lyryx case study 4 answers

Course: ACCT 253 Ly Case Study 4 (Part 2) - Lyryx Learning Inc - Google Chrome lifa1.lyryx.com/student-servlets/CaseStudyServlet?ccid=10460 C lifa1.lyryx Part 2 [20 points] Tyryx

Course: acct 253 ly case study 4 (part 2) - lyryx learning inc - google chrome lifa1.lyryx.com/student-servlets/casestudyservletccid=10460 c lifa1.lyryx part 2 [20 points] tyryx purse home sunblush technologies inc.'s may journal entries have been posted to the general ledger for you as shown below. this is similar to how an accounting software package posts automatically. orrections and updates introduction to financial the accounting process adjusting accounts for fir the classified balance sh accounting for the sale of assigning costs to merch date 30/apr cash explanation account no. 101 ll f debit credit balance opening balance 132,500 1/may issued shares 1/may earned and received consulting revenue gj1 gj1 80,000 396 212,500 212,896 1/may prepaid for insurance gj1 3,600 209,296 cash and receivables 3/may received payment for consulting in advance gj1 7,800 217,096 long-lived assets 4/may paid for repairs to building gj2 400 216,696 current and long-term li 8/may earned and received consulting revenue gj2 371 217,067 equity financing 18/may paid for dinner with client gj2 90 *216,977 statement of cash flows 20/may received customer payment gj3 5,088 222,065 financial statement anal 25/may paid cash for salaries gj3 15,200 206,865 proprietorships and part 31/may ossary 31/may paid bill for utilities expense dividends gj3 700 206,165 gj4 4,500 201,665 ni spreadsheet 31/may paid for property taxes expense. gj4 600 201,065 it course date accounts receivable explanation account no. 106 f debit credit balance type here to search 30/apr opening balance. 6/may earned consulting revenue 15/may earned consulting revenue 18/may earned consulting revenue 20/may received customer payment 122,000 gj2 5,088 127,088 gj2 10,032 137,120 gj3 7,920 145,040 gj3 5,088 139,952 o introduction to fina... case study 4 (part 2... 8:00 pm 2/12/2024 w h c 0 x 1.lyryx case study 4 (part 2) - lyryx learning inc - google chrome 2 lifa1.lyryx.com/student-servlets/casestudyservletccid=10460 prepaid insurance account no. 128 date 1/may explanation f debit credit balance prepaid for insurance gj1 3,600 3,600 computers account no. 151 tes ancial a ocess date 2/may explanation f debit credit received computers gj1 15,600 balance 15,600 s for fir nce sh date sale of merch 30/apr opening balance building explanation account no. 173 f ll debit credit balance 54,500 les accumulated depreciation, building account no. 174 date erm li 30/apr opening balance explanation ll debit credit balance 4,000 flows nt anal nd parti date 30/apr opening balance accounts payable explanation account no. 201 f debit credit balance 70,500 2/may received computers gj1 15,600 86,100 22/may received bill for utilities expense gj3 700 86,800 31/may paid bill for utilities expense gj3 700 86,100 date 3/may unearned consulting revenue explanation account no. 230 f debit received payment for consulting in advance gj1 credit balance 7,800 7,800 date share capital explanation f debit credit account no. 301 balance search introduction to fina... case study 4 (part 2... e: acct 253 x ly case study 4 (part 2) lyryx learning inc - google chrome 2 lifa1.lyryx.com/student-servlets/casestudyservletccid=10460 lifa1.lyryx 10 ryx date 30/apr 1/may share capital explanation account no. 301 f debit credit balance opening balance. 188,000 issued shares ome ns and updates ction to financial a counting process ng accounts for fir ssified balance sh ting for the sale of ng costs to merch ad receivables date 31/may dividen dividends gj1 dividends explanation 80,000 268,000 account no. 302 f gj4 debit 4,500 credit balance 4,500 date retained earnings explanation account no. 318 ll f debit credit balance 30/apr opening balance_ 46,500 ved assets consulting revenue earned account no. 403 and long-term li financing date explanation ll f debit credit balance 1/may earned and received consulting revenue gj1 396 396 ent of cash flows ial statement anal torships and part 6/may earned consulting revenue gj2 5,088 5,484 8/may earned and received consulting revenue. gj2 371 5,855 15/may earned consulting revenue gj2 10,032 15,887 18/may earned consulting revenue gj3 7,920 23,807 dsheet e date salaries expense explanation account no. 622 f 25/may paid cash for salaries gj3 debit 15,200 credit balance 15,200 food and drinks expense account no. 668 date explanation f 18/may paid for dinner with client gj2 debit 90 credit balance 90 e here to search w e r introduction to fina... case study 4 (part 2... urse: acct 253 c x lifa1.lyryx 2 ly case study 4 (part 2) lyryx learning