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How can you use data structures to speed up dispute resolution?

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Dispute resolution is a crucial aspect of any payment system, as it can affect customer satisfaction, trust, and retention. However, resolving disputes can also be time-consuming, costly, and complex, especially when dealing with large volumes of transactions, multiple parties, and different rules and regulations. In this article, you will learn how you can use data structures to speed up dispute resolution and improve your payment system's performance and user experience.

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Vedansh Gupta

Manipal Academy of Higher Education | ACCA Aspirant | LinkedIn Top Voice | Navmarg | Bookkeeper | Investment Banking |…
Paul Erdal

Chief Executive Officer | Founder at Payment System Consultants

1 Data structures basics

Data structures are ways of organizing and storing data in a computer program, such as arrays, lists, stacks, queues, trees, graphs, and hashes. Each data structure has its own advantages and disadvantages, depending on the type, size, and complexity of the data and the operations that need to be performed on it. Choosing the right data structure can make a big difference in how fast and efficiently your program can access, manipulate, and process the data.

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Mohamed Abdallah

B2B Marketing Expert | Fintech Trends Enthusiast | E-Payments Expert | B2B Content Creator and Brand Builder | Brand Communication | Communications Strategist & Consultant.
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appending new dispute-related events to a linked list, you can track the progress of dispute resolution activities, maintain an audit trail of actions taken, and ensure transparency and accountability throughout the process.

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Mohamed Abdallah

B2B Marketing Expert | Fintech Trends Enthusiast | E-Payments Expert | B2B Content Creator and Brand Builder | Brand Communication | Communications Strategist & Consultant.
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representing transaction networks as graphs, you can analyze transaction flows, identify suspicious patterns or anomalies, and trace the origin and destination of disputed funds more effectively.

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2 Data structures for dispute resolution

When it comes to dispute resolution, you need to consider a range of factors, such as the nature and frequency of disputes, the number and roles of parties involved, the sources and formats of data, the rules and procedures for resolving disputes, and the expected outcomes and feedback. Depending on these factors, you may need to use different data structures to store and handle the data related to disputes. For instance, arrays or lists can be used to store basic information about each dispute. Similarly, stacks or queues can be used to manage the order and priority of disputes that need to be resolved. Trees or graphs can represent the relationships and dependencies between disputes and parties. Lastly, hashes or maps can index and search for disputes and parties by using key-value pairs.

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Paul Erdal

Chief Executive Officer | Founder at Payment System Consultants
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Hash Tables: At the heart of efficient dispute resolution lies fast data retrieval. Transactions, with unique identifiers (e.g., invoice number), can be stored in a hash table. This structure allows for quick lookups based on the ID, enabling rapid access to specific transaction details for analysis. Trees and Graphs: Customer and merchant information is crucial for contextualizing disputes. Storing customer details (contact information, transaction history) in a tree structure facilitates efficient navigation and retrieval of relevant data. Similarly, graphs can be used to model complex relationships between entities involved in a dispute (e.g., multiple vendors or subsidiaries)

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3 Data structures benefits

Utilizing data structures to speed up dispute resolution can bring several advantages to your payment system, such as improving performance and scalability, enhancing user experience, simplifying code and logic, and facilitating testing and debugging. This is achieved by reducing the time and space complexity of data operations, providing faster and more accurate dispute resolution, using abstract data types and predefined methods, and utilizing modular and reusable data structures.

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Vedansh Gupta

Manipal Academy of Higher Education | ACCA Aspirant | LinkedIn Top Voice | Navmarg | Bookkeeper | Investment Banking | Stock Trader |
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Using data structures to speed up resolving disputes in your payment system has many benefits. It makes things faster and able to handle more users. This means people using the system will have a better experience. It also makes the code simpler and easier to understand, which helps with testing and fixing problems. By organizing data in smarter ways, the system can quickly find and fix issues, making the whole process smoother.

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4 Data structures challenges

When utilizing data structures to speed up dispute resolution, there are certain challenges to consider for your payment system. Choosing the correct data structure is essential as there is no one-size-fits-all solution, and different data structures may have trade-offs between time and space efficiency, flexibility and simplicity, or security and accessibility. Additionally, the dynamic and heterogeneous nature of data related to disputes must be handled, as it can change over time, vary in size and format, or come from different sources and systems. Quality and integrity of this data should also be ensured as it may be incomplete, inaccurate, inconsistent, or corrupted. Lastly, privacy and confidentiality of data must be protected as it may contain sensitive or personal information.

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5 Data structures examples

Data structures can be used to speed up dispute resolution. For example, in Python, a list of dictionaries can be used to store the basic information about each dispute. Each dictionary contains key-value pairs for the transaction ID, amount, date, status, and parties involved. A queue is useful for managing the order and priority of disputes that need to be resolved. A graph can represent the relationships and dependencies between disputes and parties. Lastly, a hash table can index and search for disputes and parties. These data structures provide a powerful way to manage disputes quickly and efficiently.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you use data structures to speed up dispute resolution?

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1 Data structures basics

2 Data structures for dispute resolution

3 Data structures benefits

4 Data structures challenges

5 Data structures examples

6 Here’s what else to consider

Payment Systems

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How can you use data structures to speed up dispute resolution?

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1 Data structures basics

2 Data structures for dispute resolution

3 Data structures benefits

4 Data structures challenges

5 Data structures examples

6 Here’s what else to consider

Payment Systems

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