AI models can help fintech organizations throughout the lifecycle of the loan process. For instance, in the initial phase of the loan process, AI can automate and optimize processes around identifying new target customers, predicting propensity to convert, risk-based pricing. And further, along the lifecycle, AI and ML can bring efficiencies and speed in loan processing through more accurate risk models, detection of fraud, and assisting underwriters with decisioning, managing customer churn, default prediction. These reduce costs, improve processing times, and customer experience.

The light at the end of the tunnel

The current uncertainty has undeniably placed businesses across the globe under economic duress, and Fintech is no exception. Albeit, many companies in the mortgage arena are already rising to the challenge and arranging their products and services to keep up with the evolving needs of customers who are struggling through the pandemic themselves.

What is more, given their differentiated capabilities—namely innovation, resilience, and adaptability— many Fintech companies are well-positioned to survive the crisis and contribute to the industry in meaningful ways once the crisis is behind us. For this unprecedented crisis, if history provides any lessons, it may be that adversity inspires creativity.

Final Thoughts

Maintaining operational resilience is top of mind of most mortgage companies. Lenders that capitalize on next-gen technology to re-imagine their credit risk scoring and decision systems can enhance the quality of leads and make better recommendations while cutting down manual activities, maintenance costs, and losses.

Transform Decision Making

Tavant solutions enable customers to make better business decisions every day by incorporating the latest developments in machine learning. To learn more about Tavant’s machine learning-based conditions management & decisioning platform, visit here or reach out to us at [email protected].

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