FINOS Open Source in Finance Podcast

FINOS
  • 5.0 (5)
  • Technology
  • Biweekly

The FINOS Open Source in Finance Podcast celebrates open source projects and interesting topics at the cross section of financial services and open source. So far, our industry experts have discussed practical applications of and their real-world experiences with a range of open source projects including desktop interoperability, low code platforms, synthetic data, and data modeling. They’ve also discussed best practices for inner source, common myths about open source and why commercial companies choose to introduce open source offerings. Tune in to hear what comes next.

  1. 2d ago

    How Do You Govern AI-Generated Code in a Bank - Archrails

    Explore Open Source in Finance with the Archrails project. Learn how this framework simplifies complex banking infrastructure.Grizz Griswold hosts brothers Mark and Kervins to discuss the evolution of their project and its role in modern financial systems. This conversation covers their tech origin stories and the shift toward structured development within regulated environments.The team breaks down how the CALM standard integrates with Archrails to solve common hurdles when working with banks. Listeners will gain insight into the current open source in finance landscape, including a preview of upcoming talks at OSFF and predictions for how AI will impact the industry over the next six months.Subscribe for more technical engineering breakdowns in finance.0:00 Meet the Founders of Arch Rails1:38 Paths to Technology: Engineering vs Operations7:39 Defining the Problem Space for Arch Rails12:42 Discipline is Freedom: The Power of Constraints18:36 Governing AI-Generated Pull Requests24:01 Predicting the Future of AI in Finance🗽 Catch Us in New York! Ready to enforce architectural governance and safely scale AI-generated code? Join global financial technology leaders at OSFF New York on November 4–5, 2026.🎟️ Register Now: https://hubs.ly/Q04n_bZL0🔥 20% OFF DISCOUNT CODE: 26YTOSFFNY20C🌐 More about FINOS: https://www.finos.org/📧 Join our newsletter: https://www.finos.org/sign-up🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcastsLinkedIn: https://www.linkedin.com/company/finosfoundation#FINOS #OSFFNewYork #Archrails

  2. 6d ago

    Monica Mock-Sipos - The "Spy vs. Spy" Approach to AI Security in Banking | Red Hat

    Host Grizz Griswold sits down with Monica Mock-Sipos, OpenShift Platform Leader for Financial Services (FSI) North America at Red Hat. Drawing on her background in enterprise IT architecture and cybersecurity, Monica explains why banks must shift their focus from perimeter "model security" to securing the full execution path of agentic AI workflows. From navigating non-deterministic logic and mid-workflow context shifts to deploying containment architectures on Kubernetes, this episode breaks down how financial institutions can safely operationalize AI without breaking compliance.🕒 Timestamps:* 0:00 - Welcome to the FINOS Podcast * 1:12 - What is an OpenShift Platform Leader? * 2:52 - Tech Sales vs. Architect-Led Engineering * 4:27 - From Building Architecture to Cyber Security * 7:04 - What Actually is Red Hat OpenShift? * 8:51 - Managing Non-Deterministic AI Risk in Finance * 10:11 - The Danger of Mid-Workflow Context Shifts * 11:31 - MCP Tool Exposures and the Anthropic Mythos Shock * 12:38 - Why You Must Secure the Full Execution Path * 14:42 - What to Expect at OSFF New York * 16:36 - "Spy vs. Spy": Why AI is the Only Defense Against AI 📊 The Problem: False Model Boundaries & Mid-Workflow Shifts* Inadequate Perimeter Defenses: Security strategies that only filter prompt inputs and outputs fail to protect the broader execution path where agents call external tools and internal banking APIs. * Mid-Workflow Context Shifts: Agentic workflows react dynamically. A transaction context can change halfway through a process—like a new fraud alert arriving during a delayed human approval step—derailing static security assumptions. * Vulnerability Proliferation: Custom DIY security stacks lack the bandwidth to keep pace with AI-accelerated vulnerability scanners, leaving unhardened environments open to machine-speed exploit chains. 🏗️ The Solution: Execution Path Hardening & Containment* Continuous Verification: Enforcing ongoing authentication, authorization checks, and least-privilege tool entitlements across every leg of a multi-step workflow until task completion. * Containment Architecture: Deploying containerized workload isolation on top of Kubernetes (OpenShift) so that runtime failures or compromised agent tasks cannot spread laterally into critical core systems. * AI vs. AI Defense: Embedding applied AI directly into the platform fabric to monitor, isolate, and remediate machine-speed attack vectors automatically (a "Spy vs. Spy" approach). ⚙️ Why This Matters for Financial Engineering* Safe Production Scaling: Empowers financial engineering teams to transition agentic AI prototypes into regulated production environments without breaching strict audit or compliance standards. * Audit-Ready Observability: Captures granular telemetry across all agent actions, tool calls, and state changes to deliver the verifiable, replayable audit logs required by financial regulators. 🌐 More about FINOS: https://www.finos.org/📧 Join our newsletter: https://www.finos.org/sign-up🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcastsLinkedIn: https://www.linkedin.com/company/finosfoundation

