Why Family Offices Are Emerging as Preferred Partners for CRED Managers

Family offices are increasingly asserting their dominance in Australia’s private credit markets, particularly in the commercial real estate debt (CRED) segment.

With more than 2,000 family offices now operating nationally—an increase of over 150% in the past decade, according to KPMG—their influence is not only growing in scale, but also in strategic sophistication.

Traditionally focused on preserving intergenerational wealth, COI Capital has found that family offices have broadened their mandates to include more active and yield-driven deployment of capital, particularly through private credit vehicles.

This shift is underpinned by a defensive allocation rationale: enhanced risk-adjusted returns, predictable income, and collateral-backed structures offer an attractive alternative to the volatility of public markets.

The Competitive Landscape for Manager Mandates

As family offices increase their exposure to private credit, the dynamic between managers and capital providers is evolving. Family offices are highly discerning capital allocators.

They expect enhanced reporting, real-time visibility into asset performance, and access to decision-makers are key differentiators for successful managers. Co-investment rights, performance-based fees, and downside protection mechanisms are increasingly standard features.

While typically fee-sensitive, many family offices are willing to accept standard management and performance fee structures when allocating $5M+ tickets, recognising the sourcing advantage and risk oversight provided by experienced managers. This has created a tiered market where only managers with demonstrated execution capability, origination networks, and robust governance frameworks are considered suitable partners.

Notably, many are competing by offering differentiated access models, such as segregated mandates, debt tranches, or tailored securitisation vehicles.

Onshore vs. Offshore Family Offices

There are important distinctions between onshore and offshore family offices in the context of CRED participation:

Onshore Family Offices: Typically have deep relationships with local stakeholders (brokers, valuers, developers) and a more intuitive understanding of planning, legal, and enforcement frameworks in Australian real estate markets. They are more likely to engage directly or via specialised mandates with domestic managers.
Offshore Family Offices: While often attracted to the yield premium and legal protections offered in Australia, they face structural barriers in accessing deal flow. Currency risk, tax treatment, and regulatory unfamiliarity are key concerns. However, they bring diversification and scale, often via feeder vehicles, special-purpose structures, or syndicated participation with Tier 1 managers.

COI Capital Management has both an offshore and onshore strategy to assist and suit both distinct Family Office needs.

Impact on the Broader CRED Market

The influx of family office capital into private credit markets has several systemic implications:

Family offices, deploying capital in significant tranches, have enhanced liquidity across the mid-market CRE sector.
Their ability to move quickly with minimal conditionality has contributed to yield compression, particularly on low-LVR, income-producing assets.
As a few family offices dominate large allocations, concerns emerge around pricing power, governance, and systemic concentration risk.

Unlike ADIs or superannuation funds, family offices operate outside the core prudential framework, raising transparency and risk management questions, particularly in a stress scenario.

So what is the answer? Are Family Offices the most Attractive?

Yes—family offices are arguably among the most attractive funding partners for CRED managers today. Their capital is not only flexible and long-term focused, but also often deployed with a strategic mindset.

Many family offices now have a deep understanding of the risk-return profile of CRE debt, making them highly engaged and informed investors.

They’re typically open to co-investment, bespoke structuring, and are less bogged down by institutional red tape, allowing them to move quickly and decisively when the right opportunity presents itself. For managers, this combination of agility, scale, and sophistication makes them a valuable and increasingly sought-after partner in the private credit space.

For high-performing CRED managers with demonstrable origination, governance, and reporting frameworks, family offices offer not only a reliable source of capital but also a collaborative partnership model capable of supporting large-scale deployments across market cycles.

Faris Dedic is the Founder and Managing Director of DIG Capital Advisory and COI Capital Management

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.