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You could do better. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus leo diam, dictum sed velit vitae, ornare fringilla turpis. Aenean luctus est eu justo pretium, at tempor metus posuere. Sed vitae suscipit mi. Maecenas at ante ac ex tempor consequat quis eu orci. Nulla nec ipsum ut eros porta fermentum non bibendum tortor. Nulla lacinia eros ligula, nec egestas libero vehicula ut. Donec venenatis ullamcorper mi, sit amet dignissim elit dictum et. Nam lectus purus, imperdiet sed metus eget, maximus bibendum urna. Phasellus id pulvinar purus. Sed ullamcorper, risus vitae congue scelerisque, est nibh fermentum nibh, quis sagittis ex felis ac est. Quisque consequat pellentesque fringilla. Ut viverra vehicula felis, aliquam viverra ligula sagittis sed. Nulla in suscipit leo. Quisque pulvinar porttitor quam, ut consectetur felis semper sit amet.

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YOUR RESPONSE

RECOMMENDATION

Explainability

Question: Can you provide clear and understandable explanations to customers?

Your answer:

AI Risk assessment workshop

AI intention Workshop

Engineering suite review

Engineering Documentation review using AI

Engineering Inventory


Redress

Question: Do you have processes available for customers to contest or seek redress for decisions made by your AI system, and are these processes communicated to and accessible by your customers?

Your answer:

AI Redress process and policy workshop

AI labs showcase

AI labs snippets

AI labs – App package/chatbot download


Fairness

Question: Have you implemented measures to ensure that your AI system does not exhibit biases or discrimination against any specific groups, particularly in terms of gender, race, or socioeconomic status?

Your answer:

AI governance review workshop

UX. Experience review

Data model intenvory

Data inventory

Hosted model monitoring


Safety

Question: Do you have measures in place to ensure that your AI system for banking decisions is resilient to adversarial attacks and operates reliably under various conditions, including atypical or high-stress scenarios?

Your answer:

Hosted AI security blueprints

Engineering stress test

Threat modelling

Toxic prompt removal

Infrastructure datacenter

Malicious traffic


Accountability

Question: Do you have governance structures and accountability mechanisms in place to oversee the development, deployment, and continuous monitoring of your AI system?

Your answer:

AI governance workshop

Enterprise Architecture

Engineering monitoring and audit

Engineering Inventory – do you know what you have, what are you able to see across processes

Identify and access management – what was it you planned in terms of who could do what


You could do better. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus leo diam, dictum sed velit vitae, ornare fringilla turpis. Aenean luctus est eu justo pretium, at tempor metus posuere. Sed vitae suscipit mi. Maecenas at ante ac ex tempor consequat quis eu orci. Nulla nec ipsum ut eros porta fermentum non bibendum tortor. Nulla lacinia eros ligula, nec egestas libero vehicula ut. Donec venenatis ullamcorper mi, sit amet dignissim elit dictum et. Nam lectus purus, imperdiet sed metus eget, maximus bibendum urna. Phasellus id pulvinar purus. Sed ullamcorper, risus vitae congue scelerisque, est nibh fermentum nibh, quis sagittis ex felis ac est. Quisque consequat pellentesque fringilla. Ut viverra vehicula felis, aliquam viverra ligula sagittis sed. Nulla in suscipit leo. Quisque pulvinar porttitor quam, ut consectetur felis semper sit amet.

Cras fermentum consectetur lorem sed maximus. Curabitur porta libero et volutpat efficitur. Donec condimentum viverra elit eget pellentesque. Ut a libero dolor. Morbi placerat nunc ac leo sagittis iaculis. Nullam eget faucibus justo, eget ornare ligula. Donec nisi tellus, elementum vel dui ac, gravida porttitor erat. Phasellus sit amet augue justo. Donec porta fermentum augue accumsan molestie. Pellentesque auctor nulla vel dapibus aliquet.

YOUR RESPONSE

RECOMMENDATION

Explainability

Question: Can you provide clear and understandable explanations to customers regarding how your AI system determines insurance?

Your answer:

AI Risk assessment workshop

AI intention Workshop

Engineering suite review

Engineering Documentation review using AI

Engineering Inventory


Redress

Question: Do you have processes available for customers to contest or seek redress for decisions made by your AI system, and are these processes communicated to and accessible by your customers?

