Grant Thornton Bharat Compliance Associate Interview Questions and Answers

Auditing is important to ensure accuracy, compliance, and transparency in financial reporting.

• Auditing helps to detect and prevent fraud and errors in financial statements.

• It ensures compliance with laws and regulations, such as the Sarbanes-Oxley Act.

• Auditing provides assurance to stakeholders that financial information is accurate and reliable.

• It helps to identify areas for improvement in financial management and rep...read more

I chose this company because of its strong reputation, innovative culture, and opportunities for growth.

• The company has a proven track record of success and is highly regarded in the industry.

• I am impressed by the company's commitment to innovation and staying ahead of the curve.

• There are ample opportunities for professional development and advancement within the company.

• The company's values align with my own, particul...read more

I plan to advance my career in project management and this role aligns with my goal.

• I have a strong interest in project management and have been actively pursuing certifications in this field.

• This role will provide me with valuable experience in managing projects and working with cross-functional teams.

• I believe that the skills and knowledge I gain in this role will be transferable to future project management position...read more

Rewrite and reinstatement are two different methods of policy modification.

• Rewrite involves creating a new policy from scratch, while reinstatement involves restoring a lapsed policy.

• Rewrite may result in changes to coverage, premiums, and terms, while reinstatement typically restores the policy to its original state.

• Examples of when to use rewrite include major life changes or significant changes in risk, while reinst...read more

No, the company will not process the claim.

• The policy was cancelled in June due to non-payment.

• The policyholder reinstated the policy in September.

• The claim arises in August, which is before the policy was reinstated.

• Since the policy was not active in August, the company will not process the claim.

Yes

• I have extensive experience in stakeholder management throughout my career.

• I am comfortable in pushing back stakeholders when necessary and standing my ground.

• I prioritize open and effective communication with stakeholders to ensure their needs are met.

• I have successfully managed stakeholders in various projects, including one where conflicting interests needed to be resolved.

• I believe in building strong relationshi...read more

I perform and manage under pressure by staying calm, prioritizing tasks, seeking support, and maintaining focus.

• Stay calm and composed to think clearly and make rational decisions

• Prioritize tasks based on urgency and importance

• Seek support from colleagues or supervisors when needed

• Maintain focus by setting goals and breaking them down into manageable steps

• Example: In my previous role, during a high-pressure project dea...read more

Successfully managed campaigns and negotiated between stakeholders for various projects.

• Developed and executed a social media campaign for a non-profit organization, resulting in a 30% increase in donations.

• Negotiated with vendors to reduce costs by 15% for a company's annual conference.

• Managed a political campaign, coordinating with volunteers and stakeholders to ensure a successful election.

• Collaborated with cross-fu...read more

I am looking for a challenging role where I can contribute my expertise and continue to grow professionally.

• Opportunity to work on complex projects

• Ability to lead and mentor junior team members

• Continued learning and professional development

• Opportunities for advancement and career growth

• Collaborative and supportive work environment

Supervised ML is a type of machine learning where the algorithm is trained on labeled data to make predictions or classifications.

• Supervised learning involves a dataset with labeled examples

• The algorithm learns from the labeled data to make predictions on new, unlabeled data

• Examples include image classification, spam filtering, and predicting housing prices

• Common algorithms include decision trees, logistic regression,