inc - google chrome lifa1.lyryx.com/student-servlets/casestudyservletccid=10460 c gryx home ions and updates duction to financial a accounting process ting accounts for fir classified balance sh unting for the sale of ning costs to merch and receivables account no. 668 balance 90 date food and drinks expense explanation 18/may paid for dinner with client. f debit gj2 credit 90 date property taxes expense explanation ll 31/may paid for property taxes expense. account no. 683 debit credit gj4 600 balance 600 date 4/may repair expense explanation account no. 684 f debit credit paid for repairs to building gj2 400 balance 400 utilities expense explanation f debit gj3 700 credit account no. 690 balance 700 lived assets date nt and long-term li y financing ment of cash flows cial statement anal ietorships and parti adsheet se 22/may received bill for utilities expense a) in account #668: o (i) the $90 debit came from page gj2 in the general journal. o(ii) the $90 debit came from page gj2 in the general ledger. o (iii) the balance is $90 on may 18. o (iv) $90 was posted from the general ledger on may 18. both (i) and (iii) are correct. both (ii) and (iv) are correct. all of (i), (ii) and (iii) are correct. all of (ii), (iii) and (iv) are correct. o none of the above. b) in account #174, the balance of $4,000 is the: e here to search introduction to fina... case study 4 (part 2... course: acct 253 c tyryx course home x lifa1.lyryx corrections and updates 1 introduction to financial a 2 the accounting process 3 adjusting accounts for fir 4 the classified balance sh 5 accounting for the sale of 6 assigning costs to merch 7 cash and receivables 8 long-lived assets 9 current and long-term li 10 equity financing 11 statement of cash flows 12 financial statement anal 13 proprietorships and parti glossary mini spreadsheet exit course ly case study 4 (part 2) lyryx learning inc - google chrome 2 lifa1.lyryx.com/student-servlets/casestudyservletccid=10460 o none of the above. b) in account #174, the balance of $4,000 is the: (i) cash balance in accumulated depreciation, building. (ii) ending balance in accumulated depreciation, building on april 30, 2023. (iii) total depreciation recorded to date on the asset. (iv) amount posted from the general journal. (v) beginning balance in accumulated depreciation, building. o both (ii) and iii) are correct. o all of (i), (iii) and (iv) are correct. o all of (i), (iii) and (v) are correct. o all of (ii), (iii) and (v) are correct. c) the $139,952 balance in account #106: (i) was calculated by taking the may 18 balance and subtracting the may 20 entry. o (ii) shows that there were 6 transactions recorded in the general journal. (iii) resulted from entries recorded on multiple pages in the general journal. o both (i) and (iii) are correct. o all of the above are correct. d) what is the next step in the accounting cycle o prepare an adjusted trial balance o prepare a post-closing trial balance analyze and journalize transactions o prepare closing entries o prepare financial statements o this is the last step 1 type here to search t 5 introduction to fina... case study 4 (part 2... 8 ourse: acct 253 c x 2 ly case study 4 (part 2) ~ lyryx learning inc - google chrome lifa1.lyryx.com/student-servlets/case studyservletccid=10460 lifa1.lyryx (ii) granny barano cumulated depreciation, dummy pi 00, 2020. gryx e home tions and updates duction to financial a accounting process sting accounts for fir (iii) total depreciation recorded to date on the asset. (iv) amount posted from the general journal. (v) beginning balance in accumulated depreciation, building. both (ii) and (iii) are correct. all of (i), (iii) and (iv) are correct. all of (i), (iii) and (v) are correct. o all of (ii), (iii) and (v) are correct. classified balance sh c) the $139,952 balance in account #106: unting for the sale of ning costs to merch and receivables -lived assets nt and long-term li ty financing ment of cash flows ncial statement anal rietorships and parti eadsheet se o (i) was calculated by taking the may 18 balance and subtracting the may 20 entry. o (ii) shows that there were 6 transactions recorded in the general journal. o (iii) resulted from entries recorded on multiple pages in the general journal. o both (i) and (iii) are correct. o all of the above are correct. d) what is the next step in the accounting cycle o prepare an adjusted trial balance o prepare a post-closing trial balance o analyze and journalize transactions o prepare closing entries o prepare financial statements o this is the last step o prepare adjusting entries o prepare an unadjusted trial balance e here to search submit and mark introduction to fina... case study 4 (part 2... .. dell, step by step solution.

