Live systems, not slides
Sessions include live demonstrations of agentic investment and risk systems running in production at NaviMod.
NaviMod Executive Programs
Agentic AI in Financial ServicesFrom strategy and governance to working agents
Executive programs, hands-on workshops and corporate AI labs that take banks, asset managers and financial institutions from AI strategy to working agents, taught by the team that builds and runs agentic AI systems in finance.
2,500+Professionals trained in executive programs led by our program director
10+ yearsOf research in AI, quantitative finance and financial analytics
Istanbul & MiamiPrograms available in both regions and in-house globally
Why NaviMod
Taught by people who build these systems
Most AI programs explain the technology from a distance. Ours come from a team that designs, deploys and governs agentic AI systems for financial institutions every day.
Academic depth
Rooted in a university spin-off from Istanbul Technical University, with published research in machine learning, financial engineering and multi-agent systems.
Institutional experience
Built from work with clearing houses, portfolio managers, investment firms and banks on AI, analytics and trading systems.
From learning to delivery
Every program ends with a concrete next step, and the same team can take your institution from prototype to production.
For Institutions
From first briefing to working agents
Agents change who does the work, who decides and who is accountable, so the transformation is as much organizational as technical. Four in-house programs take your institution through it as one path: leadership sets the direction, teams prove what works, and a joint lab turns it into a real system.
1
Learn
Build shared understanding at the top: what agentic AI changes in finance, where it creates value, and what the institution should do next.
2
Build
Prove feasibility with working agents built with your teams.
3
Scale
Validate the use case on your data, measure the results and build the business case.
Executive Briefing opens the conversation. The Executive Program identifies the opportunities. The Hands-on Workshop proves feasibility. The Corporate AI Lab turns the opportunity into a real project.
Learn
Agentic AI in Financial Services: Executive Briefing
A focused 90-minute briefing that equips boards and executive committees to oversee the move to AI and agentic AI with confidence.
- Duration
- 90 minutes
- Format
- In-house, in person or online
- For
- Boards, CEOs and executive committees
What you take away
- Five questions to ask about any AI agent: what it sees, who sets its goal, what it decides, when a person steps in, and how it is stopped
- Board checklist for overseeing AI and AI agents
- A leadership-level view of where the institution stands
Next step
The turns leadership direction into a concrete plan.
Agenda
Three short segments and a discussion
- From GenAI to agentic AI. What changes when AI can act, what is hype, and what it means for competitive position20 min
- Agentic AI in action. A live demonstration of agents running investment and risk workflows20 min · Demo
- Risk, regulation and board oversight. Accountability when agents act, and whether the institution can still explain and stop what they do20 min
- Discussion. Where does our institution stand, and what should we do first?30 min
Learn
Agentic AI in Financial Services: Executive Program
A strategic program on how agentic AI is reshaping financial services, and how your institution should lead the transformation.
- Duration
- 2 days
- Format
- In-house for your leadership team
- For
- C-suite, EVPs and heads of strategy, digital banking, investment, operations, risk and technology
Before and after
- Before: Agentic maturity assessment, from monitoring and suggestions to supervised and autonomous execution
- 30 days after: Online Roadmap Review session
What you take away
- Agentic maturity snapshot for your institution
- Prioritized portfolio of agentic use cases (value vs. feasibility)
- Decision autonomy map: which decisions agents may take, which they recommend, and which stay with people
- Strategic roadmap for the agentic transformation
Next step
The prototypes your highest-priority use case.
Day 1
Understanding the shift
- From GenAI to agentic AI: what changes when AI can act
- How agents are reshaping banking, payments and investment management
- Agentic systems in action: investment research and risk workflowsLive demo
- Agentic use cases across front, middle and back office
Day 2
Leading the transformation
- The agentic operating model: how roles shift from doing the work to setting goals, limits and exceptions, and who owns an outcome end to end
- Earning autonomy: the evidence, controls and governance that let agent authority widen safely
- Build vs. buy vs. partner: strategic choices for financial institutions
- Use-case prioritization and transformation roadmapWorkshop
Build
Agentic AI in Financial Services: Hands-on Workshop
Your teams build a financial agent, connect agents into a governed workflow, then prototype a use case from your own institution.
- Duration
- 3 days
- Format
- In-house, 12–24 participants
- For
- Mixed teams from business, technology and risk
- Prerequisites
- None. No coding required
- Environment
- A ready-to-use NaviMod sandbox. No installation and no internal data needed
What you take away
- Two guided financial agents
- A multi-agent workflow with human approval
- A prototype for your own use case
- Feasibility and Lab Readiness Report
Next step
The workshop shows the concept works. The validates it on your institution's data and infrastructure.
