for Artificial Intelligence
Real-time AI and data analytics oversight platform that bridges the gap between the promises of AI and accountable execution.
The Challenge
Is your organization getting adequate ROI on advanced analytics and artificial intelligence initiatives?
If you are like most executives in regulated industries, the promise of advanced analytics is clouded by the risks of opaque black box decision making.
Who We Help
AI and advanced analytics are playing a meaningful role in financial services and health care.
These analytics can help improve efficiencies, adapt prices to real-time actions, and distinguish risk patterns across traditional data silos. Global enterprises continue to invest in leading technologies such as big data, unstructured analytics, and machine learning because of benefits AI can have on their bottom line.
Bank Survey: Top Reasons Banks Use Artificial Intelligence
Data Analytics & Insight
Increased Productivity
Cost Savings/Benefits
Healthcare Survey: Top 3 Reasons to Invest In AI
Revenue Growth
Customer Experience
Analytics & Decisions
#1 Provide transparency
with respect to data quality, availability, and sources
#2 Aligning analytics
to meet business objectives and requirements
#3 Access to traceability
in data-driven decisions and their support processes
#4 Ability to audit
or simulate critical business decisions in a systemically repeatable manner
#5 Protection
of the analytic engine “brain” from an insider threat
Black Box Blog & White Papers
Research
Accountable AI White Paper
Coming Soon
Insights
Black Box Blog
Who We Are
Our team’s mission at Talisai has been clear from the outset:
Create more transparency and accountability in advanced analytics.
Through decades of experience in digital transformation, cybersecurity, enterprise risk management, regulatory compliance, and data analytics, the leaders at Talisai identified a glaring need and deficiency in advanced analytics and modeling capabilities including Artificial Intelligence (AI). This lack of transparency and trust results in most data and analytics projects falling short of business objectives.
The promises and advantages of AI technologies are well documented, with AI expanding into mission-critical functions spawning entirely new industries. AI is evolving at hard-to-comprehend velocities and scale, all while playing significant roles in high-risk industries. With these advancements, an entirely new segment of risk is emerging, termed algo (algorithm) risk. AI, and any advanced analytics for that matter, is exposing organizations to dangerous new risks, particularly the risk of unknown algorithmic behavior with less human control. These risks are magnified in financial services, health care and all regulated industries.
At Talisai, we are passionate about optimizing integration between human-driven processes and data-driven intelligence, creating desperately needed transparency and trust.
Joonho Lee
Co-Founder, CEO
Joonho Lee is an innovative and strategic leader with more than 20 years of experience leading digital transformation, Fintech, Regtech, Cybersecurity, regulatory compliance and data management for the financial industry. Before co-founding TalisAI, at Federal Reserve Bank of New York and San Francisco, he served many roles including a Sr. VP & Chief Information Officer, a Transformation program director, Head of Strategy and Operations and a Managing officer of the Federal Reserve’s national Cybersecurity competency center.
Jonathan Heigel
Co-Founder, COO / CFO
Jonathan Heigel brings more than 20 years of consulting and industry operating experience, focusing on identifying and leveraging technical and data opportunities. Previously, Jonathan served as Principal at Diamond Technology Partners and a Partner at Sagence Consulting focused on regulatory compliance for financial services. He also co-led the strategy and innovation group for the nation’s largest tax preparer.