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AML Case Study with Answers: Learning from Real-World Scenarios

In the ever-evolving landscape of financial crime, Anti-Money Laundering (AML) compliance is a critical priority for financial institutions. Despite robust frameworks and stringent regulations, many organizations still struggle with effective implementation, leading to significant lapses in AML compliance. Understanding real-world scenarios through case studies can provide invaluable insights into the practical challenges and solutions in this domain.

AML case studies highlight the complexities of preventing money laundering activities and showcase how organizations have either failed or succeeded in managing compliance. By analyzing these case studies, financial institutions can learn from past mistakes and successes, adapting their strategies to enhance their own AML frameworks.

This article explores several case studies, both from Tookitaki's extensive portfolio and industry examples, to provide a comprehensive view of AML compliance challenges and effective solutions. From e-wallets to traditional banks, each case study offers a unique perspective on how different financial entities navigate the complexities of AML compliance. Let's dive into these real-world examples and uncover the lessons they hold.

Case Study 1: E-Wallet Compliance Success with Tookitaki

The problem.

A leading e-wallet provider in Asia faced growing challenges in managing AML compliance. As the platform expanded, it struggled to identify suspicious activities accurately. The existing system generated too many false alerts, overwhelming the compliance team and making it hard to focus on real threats.

Tookitaki's Solution

Tookitaki implemented its Anti-Financial Crime (AFC) Ecosystem and FinCense platform. The solution used AI technology to improve transaction monitoring and reduce false alerts. Key features included:

• AI-Powered Monitoring: The platform analyzed transactions more accurately to spot suspicious activities.
• Better Alert Management: The system reduced false alerts, helping the team focus on genuine risks.
• Quick Scenario Updates: New AML scenarios were quickly added to keep up with emerging threats.

Results and Key Learnings

With Tookitaki's solution, the e-wallet provider saw:

• 50% Fewer False Alerts: The reduced false alerts saved time and resources.
• Improved Detection: More accurate identification of risky transactions.
• Faster Response: The ability to quickly adapt to new threats.

This case shows how advanced technology can help digital platforms stay compliant and secure.

Case study details

Case Study 2: Compliance Solutions for a Payment Processor

A global payment processor was struggling with its AML compliance due to a high volume of transactions and complex cross-border payments. The company faced challenges in detecting suspicious activities across different countries and currencies. Their existing system generated numerous false positives, making it difficult to identify genuine threats and comply with various regulatory requirements.

Tookitaki provided the payment processor with its FinCense platform, integrated with the AFC Ecosystem. The solution offered:

• Advanced AI Screening: The system used AI to accurately screen and monitor transactions, reducing false positives.
• Cross-Border Compliance: The platform handled multiple jurisdictions and currencies, ensuring compliance with different regulatory frameworks.
• Efficient Alert Management: Tookitaki’s solution prioritized alerts, allowing the compliance team to focus on high-risk transactions.

After implementing Tookitaki’s solution, the payment processor achieved:

• 60% Reduction in False Positives: The reduced false positives improved the efficiency of the compliance team.
• Enhanced Cross-Border Monitoring: The platform provided better oversight of international transactions, ensuring compliance across regions.
• Improved Compliance: The solution helped the company meet diverse regulatory requirements, reducing the risk of fines.

This case highlights the importance of using advanced technology to manage complex AML challenges in the global payments industry.

Case Study Details

Case Study 3: AML Compliance for a Digital Bank

A digital bank in Asia was facing difficulties in managing its AML compliance due to rapid growth and a diverse customer base. The bank's existing AML system was outdated and struggled to keep up with the evolving nature of financial crime. This led to an overwhelming number of false alerts and gaps in detecting suspicious activities, putting the bank at risk of regulatory penalties.

Tookitaki implemented its FinCense platform and AFC Ecosystem to strengthen the bank’s AML capabilities. The solution featured:

• Dynamic Risk Scoring: The platform used AI to continuously assess customer risk profiles, ensuring up-to-date evaluations.
• Enhanced Transaction Monitoring: The system monitored all transactions in real-time, using advanced models to identify unusual patterns.
• Integrated Alert Management: Alerts from various sources were consolidated, making it easier for the compliance team to investigate and take action.

