Hype or help? – NMP

The mortgage industry has been talking about ending its “Paper-Palooza” for at least 20 years as we linger behind other industries like healthcare and insurance. Although it is currently enjoying a surge of innovation and investment, it is only a small spark. The opportunities of digital technology span the entire ecosystem, bound only by the will of its participants.

Artificial intelligence (AI) and machine learning (ML) are best understood and deployed, paving the way for these early stages. Blockchain, on the other hand, is fuzzier to many, but has a persuasive cast of evangelists.

Some companies, and even countries, are built on blockchain technology, like Figure and Liquid Mortgage. Estonia is blockchain crazy, starting with its own government entities, driving exponential business growth. They apparently started 20 years ago. Sweden and the United Arab Emirates are said to be the leaders in mortgage blockchain.

In the US mortgage industry, there seem to be more theoretical blockchain use cases than actual deployments, so far. Although, when you understand what is possible and some current successes, optimism abounds.

Artificial Intelligence (AI) and Machine Learning (ML)

Companies in our industry are increasingly deploying AI/ML, with significant gains in borrower engagement, credit decisioning, risk and portfolio analytics, and fraud detection, to name a few. name a few.
An excellent barometer of adoption is the corresponding level of interest from regulators. Recently, the Business Regulation Division (DER) of the Federal Housing Financial Agency (FHFA) increased oversight of AI/ML usage at Fannie Mae and Freddie Mac. AI/ML can pose additional risks, including operational, compliance, modeling, and financial.

In February 2022, the DER issued an advisory specific to the use of AI/ML, which would be the first of such guidance from a mortgage regulator. The guidance calls on institutions to increase risk management practices. The FHFA, along with the Mortgage Industry Standards Maintenance Organization (MISMO), also recommend that institutions set a code of ethical standards for checks and balances. With adoption already well advanced in government-sponsored enterprises (GSEs), AI/ML has arrived.

Advances in AI/ML are happening so quickly that some leaders admit they’re struggling to keep up, causing a bit of decision paralysis. According to multiple senior executives we spoke to, mostly representing Top 40 creators, some said they felt overwhelmed by the pace and scope of digital technology. What a strange dichotomy – we’ve waited years to get started, and now we’re slowing down the action to figure out where to start. It’s a fantastic disposition, unless the result is indecision.

Given the steady growth of vendors and experienced deployments of AI/ML, this technology will soon become mandatory, and institutions that lag behind will be disadvantaged on many fronts.

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