Jun 26, 2017, 4:58 PM ETPanel

Shaping Digital Finance

Panelists represent a convergence of legacy banking, fintech disruption, and big tech:
- Michael Tannenbaum (SoFi, Chief Revenue Officer)
- Alfred Spector (Two Sigma, Chief Technology Officer)
- Julie Monaco (Citigroup, Corporate Investment Bank)
- Paul Hamill (Citadel Securities, Fixed Income Market Making)
- Corey Elston (Google Cloud Platform, Solutions Architect)
- David Rockefeller Jr. (Moderator/Observer)
Digitization is described as accelerating rapidly:
- Goldman Sachs reduced equity traders from 2,000 to effectively two (one to monitor the machine, one to manage the first).
- The inclusion of Google, Two Sigma, and Citadel Securities on the panel signals a shift from banking silos to multi-institution collaboration.
The pace of financial digitization is widely considered too slow:
- Core problems like mortgage applications, which were technically solvable 10 years ago, still take weeks to process.
- Finance is viewed as more resilient but slower to adopt than education and healthcare sectors.

Legacy banks are reclassifying fintechs from "disruptors" to "partners":
- Citi established Citi Ventures nine years ago to invest in and partner with fintech companies rather than fight them.
- Citi's strategy includes an open API framework via the Citi Fintech Group to allow external developer collaboration.
Fintechs are adopting "disruptor" identities while banks emphasize scale:
- SoFi identifies as a disruptor, utilizing a membership model and direct digital engagement rather than acting as a platform on top of a bank.
- Banks offer scale and regulatory trust, while fintechs offer speed, transparency, and specific customer acquisition models.
The role of human relationships in finance is evolving, not disappearing:
- As technology handles 80-90% of transactional volume (e.g., standard loans funded in a day), the remaining human interactions become higher-value, trust-based partnerships.
- Institutional clients require trust in new counterparties as liquidity drains from the system and market concentration shifts.

Blockchain and Distributed Ledgers:
- Use Cases: Focus is on multi-party complex transactions, trade finance, supply chain management, and instant settlement (eliminating daily reconciliation).
- Implementation Reality: Most financial blockchain implementations are "private" (permissioned), effectively functioning as high-trust databases rather than decentralized public ledgers.
- Barriers: Requires full digital end-to-end integration, digital identity verification, and significant legal/regulatory overhaul to move beyond legacy paper-based settlement.
- Currency Revolution: Consensus is low regarding a Bitcoin-style currency revolution; focus remains on back-end infrastructure and potential Central Bank Digital Currencies (CBDCs).
Machine Learning (ML) Applications:
- Underwriting: Used to trigger specific workflows for complex cases, such as identifying self-employed applicants who require additional documentation.
- Compliance: ML improves Anti-Money Laundering (AML) detection accuracy from ~80% to 99.4% in pilot programs, drastically reducing false positives.
- Pricing: Citadel Securities uses ML to continuously correlate global asset prices to precision-price risk in fixed income, equities, and FX.
- Adoption Gap: While high potential exists, ML adoption in large, older institutions lags due to regulatory caution and the difficulty of obtaining production approval for new algorithms.

Regulatory Environment:
- Current AML/KYC regulations are described as bureaucratic and expensive, creating high barriers to entry.
- Regulators are slowly adapting; the OCC recently created an innovation unit to collaborate with fintechs and financial institutions.
- Cybersecurity: Security is now a primary competitive differentiator for institutional clients; governments and large corporations demand proof of real-time monitoring and rapid recovery capabilities during due diligence.
Financial Inclusion in Emerging Markets:
- Success Stories: M-Pesa in Africa (telecom-led banking) and partnerships in Mexico (convenience store models) have brought financial services to millions of unbanked citizens.
- Anti-Corruption: Digital payment systems for government benefits reduce corruption, saving billions (est. $4 trillion globally) by eliminating bribe-based distribution.
- Data Sovereignty: Governments vary in their requirements for local data hosting; while inefficient, some nations mandate that unbanked services and data remain within national borders.
Future-Proofing:
- Experts warn that artificial intelligence solutions may be solved before cybersecurity threats are fully mitigated, necessitating intense focus on national-state level security threats.

Market Structure Changes:
- The future of finance is not geographically bound to Wall Street or Silicon Valley but is "everywhere" due to the scale of the unbanked 90% of the global population.
- Trust is shifting from individual bankers to institutional brands and regulatory frameworks underpinning technology platforms.
Hypothetical Startup Ideas from Panelists:
- Alfred Spector: An optimization platform for cross-industry scheduling and market structures (similar to Uber's model).
- David Rockefeller Jr.: A financial services focus on retirees, specifically housing and financing for aging populations.
- Julie Monaco (Citi): A company dedicated to reducing the economic cost of corruption ($4 trillion impact) by providing governments with technology tools.
- Paul Hamill (Citadel): A venture focused on restoring and providing liquidity in fixed income markets.
- Corey Elston (Google): Declined to bet on Google becoming a full-service bank or acquiring one in the next five years.