  3. Oct 14

    The 28-to-0 Controls Debate: Are Your Pipelines Secure? Alex Kantor, Kosli - OS in Finance Podcast

    On this episode of the FINOS Open Source in Finance Podcast, host Grizz Griswold sits down with Alex Kantor, Director of Technology at Kosli and maintainer for the FINOS Open SDLC Controls Framework. Alex shares his career journey from bypassing slow manual controls to turning automated governance into a competitive advantage—scaling deployments from 2 to 23 per day. He unpacks his famous "race car brakes" metaphor, tackles the explosion of automated AI vulnerability scanners, details the impact of the EU Cyber Resilience Act on SBOM tracking, and explores who is verifying AI-generated code in pull request reviews. 🕒 Timestamps:0:00 Welcome to the FINOS Open Source in Finance Podcast1:12 OSFF NY Announcement & Hands-On SDLC Workshop Preview2:10 Alex Kantor’s Role at Kosli: Governance Engineering Platform4:32 Career Roots: From Unix Infrastructure to Tesco Bank6:29 Poacher Turned Gamekeeper: Shifting from Control Dodger to Owner8:43 Automating Segregation of Duties: Scaling from 2 to 23 Deployments/Day11:25 The Race Car Brakes Metaphor: Why Controls Drive Speed13:29 FINOS SDLC Controls Framework: Speaking a Common Language with Auditors17:52 AI in the SDLC: Who’s Checking the AI Reviewers?19:18 Rising Vulnerabilities, Mythos Scanners & EU CRA SBOM Mandates24:40 OSFF New York Talk Preview & Hands-On Workshop Details27:08 The 28-to-0 Controls Debate: New Vectors, Same Core Risks30:08 Homework for Engineers: Turning Silent Human Trust into Automated Checks 📊 The Problem: Friction-Heavy Governance & Rapid AI Vulnerability ExploitationControls as Bureaucratic Roadblocks: Enterprise financial institutions frequently treat software delivery controls as friction—relying on manual spreadsheets, screenshot gathering, and rigid team-to-team handoffs that stall innovation and delay time-to-market. Accelerated Exploit Windows: Automated AI scanning engines (such as Mythos) are identifying and exploiting software vulnerabilities at unprecedented rates, shrinking remediation windows to negative days and flooding bug bounty channels with alerts. Fragmented Audit Definitions: Inconsistent nomenclature across internal audit teams, engineering orgs, and external regulators creates policy paralysis and compliance confusion under upcoming frameworks like the EU Cyber Resilience Act (CRA). 🏗️ The Solution: Governance Engineering & The FINOS Open SDLC FrameworkAlex Kantor outlines how Kosli and FINOS help engineering teams automate controls to move faster: The "Race Car Brakes" Philosophy: Treating automated controls not as speed limiters, but as high-performance brakes that give developers the confidence to push release velocity to the limit. Automated Evidence & Segregation of Duties: Capturing continuous, immutable provenance across CI/CD pipelines to prove person-to-person segregation of duties and track live Software Bills of Materials (SBOMs) without manual audit overhead. FINOS SDLC Common Controls Catalog: Establishing an open, standardized taxonomy of software development controls so banks, auditors, and regulators share an unambiguous operational language. ⚙️ Why This Matters for Financial EngineeringDramatic Delivery Acceleration: Automating audit evidence collection eliminates release bottlenecks, enabling regulated firms to jump from batched deployments to continuous daily delivery. Governing Agentic Coding: Replaces silent, unverified trust in human reviewers with explicit, automated pipeline assertions to govern both human and AI-generated code changes. 🌐 More about FINOS: https://www.finos.org/ 📧 Join our newsletter: https://www.finos.org/sign-up 🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts LinkedIn: https://www.linkedin.com/company/finosfoundation#FINOS #OSFFNewYork #Kosli

