Fintech Impact

Host Jason Pereira interviews Greg Bogich, CEO of AcquireUp, a wealth-management-focused marketing services firm that helps advisors drive organic net-new asset growth by filling in-person seminars and workshops using direct mail, digital targeting, and data enrichment. Bogich explains AcquireUp’s origins as a merger of White Glove (digital-driven educational seminars with post-event pay models) and AcquireDirect (direct-mail and market/registrant insight technology) backed by Rockbridge Growth Equity. He outlines the process: define goals and ideal client profile, map local opportunity in Perspectix, target households near venues, capture registrations in LeadJig, and augment attendee data to help advisors prepare and prioritize follow-up. Typical campaigns involve two events, ~30 attending households from ~60 registrations, 8–14 meeting requests, and 1–2 closes, often producing strong ROI; AcquireUp runs about 100 seminars per day and sees opportunity in nurturing non-converting registrants.Episode Highlights:00:00 Welcome and Guest Intro00:37 What AcquireUp Does01:03 Origins and Early Success02:19 Merger and Private Equity04:24 Advisor Onboarding Process05:40 Targeting and Lead Data07:59 Conversion Tracking Limits09:11 Ideal Client and ROI Math10:54 Data Sources and Local Focus12:26 Why In-Person Works13:55 Campaign Example Breakdown16:41 Scaling and Nurturing Leads20:22 Relationship Building Lessons22:32 Rapid Fire Closing Questions26:17 Wrap Up and SponsorResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorAcquireUpLinkedIn - Greg Bogich’s LinkedIn

In episode 450 of FinTech Impact, host Jason Pereira welcomes back John O’Connell, founder and CEO of The Oasis Group, to unpack how generative AI has reshaped wealth management technology since ChatGPT’s launch. They discuss the proliferation of large language models, falling token costs, and why most advisory workflows don’t require frontier models. The conversation emphasizes pairing probabilistic AI for design and prototyping with deterministic tools like Python for repeatable, secure execution, and clarifies the difference between true agents and “glorified calculators.” They also cover the risks of vibe-coding into production, the importance of SDLC, vendor due diligence, and training, plus how orchestration layers are still immature. Looking ahead, O’Connell predicts more embedded agentic AI, reduced busywork, faster career paths, and previews Tara, Oasis’s digital worker for wealth tech intelligence.Episode Highlights:00:00 Welcome Back, John00:58 Oasis Group Overview02:12 Gen AI Changes04:52 Model Costs Matter07:10 Low-Cost Agents09:40 Deterministic Workflows12:13 What Is An Agent17:31 Vibe Coding Limits20:51 SDLC And Security27:05 Orchestration Agents29:36 Alfred Orchestration Limits32:03 Agents Need Real Engineering33:59 Vibe Coding Reality Check37:20 Hallucinations And Determinism39:19 Future Of Agentic Advisors43:20 Digital Worker Defined47:24 AI As Team Multiplier50:15 Training And Adoption Advice55:50 Tara Digital Worker Launch57:20 Wrap Up And CreditsResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorThe Oasis GroupLinkedIn - John O’Connell’s LinkedIn

