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Our portals News. Management and boards should be convinced that the information is useful and relevant; regulators will want to know that it is accurate and compliant.

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If all reporting information — whether it is financial or nonfinancial — is not investment-grade, trust will suffer. Independent assurance of information, either mandated or voluntary, can play a critical role. EY research finds that companies that have their nonfinancial information independently verified are more likely to be confident that their corporate reporting is trusted. Global policy debates, new regulatory requirements and more stringent supply chain practices play a part, but the collective voice of the investor continues to be among the clearest.

Many teams are overwhelmed by the volume of data available. They should utilize technology but not at the expense of standards and trust. Organizations and their finance teams have more data than ever before thanks to increases in computer processing power, ever-growing connectivity, and the cloud and its massive storage capacity. However, many finance and reporting teams are simply overwhelmed by the volume and variety of that data.

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Many finance and reporting teams are overwhelmed by the volume and variety of data. The most agile finance and reporting teams are using automation to drive new levels of operational agility:. Finance leaders can use AI to look for underlying patterns in data as well as machine learning to predict scenarios and improve outcomes. Finance leaders were asked to rank the importance of three technologies — RPA, AI and blockchain-based tools. However, finance leaders do not just have to think about how they use AI in their finance functions.

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  • They should also think about how stakeholders, such as investors, are using it to highlight corporate reporting. This is because AI allows investors to analyze corporate financial information in ways that were previously unthinkable. AI is developing rapidly, and it is critical that finance leaders keep up.

    This means making informed decisions now about where the technology can drive most value in finance and reporting. Only then can finance leaders plot out their transformation and lay the groundwork for strong collaboration between finance and IT. But there are ethical issues. In finance and reporting, it is not enough to ask whether systems are doing things right.

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    You should also ask whether systems are doing the right things. This is especially important with a fast-moving technology such as AI, because rules and regulations lag behind technology, and have not yet been proven to assure and address risks adequately. One approach to developing ethical standards for these tools is to ask the stakeholders who will be impacted by the technology to look at it from their perspective.

    And the design of the system should reflect the importance of transparency around how the reporting system has made its decisions. Blockchain records transactions using a distributed ledger, which gives every network participant a secure audit trail of all transactions ever made — in near real-time.

    Some commentators, therefore, expect the technology to become the industry standard for reporting and accounting, replacing existing back-end IT and traditional reporting practices. If blockchain is used to automatically consolidate accounting records automatically, then reporting teams can spend less time on cross-checking and aggregation, and more time on analyzing data that can be trusted. Of course, a number of challenges will need to be overcome.

    For example, key stakeholders — from regulators to boards — would need to agree on and implement the required regulatory environment. Finance leaders are focusing on turning data into reporting insight, but they have to negotiate a difficult balancing act; driving innovation in how they use data without compromising standards and undermining trust. And concerns about data security are one of the most critical barriers to implementing new reporting technologies.

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    However, concerns about digital and data risks should not hold organizations back. To get to true value-driven reporting finance teams should be able to embrace their data with confidence. This will require changes not only to technology and processes, but also to mindset, skills and governance. Finance functions require a different talent profile that may require leaders to overcome cultural barriers and entrenched processes.

    Value-driven reporting does not just demand that finance teams adopt new technology — they also require a different talent profile and skill sets. The finance function will benefit from team members with a range of new capabilities beyond traditional finance and accounting skills, including strategic awareness of new technologies, such as AI, and knowledge in disciplines such as data science and advanced statistics.

    Those who can help the team understand and measure the interdependencies between nonfinancial and financial information will prove valuable. However, driving a change in approach can be very difficult, with an entrenched culture and resistance to change acting as a brake on progress. To overcome resistance and accelerate the changes that should happen in the finance workforce, organizations should focus on two priorities.

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    • Finance is starting to require people with new skills. The next generation should understand not just accounting and their industries, but also AI, blockchain and machine learning — as well as how these technologies work together. Leading finance functions are auditing the existing capabilities of their teams to understand what gaps they face. This should include both hard skills required to exploit new technologies and data as well as soft interpersonal and strategic skills. Many organizations understand that they require new skills and profiles, but they often fail to look for talent in different places, and do not use new tactics for developing their people.

      Too often, they are stuck in traditional practices: they use the same methods that have been in place for years, and were used to recruit and develop themselves. Finance should do more to challenge these entrenched approaches and views of what constitute finance capabilities. The automotive industry, for instance, has responded boldly to the challenge of digital disruption and connected cars.

      This EY research shows that while all respondents believe new areas of technology expertise will be critical to driving digital innovation, younger finance executives place more of a premium on this area. It was found that younger finance executives are also more likely to feel that data scientists and statisticians will be very important when it comes to driving digital innovation. This perhaps reflects the fact that younger generations are very much aware of the impact of new technologies, and are more open to finance recruiting the expertise required to respond.

      By exploiting the rich data available, the finance function can provide insights into the business and support long-term value to stakeholders. Trust can take a lifetime to build and seconds to lose. While rebuilding it depends on many factors, reporting can play a vital role. Reporting teams should be able to exploit the rich, multidimensional data they now have access to. Using digital technology and analytics skills, you may provide the reporting insights that give stakeholders visibility into the business and support long-term value.

      You should compare your approach to reporting against peers and leaders in this field. This can help stimulate your thinking about creating a structured framework for reporting long-term value to key stakeholders. You also should consider how they approach nonfinancial assurance so that external stakeholders and boards trust that information.

      You should also consider how to manage risk and seize opportunities to improve supporting processes and systems. Over the coming years, intelligent systems are likely to play an increasing role in more reporting processes and tasks, transforming the ability of finance teams to drive insight from their data. To realize the potential of intelligent systems, you should act now to identify the reporting issues these technologies may solve and to set out how they could transform your approach. This can give finance both a compelling vision and a practical road map for change.

      This may also help you overcome organizational resistance and engage with key stakeholders such as supervisory boards and audit committees. This means creating the right internal culture for data, with everyone following a clear data strategy underpinned by a code of conduct and data governance framework. And rather than seeing regulatory frameworks for data protection and privacy just as compliance exercises, you should consider reframing them as an opportunity to take a positive approach to data.

      Finance leaders are under pressure to deliver more reporting more quickly in an environment of technological change, increased regulatory change and increased scrutiny. EY can support clients in this ever-changing landscape. Data is one of the principal drivers of your business growth. Companies are increasingly dependent on collecting, analyzing and developing insights from data. Better understanding of this data can underpin your business transformation and growth.

      Organizations have an urgent need to develop reporting transparency in a way that builds trust and helps explain how they are creating long-term value by exploiting the data at their disposal and turning it into a strategic asset. In order to help rebuild trust, organizations should utilize new technology to organize and analyze data and adopt new competencies beyond traditional accounting skills to deliver value-driven reporting.

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      For more information about our organization, please visit ey. This material has been prepared for general informational purposes only and is not intended to be relied upon as accounting, tax, or other professional advice. Please refer to your advisors for specific advice.