  4. Oct 9

    A discussion about how to apply brain neuroplasticity to engineering of learning

    On this episode of the FINOS Zenith Podcast, host Peter Smulovics sits down with neuroscientist Aki Nikolaidis (Co-Founder & Chief Scientist) to explore how brain neuroplasticity, cognitive science, and 3D virtual reality (VR) environments are transforming professional training. Aki explains the neural circuits behind procedural skill acquisition (cortico-striatal-thalamo-cortical loops), why traditional multiple-choice testing fails to measure true competence, and how high-resolution behavioral analytics (millisecond and millimeter tracking) unlock near-transfer skill acquisition. Discover how VR flight deck simulators achieve 4-day training footprint reductions and how NSF-funded biometric research is paving the way for personalized AI tutors. 🕒 Timestamps:0:00 Welcome & Setup: Asking How the Brain Learns1:20 Aki’s Journey: From Cognitive Neuroscience to Aviation Training4:08 Checklists & Procedural Learning in High-Stakes Environments7:20 How Skills Form in the Brain: Cortico-Striatal Circuits & Unitization10:52 Expert Blindness & Moving Beyond Executive Function11:24 Productive Difficulty vs. Friction: Why Variability Boosts Transfer13:42 Beyond Pass/Fail: High-Resolution Behavioral Analytics15:04 NSF SBIR Award: Biometric Micro-State & Cognitive Detection17:16 Personalized AI Tutors (Digital Aristotle) & Evaluation Ethics21:57 Real-World Evidence: CommuteAir Flight Deck VR Case Study25:18 Near Transfer vs. Far Transfer: Thorndike’s First Principles29:42 Novelty vs. Durable Learning: Brain Calorie Economics & Decay33:19 Scaling VR Training to Technicians & Complex Operations38:28 Spatial Workstations, Screen Real Estate & Content Generation Costs45:03 Rethinking Competence: Why Multiple Choice Tests Fail49:15 Closing Remarks: Can We Truly Engineer Learning? 📊 The Problem: Static Assessments & Fragile Skill RepresentationsThe Limitations of Pass/Fail Testing: Traditional corporate and high-stakes training relies heavily on passive video watching or multiple-choice questions, evaluating if an answer was selected correctly rather than how the brain acquired and processed the underlying skill. Fragile Skill Representations: Rote practice in fixed, non-variable settings creates fragile neural representations that quickly degrade over time due to brain calorie economics and fail to transfer during real-world, high-stress operational anomalies. 🏗️ The Solution: Spatial VR Simulators & High-Resolution Behavioral AnalyticsAki Nicolaidis outlines how cognitive neuroscience and spatial technology combine to engineer durable learning: Accelerating Cortico-Striatal Unitization: Deploying 3D VR environments that closely match real-world performance contexts, shifting skill execution off heavy executive function (prefrontal cortex) into automated procedural circuits. Near-Transfer First Principles: Grounding training in Thorndike's law of near transfer—ensuring the learning environment's spatial fidelity directly mirrors the real-world operational environment. Millimeter & Millisecond Analytics: Replacing subjective 1-5 evaluation scales with continuous eye-tracking, hand position, and gesture telemetry to detect cognitive fatigue, hesitation, and stress micro-states. Personalized AI Tutors (Digital Aristotle): Utilizing air-gapped, student-centric AI tutors to adapt practice scenarios to an individual's specific learning decay without generating punitive surveillance records. 🌐 More about FINOS: https://www.finos.org/ 📧 Join our newsletter: https://www.finos.org/sign-up 🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts LinkedIn: https://www.linkedin.com/company/finosfoundation

