Getting ahead of the game with your financial digital transformation means understanding the importance of security and privacy. It also means improving your analytics and forecasting capabilities. This can help you make faster trade decisions in capital markets. It can also help you avoid fraud and money laundering risks. It can even improve the accuracy of your financial analysis.
Table of Contents
Insight-driven decisions improve accuracy of financial analysis and forecasts
Using data to power your decision making processes is a no brainer if you are looking to gain a competitive edge. It’s no secret that modern organizations are competing to reduce waste, and improve their financial acumen. As a result, they are turning to technology to help them on their quest.
For example, there are many cloud-based platforms that allow organizations to sift through massive amounts of data and find the best-fit solutions for their needs. Similarly, these companies are using technologies like artificial intelligence (AI) to augment their human staff. Moreover, these tools are designed to make a company’s financial operations more efficient and effective, so that the finance team can focus on what they do best: creating value for the organization. These are only a few of the myriad reasons why companies should invest in the best cloud-based data management platforms.
The latest offerings from SAP and Workday are the perfect companions for this new breed of data-driven companies. These cloud-based data management and analytic solutions enable companies to perform financial forecasting, budgeting, and reporting activities, in a highly automated fashion. These tools also provide analytic and predictive insights that are actionable. Having these tools at hand enables Roche to better understand and forecast its revenue and expenses. This translates into better planning and increased agility, as well as improved decision-making capabilities.
Likewise, these new tools have allowed Roche to streamline its financial forecast process, which formerly took several weeks to accomplish. In fact, this streamlined process has already freed up the finance team’s attention to other, more value-adding activities. The new system will also allow Roche to take a broader view of its operations, allowing the company to better serve its global customer base.
Insight-driven decisions mitigate fraud and money laundering risks
Increasingly sophisticated criminals are challenging the financial services industry’s defenses, demanding that organizations make insight-driven decisions to mitigate fraud and money laundering risks. These attacks come from external and internal attackers. Some of the most common types of financial crime include: bribery, insider trading, tax evasion, and terrorist financing.
The Financial Action Task Force (FATF) is a multi-governmental body whose mission is to combat money laundering and terrorist financing. Over 190 jurisdictions have committed to FATF recommendations. These measures include identity verification procedures, and the use of alternative sources.
Among the key steps to take in fighting financial crime is to develop a comprehensive AML program. This program should be tightly focused, and it should include a variety of data fields to monitor. Ideally, these fields should be clean and consistent. The data fields should also contain enough historical value to help in the detection process.
AML processes can be automated with semantic analysis, robotics, and machine learning. This new technology helps banks analyze data more intelligently. Using AI, a bank can gather more data, reduce the time required to complete tasks, and decrease the number of false positives. AML solutions can also be adapted to address the needs of a specific business, including customer sentiment analyses, and the customization of portfolio solutions based on risk appetite.
As companies move toward digital transformation, they are faced with increasing challenges, including securing customer data and managing the shift to contactless payments. Financial crime solutions are designed to help organizations meet this new challenge. These solutions are built on predictive analytics, which keep up with real-time transactions and manage the move to electronic payments.
With the increasing complexity of financial transactions, it is important to have a thorough understanding of the different stages of money laundering. In addition to documenting these stages, financial institutions should identify which data fields are appropriate for AML analysis. They may also need to work with subject-matter experts to implement this strategy.
The financial services industry has been undergoing a broad-based transformation. A major focus has been on improving risk governance standards, customer experience, and revenue streams. But the corporate sector must also be vigilant about regulatory and reputational risks. These threats are often caused by cyberattacks. These attackers can manipulate data, set up fraudulent bank accounts, and launder funds.
Security and privacy can’t be an afterthought
Regardless of the industry, security and privacy cannot be an afterthought in financial digital transformation. This is especially true for the insurance industry, which has been a long time supporter of the concept. But, despite the positives, it’s clear that the threat to digital transformation is still large.
The cybersecurity industry has faced several challenges in the past two years, including an increase in ransomware attacks and personalized attack methods. As the industry continues to evolve, legislation will need to keep up. Traders will need more powerful systems, and identity and network controls are needed for financial advisors. Yet the data security function is often isolated from the core development team.
With so many technologies influencing financial businesses, it’s clear that cybersecurity isn’t keeping up with the pace of digital transformation. This is reflected in the rising number of high-profile vulnerabilities. Traders and financial advisors are also more mobile than ever, and require more advanced identity and network security. However, some boardrooms are more focused on efficiency and the bottom line. This means that they don’t think about Digital Transformation enough. It’s up to organisations to balance security and flexible working practices.
The banking and financial industries are among the most important sectors to protect from cyber attacks, and they have a unique set of risks. For instance, digital transformation increases the attack surface, making it harder to keep up with strict compliance requirements. This is particularly true when it comes to remote working.
If security and privacy aren’t part of the planning process for a project, it can be a huge risk. In fact, the failure to adequately address these risks could lead to the loss of customer trust. Ultimately, it’s up to organisations to keep their customers’ and employees’ data safe. This is an increasingly complex issue, and it’s essential that companies implement cybersecurity solutions as part of their digital transformation plans. While it’s impossible to eliminate all risks, organizations can improve their chances of avoiding cyber attacks by automating fraud and financial crime processes. This can also improve accuracy, speed, and customer experience.