Conference Presentation, Panel, Fireside Chat
The Future of Finance
Milken InstituteDavid Faber, Mike Cagney, Brian Chin, Tom Farley, Louise Pentland, Igor Tulchinsky, Christian McGuire
- SoFi projects that nontraditional data sources like cell phone and utility bill data will soon be utilized in underwriting, potentially outperforming FICO scores by 40% once computing power and algorithms mature, though the technology is currently in nascent stages.
- Credit Suisse anticipates piloting the AI compliance tool "Reggie" to reduce compliance call center volume by 50%, resulting in a headcount shift away from processing roles toward technology while maintaining a need for human interaction with institutional and private bank clients.
- WorldQuant expects its workforce to continue doubling annually for the foreseeable future, projecting a growth curve peak in 10 to 15 years, with expansion driven by diverse opinions and the necessity of managing the shift from 100 to millions of annual signal generations.
- PayPal expects mobile technology to enable universal payments ("pay for anything from anywhere to anyone"), while forecasting that automation will retool workers into higher-skilled roles rather than simply replacing them, necessitating regulatory engagement to avoid stifled innovation.
- Tom Farley predicts that NYSE data volume could reach 100 times the current 10 to 20 billion messages within 10 years, potentially creating opportunities for wealthy entrepreneurs to solve distribution challenges, while the IPO process is expected to become more efficient and cost-effective over the next 20 years.
- SoFi envisions a future where community-based financial models expand beyond geographic boundaries to include employers or shared interests, predicting that traditional banks will attempt to adopt this interactive approach to engage 35-year-old demographics.
- Brian Chin observes that ubiquitous market data is creating efficiency and reducing opinion divergence, leading to a future where alpha is generated only from deviations of the second, third, or fourth standard deviation away from consensus views.
- Igor Kolchinsky expects the complexity of combining increasingly predictable individual data points to amplify the role of technology in making sense of information, despite the world becoming more complicated to assemble.
- Mike Cagney identifies regulatory and rating agency resistance to new data methodologies as a primary risk, citing an "agency problem" where risk asymmetry and the Consumer Financial Protection Bureau's empirical proof requirements create a "chicken and egg" situation for nontraditional underwriting.
- Tom Farley forecasts that regulators may eventually shift toward a "thousand flowers bloom" approach involving crowdsourcing, while Louise Pentland expects banking to bifurcate between high-touch and low-touch models depending on the service required.