  5. Oct 7

    Why Autonomous Agents Are the Next Major Risk in Finance - Heather Domin

    On this episode of the FINOS Open Source in Finance Podcast, host Grizz Griswold speaks with Heather Domin, Global Head of the Office of Responsible AI and Governance at HCLTech. Heather shares her 20-year journey in data science and AI ethics, discussing why 76% of organizations delay AI deployments over responsible AI concerns. She explores the evolution from simple model risk to autonomous compounding risks in agentic workflows, the rise of the "Agentic Web" across financial transactions, and how the FINOS AI Governance Framework (AIGF) enables regulated banks to deploy audit-ready AI guardrails without hindering innovation velocity. 🕒 Timestamps:0:00 Welcome to the FINOS Open Source in Finance Podcast0:34 Executive Women’s Forum & Speaker Intro1:18 OSFF New York Announcement & Fluxnova Con Preview2:43 Heather Domin’s Journey: Data Science to Responsible AI Lead4:16 The Evolution of AI Ethics: From Research to the EU AI Act7:12 Why 76% of Organizations Delay AI Over Governance Concerns8:51 Evolving Risks: From GenAI Hallucinations to Autonomous Agentic Chains10:45 Managing High-Risk Financial AI vs. Retail Use Cases12:12 Overcoming AI Fear: Policy, Process & Technical Controls16:28 Reasons for Optimism: Upskilling & Inbuilt Safety Controls18:49 The Next Wave: Financial Transactions on the "Agentic Web"21:22 OSFF Talk Preview: Operationalizing the FINOS AI Governance Framework (AIGF) 📊 The Problem: The AI Deployment Bottleneck & Compounding Agent RisksThe 76% Deployment Freeze: HCLTech research reveals that 76% of enterprises delay AI rollouts due to responsible AI, governance, and regulatory uncertainty. Evolving Risk Profiles: Moving from generative AI text outputs to autonomous agentic chains introduces compounding, multi-step transaction risks that traditional model risk management frameworks cannot capture. Regulated Capital Risk: Financial institutions handle high-risk customer assets where un-governed agentic decisions carry severe legal, reputational, and financial consequences. 🏗️ The Solution: Responsible AI Governance & The FINOS AIGFHeather Domin details HCLTech's approach to operationalizing responsible AI: Control by Design: Embedding policy rules, threshold limits, and entitlement checks directly into AI platforms so developers innovate inside safe, automated guardrails. FINOS AI Governance Framework (AIGF): Leveraging open-source, consensus-driven control definitions tailored specifically for financial services to standardize risk mitigations across the software lifecycle. Governing the Agentic Web: Preparing enterprise architectures for cross-firm autonomous agent interactions, ensuring multi-step financial transactions across web protocols maintain auditability and human oversight. ⚙️ Why This Matters for Financial EngineeringUnlocking Scaled Production: Transitions financial institutions past prototype paralysis by establishing verifiable guardrails that satisfy regulatory mandates (such as the EU AI Act) without slowing engineering velocity. Human-in-the-Loop Orchestration: Ensures high-impact financial actions executed by autonomous agents retain explicit human oversight, verification checkpoints, and incident logging. 🌐 More about FINOS: https://www.finos.org/ 📧 Join our newsletter: https://www.finos.org/sign-up 🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts LinkedIn: https://www.linkedin.com/company/finosfoundation #FINOS #OSFFNewYork #AIGovernance

  6. Sep 30

    James Calise & Travis Liles - Oracle - The Open Source Shift: Oracle Experts Reveal What's Next

    On this episode of the FINOS Open Source in Finance Podcast, host Grizz Griswold sits down with James Calise (Pre-Sales Engineering Lead) and Travis Liles (Cloud Architect) from Oracle Cloud Infrastructure (OCI) Financial Services. Together, they explore how Oracle is shifting from proprietary models to open-standards-based cloud architecture to help financial institutions prevent vendor lock-in, meet strict DORA multi-cloud resiliency mandates, and scale grid computing across on-premise and multi-cloud environments with OpenGris. Plus, they share how autonomous AI agents are becoming the next-generation operational management layer for open-source enterprise platforms. 🕒 Timestamps:0:00 Welcome to the FINOS Open Source in Finance Podcast0:53 Guest Introductions: James Calise & Travis Liles (Oracle Cloud)5:17 Verticalized Cloud Engineering for Financial Services8:11 Why Financial Compute Remains Heavily On-Premise & Legacy10:23 Mainframe Migrations vs. Performance Realities11:18 Oracle’s Shift to Open Standards & Breaking Cloud Lock-In14:46 DORA Regulations & Multi-Cloud Resiliency Mandates17:25 Introducing OpenGris: Bursting Grid Compute Across Multi-Cloud20:45 Bridging High-Performance Computing (HPC) with AI24:00 Pace-Layered Architecture: Secret Sauce in the Agent Layer28:22 Avoiding Hype: Actionable AI without Vendor Box-In32:05 Autonomous AI Agents as 24/7 Open-Source Operations Managers36:50 Oracle’s Expanding FINOS Contributions & OSFF Preview 📊 The Problem: Cloud Lock-In, On-Prem Ceilings & Admin OverheadCloud Lock-In & DORA Compliance Barriers: Proprietary cloud services lock financial institutions into closed ecosystems, making multi-cloud resiliency and regulatory compliance (e.g., DORA exit plans) nearly impossible to execute. On-Premise Compute Ceilings: Financial risk modeling and overnight grid calculations require massive bursts of compute power that exceed fixed on-premise hardware ceilings, yet low-latency requirements keep core systems tied to legacy infrastructure. Administrative Overhead for Open Source: Adopting self-hosted open-source platforms turns internal engineering teams into full-time IT administrators tasked with manual monitoring, patching, and operational upkeep. 🏗️ The Solution: Open Standards, OpenGris & Autonomous AI AgentsOpen Standards Cloud Foundation: OCI builds its financial cloud infrastructure around open standards, enabling institutions to deploy workloads seamlessly across on-premise, dedicated regions, and multi-cloud environments. OpenGris Elastic Bursting: Leveraging the OpenGris project to schedule and scale financial compute jobs elastically across cloud providers based on performance, availability, and cost. Agentic AI Operations Layer: Deploying 24/7 autonomous AI agents as a management layer that actively monitors open-source projects, applies patches, tests builds, and automates operational maintenance. ⚙️ Why This Matters for Financial EngineeringPace-Layered Innovation: Standardizes baseline infrastructure and APIs, allowing capital markets firms to build their core IP and competitive advantage directly into the agentic AI layer. Smooth Onboarding & Multi-Cloud Flexibility: Eliminates re-skilling delays and proprietary rewrites, giving financial engineering teams true mobility across hybrid and multi-cloud platforms. 🌐 More about FINOS: https://www.finos.org/ 📧 Join our newsletter: https://www.finos.org/sign-up 🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts LinkedIn: https://www.linkedin.com/company/finosfoundation #FINOS #OSFFNewYork #Oracle

