L- R: Beeler, Zayicek, Kurlander.

How are the most forward-thinking managers leveraging high-quality data in their operations?

This was the question asked of contributors in a recent Clear Path Analysis report.

The report, sponsored in conjunction with SS&C Advent, was based on an in-person roundtable in New York attended by representatives of Citymark Capital, Angel Oak Capital, Adams Street Partners, SKK, Prosperity Asset Management, and PSP Investments.

Here, we look at the question of not only achieving high-quality data for an operations team but also what to do with it once it has been acquired.

Beth Zayicek, Chief Operating Officer, Citymark Capital, Adam Beeler, Managing Director, Credit, Angel Oak Capital, and Mike Kurlander, Chief Financial Officer, Adams Street Partners, speak on the topic, with questions by Russell Newman, Former Chief Operating Officer, Rothschild & Co Asset Management, who moderated the discussion.

Russell Newman: How are the most forward-thinking managers leveraging high-quality data in their operations?

Mike Kurlander: For us, it’s primarily focused on the fund business and direct investing. If you want to improve data quality, we can probably use risk and control tools better. There’s a lot of information flowing in, and the key is to gather and process that information so it can be used effectively. To the extent you can, it’s about applying psychology and identifying opportunities within your investment insights.

Beth Zayicek: If you have a large real estate portfolio, you can start to see trends emerging in your own data before those trends are published by third-party sources. That insight helps inform how you manage your assets. We have a network of 400 operating partners across the country, and we see deal flow from many different operators. This gives us early signals, like noticing shifts in investment types or markets before the data officially hits the tape.

Adam Beeler: We’re moving beyond just saving this data; we’re proving its value for a specific strategy. In our mortgage and residential non-agency business, we’ve been leveraging this approach since around 2013. When you own the originator, it’s just as important to track the loans you say “no” to as it is to track the ones you say “yes” to and bring on board. Eventually, those loans will end up in a warehouse for financing or securitisation. We’ve originated over 60,000 individual loans across the US, but the vast number of declined loans is equally significant.

"This data is critical when originating loans, warehousing them, and securitising them."

One metric we use is the pull-through rate, which measures how many loan applications result in funded loans. In the early days, that rate was probably around 20-30%. But as we’ve integrated better technology, including third-party and in-house systems, that pull-through rate has climbed into the 90% range. This data is critical when originating loans, warehousing them, and securitising them. There are multiple layers of checks and balances: the originator’s due diligence, the warehouse bank’s oversight, the securitisation process, and then the investors, whether insurance companies or asset managers, all doing their own diligence.

Because of this, the data quality and control process has become smarter and more efficient.

Mike: One thing we’re doing is trying to take advantage of the AI buzzword. So instead, we’re reaching out to all our top vendors and saying, “How is AI benefiting you?”

"This is one way we’re trying to answer the bigger question of how we get better, by understanding how new technology makes jobs easier, faster, and more efficient."

It’s only going to become more widespread, so the follow-up question is, how does that benefit then being fed back to the user?

This is one way we’re trying to answer the bigger question of how we get better, by understanding how new technology makes jobs easier, faster, and more efficient.

You can read the report in full, which features this full discussion, here.

 

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