In this episode of Fintech Impact, host Jason Pereira sits down with Joshua Summers, co-founder and CEO of Enfi. Enfi is an AI platform built to take the grind off lending teams—automating everything from document extraction and underwriting to portfolio monitoring and credit memo drafting.Summers says the company started after he spotted a glaring bottleneck in credit: lenders are bogged down doing 70 to 80 percent of their work on repetitive, low-value tasks. He walks through why off-the-shelf LLMs don’t cut it for this kind of work. Credit decisions require a tightly controlled framework—specialized ontologies, strict routing, built-in quality checks, and the kind of audit trails and explainability that regulators actually expect.They dig into why vertical, specialized AI agents are a better fit than broad, general-purpose models in regulated finance. Summers shares some hard numbers, too: clients have unlocked $300 million in additional lending volume without adding a single head, cut annual review turnaround from eight hours down to 45 minutes, and completely cleared an indirect auto backlog in just 90 minutes.The conversation wraps up with Enfi’s hands-on “proof of value” rollout strategy, and the human side of the equation—how teams actually adjust their workflows and mindset when bringing AI into established credit departments.Episode Highlights:00:00 Welcome and Guest Intro00:34 What Enfi Does01:24 Origin Story and Insight02:42 The Human Capacity Crisis04:56 How Enfi Fits Workflows07:12 Credit Harness and Ontology10:00 Why Generic LLMs Fail11:01 Harnesses and Regulation15:57 Routing Models and Evals20:04 Customer Results and ROI22:07 Scaling Adoption and Change25:53 Rapid Fire Closing Questions31:11 Wrap Up and SponsorFacebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorEnfiLinkedIn - Joshua Summers’ LinkedIn

In this episode of FinTech Impact, host Jason Pereira interviews Gene Farrell, CEO of Vanilla, an estate planning platform built to help advisors deepen multigenerational client relationships by creating, managing, and analyzing estate plans. Farrell explains the company’s origins with founder Steve Lockshin, who turned a manual, time-intensive document-review process into software, then scaled it into a standalone business after raising a Series A led by Venrock in 2021. The conversation covers Vanilla’s client engagement tools like Estate Health Check, state-specific document building, and AI-driven analysis that flags gaps such as improperly executed documents, unfunded trusts, or outdated plans after interstate moves. Farrell also details why Vanilla was built for enterprise early—driven by clients like Vanguard—emphasizing security, role-based controls, and obfuscating PII from AI models, while staying focused on end-to-end estate planning depth rather than expanding into adjacent tools.Episode Highlights:00:00 Welcome to Fintech Impact00:33 Future-Proof Ice Cream Banter01:12 What Vanilla Does01:58 How Vanilla Started04:44 Gene Joins as CEO06:15 Getting Clients Engaged07:32 Estate Planning Explained11:25 AI Document Analysis12:43 Growing AUM and Family Ties16:19 Attorney Network and Flexibility18:17 Why Enterprise First22:54 Staying Focused on Estate25:42 Rapid Fire Closing Questions31:51 Final Thanks and Wrap UpResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorVanillaLinkedIn - Gene Farrell’s LinkedIn

In this episode of FinTech Impact, Jason Pereira sits down with Dr. Toby Wade, CEO of DeepVest, to explore how wealth management firms can leverage AI without worrying about false information or incorrect math. Wade explains how DeepVest’s "hallucination-free" AI stack uses pre-coded, deterministic calculations for structured financial data, ensuring the system returns exact portfolio analytics and refuses to guess unsupported numbers. Listeners will learn how DeepVest evolved from natural-language backtesting into a complete advisor platform that accelerates proposal generation, portfolio stress-testing, and meeting prep. By integrating directly with existing CRMs and custodians, the platform helps advisors win new business and scale AUM without taking on the role of a custodian or trading desk.  Give this episode a listen to discover how deterministic AI is giving wealth managers institutional-grade analytics without the risk of hallucinations.Episode Highlights:00:00 Welcome to Fintech Impact00:37 What DeepVest Does00:57 Origin Story and Focus01:56 Deterministic Analytics Engine04:25 Why LLMs Hallucinate07:04 Expanding Into Proposals08:41 All In One Advisor Platform10:15 Data Context and Guardrails14:34 Real World Advisor Wins18:33 Future Butler Service Vision19:59 Where DeepVest Wont Play21:20 Rapid Tech Adoption Wish23:23 Startup Challenges and Wrap24:39 Closing and Sponsor MessageResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorDeepVestLinkedIn - Toby Wade’s LinkedIn