  7. Sep 23

    Nichola Hammerton - Deutsche Bank - Why Enterprise Architecture Needs Open Source

    On this episode of the FINOS Open Source in Finance Podcast, host Grizz Griswold sits down with Nichola Hammerton, Head of Architecture at Deutsche Bank, in Canary Wharf, London. Nichola shares her unique career trajectory—from studying chemistry and co-founding a tech consulting firm to restructuring the British Red Cross and leading large-scale capital markets transformations. She details how Deutsche Bank is embedding "control by design" into its enterprise AI architecture platforms, navigating the interplay between legacy mainframes and cutting-edge AI agents, and why cross-industry open-source collaboration on projects like FINOS Fluxnova is essential for solving shared industry challenges. 🕒 Timestamps:0:00 Welcome & Catching Up on the FINOS Open Source in Finance Podcast1:15 Current Role: Head of Architecture at Deutsche Bank3:30 Career Journey: From Chemistry to Consulting & The Red Cross7:14 Large-Scale Tech Transformation During the Credit Crunch9:45 What is Architecture? Focus on Business Outcomes Over Tech Hype10:55 Control by Design: Embedding AI Governance & Controls13:12 Mainframes & Legacy Infrastructure in the Age of AI14:36 Data Quality, Freshness & Semantic Layers for AI Agents16:00 Open Source Consolidation & Cross-Firm Collaboration (Fluxnova)18:08 Why Concrete Use Cases Drive Effective Architecture19:21 Building Architecture vs. Technology Architecture 📊 The Problem: AI Governance Overload & Architecture Disconnected from OutcomesRapid AI Adoption Risks: Deploying autonomous AI agents without embedded governance creates massive code review backlogs, data entitlement risks, and quality control overhead. Technology for Technology's Sake: Architectural designs often get caught up in technological hype rather than focusing strictly on measurable business outcomes and operational use cases. Legacy Interoperability: Modern AI platforms must operate alongside decades-old core banking infrastructure (such as mainframes) that remains essential for daily operations. 🏗️ The Solution: "Control by Design" & Use-Case-Driven Open CollaborationNichola Hammerton outlines a strategic approach to modern enterprise architecture: Embedded Control-by-Design: Building security, compliance, and governance frameworks directly into the underlying architecture platform so developers can innovate safely without managing controls manually. Data Quality & Semantic Layers: Establishing robust data freshness, entitlement management, and semantic layers to power reliable end-user AI agents. Consolidation Through Open Source: Collaborating across buy-side and sell-side institutions on shared infrastructure (such as FINOS Fluxnova) to pre-solve common use cases and access broader talent pools. ⚙️ Why This Matters for Financial EngineeringShift from Delivery to Strategic Architecture: Empowers technology leaders to establish guardrails that scale across vast enterprise portfolios while maintaining operational stability. Grounding AI in Real-World Use Cases: Ensures AI investments deliver business value by anchoring architectural designs to specific operational problems rather than abstract tech capabilities. 🌐 More about FINOS: https://www.finos.org/ 📧 Join our newsletter: https://www.finos.org/sign-up 🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts LinkedIn: https://www.linkedin.com/company/finosfoundation

  8. Sep 15

    [OSFF Panel] Can Open Data Solve Financial Data Pain Points?

