Business

Turning Tragedy into Triumph Through Walking With Anthony

Published

2 years ago

April 18, 2024

On the morning of February 6, 2010, Anthony Purcell took a moment to admire the churning surf before plunging into the waves off Miami Beach. Though he had made the dive numerous times before, that morning was destined to be different when he crashed into a hidden sandbar, sustaining bruises to his C5 and C6 vertebrae and breaking his neck.

“I was completely submerged and unable to rise to the surface,” Purcell recalls. “Fortunately, my cousin Bernie saw what was happening and came to my rescue. He saved my life, but things would never be the same after that dive.”

Like thousands of others who are confronted with a spinal cord injury (SCI), Purcell plunged headlong into long months of hopelessness and despair. Eventually, however, he learned to turn personal tragedy into triumph as he reached out to fellow SCI victims by launching Walking With Anthony.

Living with SCI: the first dark days

Initial rehabilitation for those with SCIs takes an average of three to six months, during which time they must relearn hundreds of fundamental skills and adjust to what feels like an entirely new body. Unfortunately, after 21 days, Purcell’s insurance stopped paying for this essential treatment, even though he had made only minimal improvement in such a short time.

“Insurance companies cover rehab costs for people with back injuries, but not for people with spinal cord injuries,” explains Purcell. “We were practically thrown to the curb. At that time, I was so immobile that I couldn’t even raise my arms to feed myself.”

Instead of giving up, Purcell’s mother chose to battle his SCI with long-term rehab. She enrolled Purcell in Project Walk, a rehabilitation facility located in Carlsbad, California, but one that came with an annual cost of over $100,000.

“My parents paid for rehabilitation treatment for over three years,” says Purcell. “Throughout that time, they taught me the importance of patience, compassion, and unconditional love.”

Yet despite his family’s support, Purcell still struggled. “Those were dark days when I couldn’t bring myself to accept the bleak prognosis ahead of me,” he says. “I faced life in a wheelchair and the never-ending struggle for healthcare access, coverage, and advocacy. I hit my share of low points, and there were times when I seriously contemplated giving up on life altogether.”

Purcell finds a new purpose in helping others with SCIs

After long months of depression and self-doubt, Purcell’s mother determined it was time for her son to find purpose beyond rehabilitation.

“My mom suggested I start Walking With Anthony to show people with spinal cord injuries that they were not alone,” Purcell remarks. “When I began to focus on other people besides myself, I realized that people all around the world with spinal cord injuries were suffering because of restrictions on coverage and healthcare access. The question that plagued me most was, ‘What about the people with spinal cord injuries who cannot afford the cost of rehabilitation?’ I had no idea how they were managing.”

Purcell and his mother knew they wanted to make a difference for other people with SCIs, starting with the creation of grants to help cover essentials like assistive technology and emergency finances. To date, they have helped over 100 SCI patients get back on their feet after suffering a similar life-altering accident.

Purcell demonstrates the power and necessity of rehab for people with SCIs

After targeted rehab, Purcell’s physical and mental health improved drastically. Today, he is able to care for himself, drive his own car, and has even returned to work.

“Thanks to my family’s financial and emotional support, I am making amazing physical improvement,” Purcell comments. “I mustered the strength to rebuild my life and even found the nerve to message Karen, a high school classmate I’d always had a thing for. We reconnected, our friendship evolved into love, and we tied the knot in 2017.”

After all that, Purcell found the drive to push toward one further personal triumph. He married but did not believe a family was in his future. Regardless of his remarkable progress, physicians told him biological children were not an option.

Despite being paralyzed from the chest down, Purcell continued to look for hope. Finally, Dr. Jesse Mills of UCLA Health’s Male Reproductive Medicine department assured Purcell and his wife that the right medical care and in vitro fertilization could make their dream of becoming parents a reality.

“Payton joined our family in the spring of 2023,” Purcell reports. “For so long, I believed my spinal cord injury had taken everything I cared about, but now I am grateful every day. I work to help other people with spinal cord injuries find the same joy and hope. We provide them with access to specialists, funding to pay for innovative treatments, and the desire to move forward with a focus on the future.”

Business

AI in Asset Management Explained: How Leading Firms Apply It

Published

3 hours ago

April 16, 2026

Matthew Wiles

AI in asset management explained at its most basic level is this: using machine learning, data modeling, and automation to make faster and more accurate investment decisions. The applications vary widely across asset classes, fund strategies, and operational functions. Understanding where AI creates real value separates productive adoption from expensive experimentation.

