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Auto-discovery of hidden risk and demand trends in insurance

Significantly improving predictive power without changing your core model

“Instead of the months (or more) of time required by other vendors that we evaluated, only a few hours were needed to implement the amplifAIr™ solution.”

Global Top 10 Insurance Company, Lead Pricing Actuary

Uncover Additional Profits Using Segmentation

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Automatically quantify AI fairness in discovered segments

Quantify Compliance

Quantify Compliance
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Easy to check, easy to deploy, easy to reap the benefits

Frictionless

Frictionless
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We use only anonymized and historical outputs of our customers

No PII required

No PII required
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Identify hidden risk and demand segments and present them as readable rules

Model refinement

Model refinement

How It Works

Replace inefficient risk and pricing models

Generalized Linear Models (GLMs) are used to determine risk levels. The problem is that these models tend to be subjective, susceptive to over-fitting, and not adaptive to complex real-world scenarios. This leads to high claim frequency or default rates when pricing is too low and lost business when pricing is too high.

amplifAIr™ applies Advanced Artificial Intelligence to anonymized historical data. Learning algorithms are trained to identify customer segments whose risks are misaligned with pricing. With granular levels of information, new customers can be assigned to a subsegment that is based on their risk profile and offered pricing discounts that are calibrated to this risk.

Risk-Premium Alignment

Use Machine Learning to improve the models (linear, additive, etc.). In this way, it is now possible to close the gap between traditional risk assessment and actual risk.

Risk-Premium Alignment

Risk-Premium Alignment

Risk-Premium Alignment

Pricing Accuracy

With improvements in segmentation, customers can be offered pricing discounts that reflect their underlying risks, thereby optimizing portfolio profitability.

Pricing Accuracy

Pricing Accuracy

Pricing Accuracy

Alerts and Monitoring

Instead of periodic risk and policy updates, underwriters can receive updated customer segment information, allowing them to align risk and pricing in (close to) real-time.

Alerts and Monitoring

Alerts and Monitoring

Alerts and Monitoring

Human Readable Rules

AI does not have to be a ‘black box.’ amplifAIr™ model recommendations are easy to interpret so that they can be applied in real-world scenarios.

Human Readable Rules

Human Readable Rules

Human Readable Rules

Explainable AI and Data Transparency

Use Machine Learning to improve the models (linear, additive, etc.). In this way, it is now possible to close the gap between traditional risk assessment and actual risk.

Explainable AI and Data Transparency

Explainable AI and Data Transparency

Explainable AI and Data Transparency

More Revenue, Lower Loss Ratios

Maximize market share by offering competitively priced policies to lower-risk customers.

Improve Market Share by 14.3%

Improve Market Share by 14.3%

Aligning pricing with customer risk profiles leads to a reduction in the portfolio loss ratio.

Reduce Loss Ratio by 8.7%

Reduce Loss Ratio by 8.7%

The “noise” from risk misalignment hurts the bottom line. With amplifAIr, insurance companies and loan originators can build healthy portfolios and minimize loss ratios.

About Us

Frictionless pricing. A new approach to an old problem.

We founded amplifAIr™ as a game-changing platform designed to meet the challenges of pricing models in the BFSI sector.


Our frictionless platform mitigates pricing mismatches and increases market share and profitability.


With no IT time investment required, our platform offers instant value which can be implemented directly into your specific discount policy.

Instead of periodic risk and policy updates, underwriters can receive updated customer segment information, allowing them to align risk and pricing in (close to) real-time.

What

With improvements in segmentation, customers can be offered pricing discounts that reflect their underlying risks, thereby optimizing portfolio profitability.

How

Use Machine Learning to improve the models (linear, additive, etc.). In this way, it is now possible to close the gap between traditional risk assessment and actual risk.

Why

Meet The Team

Global product leader, steered strategy and teams to top results in competitive markets. VP R&D with AI focus. Pivotal role in driving sales strategies for Fortune 500 companies.

Bar Tsoury

Bar Tsoury

CEO, Co-Founder

Data science and AI expert, 15 years of experience. Algorithm groups leader in corporates and startups.

Avner Atias

Avner Atias

CTO & Co-Founder

Reuven Marko is an experienced hi-tech professional with over 40 years of experience.

Reuven Marko

Reuven Marko

Chairperson & Co-Founder

Dan Krubiner

Dan Krubiner

Director & Co-Founder

Nimrod Cohen is an skilled Managing Partner of TAU Ventures, a unique venture capital firm co-founded with Tel-Aviv University.

Nimrod Cohen

Nimrod Cohen

Board Observer

Dr. Giora Yaron is a renowned entrepreneur and investor with a wealth of experience in the high-tech and med-tech industries.

Dr. Giora Yaron

Dr. Giora Yaron

Board Observer

Why companies love amplifAIr

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Sean Farmer
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Sean Farmer

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Sean Farmer

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