    In this episode of the Open Source in Finance Podcast, host Grizz Griswold introduces an expert OSFF panel moderated by Hilary Carter (Linux Foundation) featuring Jose Plehn (Bright Query / open-data.org), Nora Anwar (Overture Maps Foundation), and Jane Gavronsky (FINOS COO). The panelists explore why financial services urgently need a shared open data commons to eliminate duplicate reference data maintenance, establish a universal entity graph across companies, people, and places, and ground AI models to prevent hallucinations. 🗽 Catch Us in New York! Ready to explore open data, shared entity graphs, and collaborative open-source engineering? Join global financial technology leaders at OSFF New York on November 4–5, 2026.🎟️ Register Now: https://hubs.ly/Q04n_bZL0🔥 20% OFF DISCOUNT CODE: 26YTOSFFNY20C 🕒 Timestamps:0:00 Podcast Intro with Grizz Griswold & Panel Setup1:34 Panelist Introductions: Bright Query, Overture Maps & FINOS3:45 Why Open Data Matters: Breaking Down Financial Data Silos5:00 The Vision of an Open Entity Graph: Companies, People & Places7:57 Governance & Community Scale: Cross-Referencing Master IDs11:06 Winners & Losers in the Open Data Landscape13:11 Financial Reference Data Pain Points: The "Light Switch" Analogy16:55 Crowdsourcing Entity Resolution & Identifier Mapping20:13 Overture Maps Origin Story: Meta, Microsoft, Amazon & TomTom Collaboration25:06 Geospatial Data Use Cases: From Insurance Risk to Fraud Detection29:10 Open Data for AI Grounding: Reducing LLM Hallucinations with RAG34:07 Success Metrics & How Financial Institutions Can Join 📊 The Problem: The "Light Switch" Reference Data Tax & Fragmented SilosRedundant Reference Data Maintenance: Financial institutions spend millions of dollars individually ingesting, cleaning, and enhancing identical vendor reference datasets just to keep basic systems operational. Entity Resolution & Identifier Disconnects: Mismatched entity IDs (LEIs, CUSIPs, ISINs, addresses) across disparate corporate databases create massive operational friction, slowing down KYC/KYB compliance, onboarding, and risk management. 🏗️ The Solution: A Shared Open Data Commons & Global Entity GraphGlobal Reference & Entity Graph: Bright Query and open-data.org are establishing an open global directory covering over 400M companies, 1B people, and 200+ countries mapped with unique, permanent entity IDs. Overture Maps Collaboration Model: Following the proven Linux Foundation model of Overture Maps (founded by Meta, Microsoft, Amazon, and TomTom), competitors mutualize base data maintenance costs so teams can focus on proprietary innovation layers. Grounding AI & RAG Pipelines: Joining LLM knowledge graphs to deterministic open entity graphs drastically reduces hallucinations during AI training and inference, providing the verifiable data lineage required in regulated finance. ⚙️ Why This Matters for Financial Engineering Mutualizing Non-Competitive Costs: Crowdsourcing entity matching, validation rules, and cross-referencing tables removes the "thankless" overhead of reference data cleanup across buy-side and sell-side firms. Spatial & Corporate Context for AI Agents: Integrating open entity graphs with spatial systems (GERS IDs) gives AI agents accurate organizational and geographic awareness to automate risk assessment and site selection. 🌐 More about FINOS: https://www.finos.org/ 📧 Join our newsletter: https://www.finos.org/sign-up 🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts LinkedIn: https://www.linkedin.com/company/finosfoundation

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The FINOS Open Source in Finance Podcast celebrates open source projects and interesting topics at the cross section of financial services and open source. So far, our industry experts have discussed practical applications of and their real-world experiences with a range of open source projects including desktop interoperability, low code platforms, synthetic data, and data modeling. They’ve also discussed best practices for inner source, common myths about open source and why commercial companies choose to introduce open source offerings. Tune in to hear what comes next.

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