Asset managers now face a data environment far larger than any human team can process manually. Market signals, company filings, macroeconomic indicators, alternative data sources, and portfolio monitoring all generate information continuously. AI tools process that information at scale. They surface patterns that traditional analysis would miss or find too late.

AI in Asset Management Explained Across Core Investment Functions

AI delivers the most measurable results when applied to specific investment functions rather than deployed as a general capability. The clearest applications sit in portfolio construction, risk management, and credit analysis.

Portfolio Construction and Factor Modeling With AI

Traditional portfolio construction relies on return and correlation assumptions built from historical data. AI-driven portfolio tools go further. They process real-time market data, alternative signals, and macroeconomic inputs simultaneously. This surfaces factor exposures that static models miss.

Machine learning models in portfolio construction can:

Identify non-linear relationships between asset classes that correlation matrices do not capture
Adjust factor weightings dynamically as market conditions shift rather than on a quarterly rebalancing schedule
Flag concentration risks before they appear in standard risk reports
Model tail scenarios using a broader range of historical stress periods than traditional value-at-risk models allow

James Zenni, founder and CEO of ZCG with over 30 years of capital markets experience, has built the platform’s investment approach around the principle that better data and faster analysis produce better outcomes. That view shapes how AI capabilities get deployed across ZCG’s private equity, credit, and direct lending strategies.

Credit Analysis and Private Markets AI Applications

Credit analysis in private markets has historically depended on periodic financial reporting and relationship-based deal intelligence. AI changes that model. Lenders using machine learning tools now monitor borrower health continuously rather than waiting for quarterly covenant tests.

Specific credit applications include:

Cash flow pattern analysis that identifies revenue deterioration weeks before it shows up in reported financials
Supplier and customer relationship mapping that flags single-source dependencies and concentration risks
Covenant monitoring automation that tracks hundreds of credit agreements simultaneously and alerts teams to early warning signs
Loan pricing models that incorporate current market spread data and comparable transaction history

These capabilities compress the time between identifying a problem and taking action. In credit, that time advantage directly affects loss rates and recovery outcomes.

AI in Asset Management Explained Through Risk and Compliance Applications

Risk management and regulatory compliance represent two of the highest-value AI applications in asset management. Both functions involve processing large volumes of structured and unstructured data under time pressure.

How AI Transforms Risk Monitoring in Asset Management

Traditional risk monitoring produces reports at set intervals. AI-powered risk systems run continuously. They flag anomalies in position data and monitor correlated exposures across a portfolio. Alerts fire when market conditions shift beyond defined thresholds.

The practical risk management applications include:

Real-time portfolio stress testing against live market inputs rather than end-of-day snapshots
Liquidity modeling that accounts for position size relative to market depth across multiple scenarios
Counterparty exposure monitoring that aggregates risk across instruments, custodians, and trading relationships
Regulatory reporting automation that reduces manual preparation time and lowers the risk of filing errors

ZCG applies these capabilities across its approximately $8 billion in AUM. The platform was founded 20 years ago. It built its investment infrastructure around systematic data analysis and operational discipline.

AI for Operational Efficiency in Asset Management Firms

Beyond investment decisions, AI delivers significant value in fund operations. Back-office functions like reconciliation, reporting, and compliance documentation consume substantial resources at most asset management firms.

AI tools applied to fund operations include document processing systems. These extract and verify data from offering documents, side letters, and subscription agreements automatically. Reconciliation tools flag breaks between custodian records and internal systems automatically. Investor reporting platforms generate customized materials from structured data inputs, reducing the manual production time significantly.

ZCG Consulting (“ZCGC”) advises operating companies across more than a dozen sectors on operational improvement programs, including technology-driven process redesign. Those operational efficiency principles translate directly to asset management back-office functions.

Applying AI to Asset Management: Limitations Firms Must Address

AI in asset management explained fully must include the limitations. Models trained on historical data perform poorly when market regimes change. Overfitting produces tools that work in backtests but fail in live environments. And AI outputs require experienced interpretation to avoid acting on statistically significant but economically meaningless signals.

The ZCG Team approaches AI adoption with the same discipline it applies to investment underwriting. Every tool requires a defined use case and a measurable success metric. A review process keeps experienced judgment in the decision chain. That framework prevents the common failure mode where AI adoption generates activity without improving outcomes.

Firms that treat AI as a capability layer on top of sound investment processes generate sustainable advantages. Those that treat AI as a replacement for process discipline find the technology amplifies existing weaknesses. It rarely corrects them.