Day 1
Your first financial agents
- Designing a governable agent: its goal, the context it works from, the tools and permissions it holds, and when it must stop and escalate
- Financial Research Agent. Turns news, filings and market data into an investment briefLab 1
- Risk Monitoring Agent. Tracks volatility regimes and generates alertsLab 2
Day 2
From agents to a governed workflow
- When is one agent not enough? Deciding whether splitting the work is worth the coordination cost
- Multi-agent workflow. Research and risk agents combined with clear handoffs, stopping rules and a human approval stepLab 3
- How do you know it works? Testing, audit trails and human-in-the-loop controlsWorkshop
Day 3
Bring your own use case
- Framing your institution's use case with the NaviMod teamWorkshop
- Building a working prototype on public, synthetic or sandbox dataBuild
- Demo Day: presentation to your executive sponsor
- Lab readiness assessment
Scale
Corporate AI Lab
A structured engagement that turns a validated use case into a working agent proof of concept, a business case and a production roadmap.
- Duration
- 10–12 weeks
- Format
- Joint NaviMod and client team
- Where
- In your environment, in your cloud or on-premises, with the models your policies allow
- Data
- Stays under your control, under NDA and your data governance policies
What you take away
- A working proof of concept on your own data
- Before-and-after results against a measured baseline
- Evaluation and governance pack covering authority and accountability, audit trail, verification and stop controls, to support your internal model risk and AI governance review
- Business case, production architecture and pilot plan
How it works
Measured results, not just a demo
Discover
Use-case inventory, data and infrastructure assessment, and a baseline of how the process runs today
Design
Use-case selection, solution architecture, success KPIs and executive sponsor alignment
Build
Iterative development on institutional data, starting with one agent at a supervised level of autonomy
Evaluate
Testing against historical and synthetic cases for accuracy, groundedness, policy compliance and cost: the evidence needed before autonomy widens
Demo Day
Results, business case and pilot recommendation presented to the executive committee
Scale
Pilot and production roadmap, widening agent authority step by step as evidence builds
Team
- NaviMod: AI architect, data scientist, software engineer
- Your institution: executive sponsor, product owner, domain experts, IT and data
Example lab themes
- Investment research agent
- Portfolio risk monitoring and regime detection agent
- Credit memo and credit analysis agent
- Compliance and document review agent
- Wealth advisory assistant
Specialist modulesAvailable on request, in-house
AI-Driven Investment & Quantitative Finance
1–2 days. ML-based prediction and alpha signals, portfolio optimization, regime detection and backtesting pitfalls.
AI Risk, Regulation & Governance
1–2 days. Model risk for AI agents, explainability, human oversight, the EU AI Act and regional regulation, AI governance operating models.
Program Leadership
Program Director
The programs are designed and led by NaviMod's founder, with guest faculty from banking and FinTech joining selected sessions.
Program Director
Prof. Dr. Alp Ustundag
Founder & CEO, NaviMod Financial Analytics Solutions
Alp Ustundag founded NaviMod as a university spin-off to turn research in machine learning, optimization and financial analytics into production systems for banks, asset managers and market infrastructure institutions. At Istanbul Technical University he served as Professor of Industrial Engineering and as founding chair of the Department of Data Engineering and Business Analytics, where he established its M.Sc. in Big Data and Business Analytics. He founded and directed ITU's Big Data and Business Analytics and Data Science certificate programs for individual professionals and corporate cohorts. His advisory and systems work spans Takasbank, Ziraat Portfolio, Ak Investment, Akbank and Deutsche Bank Türkiye.
2,500+Participants in executive programs he designed and led
300+Graduates of the M.Sc. program he founded
4,400+Citations across 31 refereed journal articles
20+Funded research projects
Author of The Agentic AI Company: How AI and Multi-Agent Systems Are Transforming Business (Springer, forthcoming) and editor of Business Analytics for Professionals and Industry 4.0: Managing the Digital Transformation (Springer). Ph.D. in Industrial Engineering, ITU; MBA, Boğaziçi University.
FAQ
Common questions
Which program should my institution start with?
Most institutions start with the Executive Briefing or the Executive Program to agree on direction. Teams that already have a clear use case can start directly with the Hands-on Workshop. Every program can be booked on its own.
Do we need to share internal data for the Hands-on Workshop?
No. The workshop runs in a NaviMod sandbox on public, synthetic or sample data. Your teams bring the use case, not the data. Working with institutional data happens only in the Corporate AI Lab, under NDA and your governance policies.
Do participants need technical or coding skills?
No. All programs are designed for executives and mixed business, technology and risk teams. The hands-on labs use a guided, no-code environment.
Can the content be adapted to our institution or region?
Yes. In-house programs are tailored with use cases, regulation and examples relevant to your business line and market, whether you operate in Türkiye, the United States or elsewhere.
In which language are the programs delivered?
Programs are delivered in English or Turkish, depending on the cohort or the institution.
Where does the Corporate AI Lab run?
In your environment, in your cloud or on-premises, with the models your policies allow. Institutional data stays under your control throughout the engagement.
How do we get started?
Send an inquiry below. We will reply with the program outline, a proposed format for your institution and available dates.
Program Inquiries
Discuss agentic AI for your institution
Tell us what you are looking for. We will reply with the program outline and the next available dates.
Program Director
Prof. Dr. Alp Ustundag · LinkedIn
Email
info@navimod.com
Locations
Miami, Florida, USA
ITU Ayazaga Campus, ARI Teknokent, Istanbul, Türkiye
ITU Ayazaga Campus, ARI Teknokent, Istanbul, Türkiye