Your answer:

AI Redress process and policy workshop

AI labs showcase

AI labs snippets

AI labs – App package/chatbot download


Fairness

Question: Have you implemented measures to ensure that your AI system does not exhibit biases or discrimination against any specific groups, particularly in terms of gender, race, or socioeconomic status?

Your answer:

AI governance review workshop

UX. Experience review

Data model intenvory

Data inventory

Hosted model monitoring


Safety

Question: Do you have measures in place to ensure that your AI system for insurance decisions is resilient to adversarial attacks and operates reliably under various conditions, including atypical or high-stress scenarios?

Your answer:

Hosted AI security blueprints

Engineering stress test

Threat modelling

Toxic prompt removal

Infrastructure datacenter

Malicious traffic


Accountability

Question: Do you have governance structures and accountability mechanisms in place to oversee the development, deployment, and continuous monitoring of your AI system?

Your answer:

AI governance workshop

Enterprise Architecture

Engineering monitoring and audit

Engineering Inventory – do you know what you have, what are you able to see across processes

Identify and access management – what was it you planned in terms of who could do what


You could do better. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus leo diam, dictum sed velit vitae, ornare fringilla turpis. Aenean luctus est eu justo pretium, at tempor metus posuere. Sed vitae suscipit mi. Maecenas at ante ac ex tempor consequat quis eu orci. Nulla nec ipsum ut eros porta fermentum non bibendum tortor. Nulla lacinia eros ligula, nec egestas libero vehicula ut. Donec venenatis ullamcorper mi, sit amet dignissim elit dictum et. Nam lectus purus, imperdiet sed metus eget, maximus bibendum urna. Phasellus id pulvinar purus. Sed ullamcorper, risus vitae congue scelerisque, est nibh fermentum nibh, quis sagittis ex felis ac est. Quisque consequat pellentesque fringilla. Ut viverra vehicula felis, aliquam viverra ligula sagittis sed. Nulla in suscipit leo. Quisque pulvinar porttitor quam, ut consectetur felis semper sit amet.

Cras fermentum consectetur lorem sed maximus. Curabitur porta libero et volutpat efficitur. Donec condimentum viverra elit eget pellentesque. Ut a libero dolor. Morbi placerat nunc ac leo sagittis iaculis. Nullam eget faucibus justo, eget ornare ligula. Donec nisi tellus, elementum vel dui ac, gravida porttitor erat. Phasellus sit amet augue justo. Donec porta fermentum augue accumsan molestie. Pellentesque auctor nulla vel dapibus aliquet.

YOUR RESPONSE

RECOMMENDATION

Explainability

Question: Can you provide clear and understandable explanations to customers regarding how your AI system determines creditworthiness and lending decisions?

Your answer:

AI Risk assessment workshop

AI intention Workshop

Engineering suite review

Engineering Documentation review using AI

Engineering Inventory


Redress

Question: Do you have processes available for customers to contest or seek redress for decisions made by your AI system, and are these processes communicated to and accessible by your customers?

Your answer:

AI Redress process and policy workshop

AI labs showcase

AI labs snippets

AI labs – App package/chatbot download


Fairness

Question: Have you implemented measures to ensure that your AI system does not exhibit biases or discrimination against any specific groups, particularly in terms of gender, race, or socioeconomic status, when making lending decisions?

Your answer:

AI governance review workshop

UX. Experience review

Data model intenvory

Data inventory

Hosted model monitoring


Safety

Question: Do you have measures in place to ensure that your AI system for lending and credit decisions is resilient to adversarial attacks and operates reliably under various conditions, including atypical or high-stress scenarios?

Your answer:

Hosted AI security blueprints

Engineering stress test

Threat modelling

Toxic prompt removal

Infrastructure datacenter

Malicious traffic


Accountability

Question: Do you have governance structures and accountability mechanisms in place to oversee the development, deployment, and continuous monitoring of your AI system used for lending and credit?

Your answer:

AI governance workshop

Enterprise Architecture

Engineering monitoring and audit

Engineering Inventory – do you know what you have, what are you able to see across processes

Identify and access management – what was it you planned in terms of who could do what