Define the problem. How to start a risk prediction project?
Defining a clear problem statement is critical to the success of any predictive solution. Here are some best practices for defining a problem statement for a predictive solution:
Identify the business problem: Start by understanding the business problem that you are trying to solve. This could be identifying potential risks associated with the P2P process, such as fraudulent activities, non-compliance with policies and regulations, or other risks.
Determine the scope: Define the scope of the predictive risk assessment project, including the specific P2P processes, data sources, and compliance areas to be assessed.
Define the outcome: Clearly define the outcome that you want to achieve with your predictive risk assessment project. This could include identifying high-risk vendors, transactions, or other entities, as well as potential areas for process improvement.
Determine the data: Identify the data that you will need to solve the problem. This could include vendor profiles, purchase orders, invoices, receipts, payment history, and any other relevant data sources.
Identify the target audience: Determine who will be using the predictive risk assessment results and what they need from it. This could include the procurement and finance teams responsible for the P2P process, as well as the risk management and compliance teams.
Define the metrics: Define the metrics that you will use to measure the success of your predictive risk assessment project. This could include accuracy, precision, recall, and other relevant metrics.
Consider ethical implications: Consider the ethical implications of your predictive risk assessment project, including potential biases and unintended consequences.
By following these steps, you can define a clear and effective problem statement for your predictive risk assessment project around the P2P process and ensure that it aligns with your business goals and compliance objectives.
Lets take a practical shot at it with an example -
Problem Statement: As a Chief Legal Compliance Officer, the organization is facing significant challenges related to compliance with laws and regulations. These challenges include keeping up with the ever-changing regulatory landscape, managing increasing amounts of data, and identifying potential risks in a timely and effective manner. To address these challenges, the organization needs to leverage data analytics to better understand its compliance risks and improve its compliance programs.
Keeping up with the regulatory landscape: The organization operates in a complex and constantly changing regulatory environment. The Chief Legal Compliance Officer must stay up-to-date with changes in laws and regulations, as well as the enforcement priorities of regulators.
Managing increasing amounts of data: The organization generates and collects large amounts of data related to its business operations. The Chief Legal Compliance Officer must be able to effectively manage and analyze this data to identify potential compliance risks.
Identifying potential risks in a timely and effective manner: The organization needs to identify potential compliance risks before they materialize into regulatory violations or legal issues. The Chief Legal Compliance Officer needs to develop a proactive approach to risk management and leverage data analytics to identify potential risks early on.
Data Analytics Solution:
To address these challenges, the organization needs to develop a data analytics solution that can help improve its compliance programs. This solution should include the following:
Data collection and management: The organization should collect and centralize data related to its compliance programs, including policies, procedures, training records, audit findings, and regulatory guidance. This data should be managed in a centralized database to ensure easy access and analysis.
Risk assessment: The organization should leverage data analytics to conduct risk assessments across its business operations. This will help identify potential compliance risks and prioritize risk mitigation efforts.
Continuous monitoring: The organization should implement a continuous monitoring program that leverages data analytics to identify potential compliance risks in real-time. This will help the Chief Legal Compliance Officer stay on top of potential issues and take proactive measures to prevent regulatory violations.
Reporting and analysis: The organization should develop reporting and analysis capabilities that provide the Chief Legal Compliance Officer and other stakeholders with timely and actionable insights into its compliance programs. This will help improve decision-making and ensure compliance with laws and regulations.
By implementing a data analytics solution that addresses the challenges faced by the organization, the Chief Legal Compliance Officer can better understand its compliance risks, proactively identify potential issues, and improve its compliance programs to ensure compliance with laws and regulations.