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Podcast news and reviews

IBAC Tech Trek podcast

In this episode of the iBAC Tech Trek Insurance Podcast, host Tom Reid is joined by industry veterans Graham Haigh and Cam Loeppky to discuss the evolution of insurance technology, the rise of insurtechs, and the impact of AI on the industry. They explore the challenges and opportunities in connectivity, the importance of leadership in […]

IBAC Tech Trek podcast

In this episode of the IBAC Tech Trek podcast, Tom Reid interviews Greg Toothe from Acturis, discussing the company’s journey in the Canadian insurance market. They explore Acturis’ growth, the importance of API connectivity, challenges in the Canadian insurance landscape, and the future of insurance technology. Greg emphasizes the need for accurate pricing, the role […]

IBAC Tech Trek podcast

In this episode of the iBAC Tech Trek podcast, hosts Tom Reid, Christy Barsalou, and Jeff Barsalou discuss the innovative insurance technology company QuickFacts. They delve into the founding story of QuickFacts, its functionality in aggregating underwriting guidelines, and how it enhances efficiency for brokers. The conversation also covers the benefits for customers, security measures […]

IBAC Tech Trek podcast

Tom Reid and Michael Scarbeau talk about HSB Canada, part of Munich Re, is Canada’s premier engineering-driven specialty insurer.

IBAC Tech Trek podcast

Tom Reid and Stacey Miranda, Sr. Director of Product Management, at Vertafore talk about what’s new.

IBAC Tech Trek podcast

Tom Reid and Jamie Ross explore the intersection of technology and brokerage in the insurance industry. Jamie shares insights on the tech stack used at Wedgwood Insurance, emphasizing the importance of tools like HubSpot and their website in enhancing the client experience.

IBAC Tech Trek podcast

Tom Reid speaks with Simon Hlywa, president of Calefy, about the innovative approach to insurance technology that Calefy offers.

IBAC Tech Trek podcast

Tom Reid speaks with Mislav Majic, the Chief Revenue Officer of SimplePin, a company that automates financial operations for insurance providers.

IBAC Tech Trek podcast

Tom Reid speaks with Chendi Ni and Kai Jai, the founders of Sonar AI, about their innovative AI-driven platform designed for insurance brokers.

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Aligning with Regulatory Frameworks and Standards

Principles will align with international AI guidelines (e.g., ISO 42001, OECD frameworks) and industry-specific regulations (e.g., RIBO, OSFI, AMF) upheld by stakeholders. Adherence to legal standards will help organizations navigate jurisdictional requirements, promote sustainable practices, and prevent misuse of AI data

Encouraging Responsible Al Innovation

Principles will encourage the broker community to innovate responsibly by developing AI systems that prioritize consumer well-being, inclusivity, and fairness, while also assessing the societal, environmental, and economic impacts of their AI solutions

Promoting Accountability in AI Oversight

AI principles will reinforce accountability across all levels of organizations and third-party collaborators. By defining roles, ensure human oversight in AI processes, this enhances traceability, enables informed decision-making, and embeds mechanisms for ethical redress when errors or adverse outcomes occur

Ensuring Consumer Trust and Fairness

AI governance principles support commitment to transparency, fairness, and accountability. By requiring explainable outcomes and proactive consumer communication, it fosters trust among the broader broker community, their clients, and external stakeholders

Supporting Ethical Standards and Stakeholder Collaboration

By incorporating AI governance principles, broker members can align with its mission of fostering an ethical culture among its stakeholders Address biases, safeguard consumer protection, and promote inclusivity, which will reinforce commitment to ethical AI practices in collaboration with industry stakeholders, regulators, and third-party solution providers

PoC Use Case Overview: Al-Assisted Coverage Discovery & Gap Analysis

Technical Requirements

AI models with context on industry benchmarks and policy structures to interpret existing policy terms, endorsements, and clauses.

Integration with BMS to retrieve client profiles, exposure information, and historical policy data.

Data ingestion and continuous updates to ensure alignment with typical coverage patterns and industry guidance.

Data security and compliance features to protect client information.

Functional Scope

Analyze client-submitted data, including exposures, business context, and other relevant information.

Extract and interpret existing policy terms (e.g., endorsements, exclusions, clauses).

Benchmark against typical coverage patterns and industry guidance to identify coverage gaps.

Prioritize identified coverage gaps and provide rationale based on considerations such as industry standards and risk.

Recommend relevant products and coverage options tailored to the client profile, and generate summaries for client discussions.

AI-Powered Client Onboarding & Data Intake – Overview:
Proof of Concept (PoC) Use Case

Technical Requirements

BMS Integration: Integration with BMS for secure data capture and storage.

Applied ARS Integration: Integration with Applied ARS to enable automated quote generation.

Dedicated Parsers for Renewal: Document parsing capability for 5–6 carrier renewal documents with high accuracy.

Extensibility Framework: Modular architecture to support future enhancements and additional automation.

Functional Scope

AI Chatbot for Client Onboarding: Collect client information, answer onboarding questions, and guide users through the onboarding process.

Data Collection & Storage: Capture and store collected data directly in the broker’s BMS.

Document Processing: Enable clients to upload renewal documents and extract key data to accelerate the onboarding process.

Quotes Generation: Generate quotes based on collected information.