In this episode of FinTech Impact, Jason Pereira sits down with Cien Solon, founder of Launch Lemonade, to explore how domain experts can build custom AI tools without writing code. Solon explains how the platform acts as an AI marketplace, allowing industry experts to package their knowledge into specialized AI "agents" that businesses can safely deploy.The conversation highlights how Launch Lemonade solves low corporate AI adoption by providing a secure, audit-friendly environment that supports over 100 language models. By combining flexible model options with natural-language workflow tools, the platform allows regulated businesses to automate complex tasks while ensuring complete data privacy and compliance.Be sure to give this episode a listen to discover how custom AI agents are helping experts monetize their knowledge and giving businesses a safer way to adopt AI.Episode Highlights:00:00 Welcome and Guest Intro00:30 What Launch Lemonade Does01:12 Origin Story and Branding02:24 Why Generic AI Fails04:15 Expert Built Agents and Security05:50 Defining Agents and Harnesses08:38 Multi Model Strategy and Costs16:13 Building and Running Workflows18:41 Customers and Use Cases21:46 Roadmap Payments and Collaboration25:00 Founder Q and A Wrap Up29:55 Final Thoughts and OutroResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorLaunch LemonadeLinkedIn - Cien Solon’s LinkedIn

Connecting fragmented advisor data into a unified, AI-driven workflow is the central theme of this episode, as Jason Pereira sits down with Boris Rankov, Head of AI for Wealth at InvestCloud. Rankov breaks down how InvestCloud—a wealthtech giant supporting $8 trillion in assets—is evolving its SMART AI and PM Plus capabilities to make wealth management more accessible and efficient.Listeners will get an inside look at how InvestCloud builds secure, enterprise-grade AI using semantic layers, guardrails, and deterministic tools to guarantee accuracy in regulated markets. Rankov highlights how these agent-orchestrated workflows simplify advisor operations by surfacing real-time insights, automating meeting prep and CRM follow-ups, and expanding research access—all while keeping human advisors firmly in the loop to maintain client trust.Be sure to give this episode a listen to discover how enterprise AI is reshaping advisor workflows and laying the groundwork to democratize wealth management.Episode Highlights:00:00 Welcome to Fintech Impact00:36 Meet InvestCloud01:18 SMART Platform Flywheel02:37 Adapting to GenAI04:52 Semantic Layer and Data05:27 Reliability and Eval Harness07:42 Agent Orchestration Explained10:47 Validation and Release Testing17:51 Advisor Wins and Workflow20:05 Client Portal and Trust21:35 Rapid Fire Questions25:36 Closing and SponsorResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorInvestCloudLinkedIn - Boris Rankov’s LinkedIn

Host Jason Pereira interviews Bruno Teixeira, founder of Aegis AI Analytics, about helping mid-sized firms strategize and implement AI in workflows. Teixeira, with 20 years in analytics across banks in Brazil and Canada and experience on CPP Investments’ gen AI team, explains that smaller firms can adopt AI faster due to less bureaucracy but must avoid treating AI like a “genie” or automating broken processes. He emphasizes change management, hands-on enablement (hackathons, office hours, champions), and aligning workflow and incentives rather than simply distributing tools like Copilot. Success should be measured by meaningful productivity and output gains, not prompt counts, using team-appropriate metrics and incremental automation targets (e.g., reducing validation work hours). He advises not to wait for new frontier models and to improve outcomes through clearer context and reverse-engineering desired outputs.Episode Highlights:00:00 Welcome and Guest Intro00:31 Bruno’s Background in AI02:28 Why Mid-Sized Firms Struggle04:21 Picking the Right Use Case06:09 AI and the Workforce Reality08:47 Adoption Programs That Work10:10 Hands-On Training and Champions12:45 Deployment Checklist and Measurement14:39 KPIs and Automation ROI16:44 Common Pitfalls and Prompting21:58 Getting Started and Final Q&A26:33 Wrap-Up and Sponsor MessageResources:Facebook – Jason Pereira's FacebookLinkedIn – Jason Pereira's LinkedInWoodgate.com – SponsorAegis AI & AnalyticsLinkedIn - Bruno Texeira’s LinkedIn