With Tookitaki’s solution, the digital bank saw significant improvements:

• 45% Reduction in False Positives: The lower false alert rate allowed the compliance team to focus on real threats.
• Improved Risk Detection: The bank was able to identify and respond to suspicious activities more effectively.
• Streamlined Compliance Operations: The integrated system simplified the compliance workflow, reducing the time needed for investigations.

This case study illustrates how digital banks can enhance their AML efforts by adopting advanced technology and a comprehensive approach to risk management.

Case Study 4: Tackling AML Challenges in Traditional Banks

A traditional bank in Asia faced ongoing challenges in its AML compliance due to a large customer base and complex transaction types. The bank’s legacy system struggled to keep up with new regulatory requirements and evolving money laundering tactics. This resulted in numerous false alerts, delayed investigations, and increased risk of regulatory fines.

Tookitaki deployed its FinCense platform along with the AFC Ecosystem to upgrade the bank’s AML framework. The solution included:

• AI-Driven Monitoring: The platform used AI to monitor transactions in real-time, identifying suspicious activities with greater accuracy.
• Smart Alert Management: Tookitaki’s system reduced the volume of false alerts, helping the compliance team focus on high-risk cases.
• Efficient Case Management: Automated case management streamlined the investigation process, improving response times.

After integrating Tookitaki’s solution, the traditional bank achieved:

• 50% Reduction in False Positives: The improved accuracy reduced unnecessary investigations and saved valuable resources.
• Faster Investigations: Automated workflows cut investigation time by 30%, allowing the team to handle cases more efficiently.
• Enhanced Compliance: The bank met regulatory requirements more effectively, reducing the risk of penalties.

This case demonstrates how traditional banks can modernize their AML systems to handle the complexities of financial crime and compliance.

Key Takeaways from AML Case Studies

Analyzing these real-world AML case studies provides valuable insights into the challenges and best practices for effective compliance. Here are some key lessons learned:

1. Importance of Advanced Technology

All the case studies highlight the critical role of AI and machine learning in enhancing AML efforts. Advanced technologies enable financial institutions to accurately monitor transactions, reduce false positives, and adapt quickly to new threats.

2. Dynamic and Scalable Solutions

Scalable and flexible solutions, like Tookitaki's FinCense platform, are essential for organizations of all sizes, from digital banks to traditional financial institutions. These solutions allow institutions to customize their AML strategies according to their unique needs and regulatory environments.

3. Efficient Alert Management

Managing false positives is a common challenge across all case studies. Implementing smart alert management systems not only reduces the number of false alerts but also helps compliance teams focus on genuine risks, improving overall efficiency.

4. Holistic Approach to Compliance

Integrating multiple compliance processes, such as transaction monitoring and risk scoring, into a single platform helps in creating a comprehensive AML framework. This integrated approach ensures better coordination and quicker responses to suspicious activities.

5. Continuous Adaptation and Learning

Financial crime tactics are constantly evolving. To stay ahead, organizations need a solution that can learn and adapt over time. Leveraging community-driven insights, like those from Tookitaki’s AFC Ecosystem, helps in staying updated with the latest threats and typologies.

These takeaways emphasize the need for financial institutions to adopt modern, technology-driven AML solutions that are adaptable, efficient, and comprehensive.

Conclusion: Effective AML Compliance Through Case-Based Learning

AML compliance is a complex and ever-evolving challenge for financial institutions worldwide. As highlighted in the case studies, organizations often struggle with outdated technology, inefficient processes, and a lack of integration. Learning from real-world scenarios is crucial for understanding these challenges and finding effective solutions.

Tookitaki’s case studies demonstrate how advanced technology, community-driven intelligence, and a holistic approach can significantly enhance AML compliance. By leveraging AI and machine learning, Tookitaki’s FinCense platform and AFC Ecosystem provide comprehensive solutions that adapt to new threats, reduce false positives, and streamline compliance processes.

For financial institutions looking to strengthen their AML frameworks, it’s essential to adopt solutions that are not only effective but also adaptable to the ever-changing landscape of financial crime. By learning from past experiences and embracing innovative technology, organizations can ensure robust compliance and safeguard against financial crimes.

Ready to Enhance Your AML Compliance?

Discover how Tookitaki’s FinCense platform and AFC Ecosystem can transform your AML compliance strategy. Contact us today for a demo or consultation and take the first step towards a more secure and efficient compliance framework.

Anti-Financial Crime Compliance with Tookitaki?

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