Artificial intelligence (AI) is transforming the world of finance, from automating tasks to enhancing customer service. But not all AI solutions are created equal. It’s all too easy to just whack a chatbot onto an existing product without really understanding the wants, needs, and challenges of audit and financial professionals.

At DataSnipper, we do things differently. We embed AI into our products, making them more intelligent, efficient, and user-friendly. We also keep up with the latest developments in the field, such as large language models, deep learning, and rules-based systems.

In this blog post, we will share how DataSnipper is approaching developing AI solutions that are truly impactful for financial professionals, and the principles that guide this.

The AI Landscape in Audit & Finance

AI is not a new phenomenon in audit and finance. For decades, financial institutions have been using various forms of AI, such as expert systems, machine learning, and natural language processing to automate tasks, analyze data, and provide insights.

However, in recent years, the AI landscape in finance has become more diverse and complex, as new players enter the market and new technologies emerge.

For example, in the last few months alone EY launched EYQ, a platform that helps clients explore the impact of emerging technologies. BDO introduced an LLM that can assist its users in applying firm guidance when auditing and KPMG announced a partnership with Microsoft to develop AI solutions for audit, tax and advisory services.

These are just some of the examples of how AI is proliferating in the finance sector, creating new opportunities and challenges for financial professionals.

The Challenges for Users

While AI can offer many benefits for financial professionals, such as saving time, reducing errors, and enhancing performance, it also poses some challenges that need to be addressed.

Some of the main challenges are:

• Auditability: A lot of the work done by financial professionals must be audited and therefore black boxes and models that are unexplainable take more work to explain than the benefits they provide. Financial professionals need AI solutions that are transparent, traceable and accountable, and that can provide evidence and justification for their outputs.
• Accuracy: Hallucinations are unacceptable when models are being used to inform financial decision making. Hallucinations are when models generate outputs that are not based on the input data, but on their own internal logic or biases. Financial professionals need AI solutions that are reliable, accurate and consistent, and that can flag any uncertainties or anomalies in their outputs.
• Security and privacy: Data security and privacy are paramount for financial professionals, who deal with sensitive and confidential information on a daily basis. Financial professionals need AI solutions that are secure, compliant and ethical, and that can protect their data and their clients' data from unauthorized access, misuse or breach.

The AI principles of DataSnipper

At DataSnipper, we are committed to developing AI solutions that are impactful for financial professionals, and that address the challenges mentioned above. We follow four principles that guide our work:

Traceable - Always Lead Back to the Source

Our AI solutions will always lead back to the source. We use the power of the Snip to ensure that our AI outputs can be traced back to the input data and the source documents.

We also provide documentation and support for our users to understand how our AI works and what are the assumptions and limitations behind it.

Actionable - Enable Users to work with the Output

Our AI solutions enable users to work with the output. We use interactive interfaces and embed our solutions directly in your favourite spreadsheet tools to make sure that outputs from our

AI solutions are not just passive information. Rather, we give you actionable data that can be aggregated, summarised, and presented in the optimal format for decision making and value creation.

We also provide training and guidance for our users to leverage the full potential of our AI features and to integrate it with their existing workflows and tools.

Supportive - The User Comes First

We go to our users. Not them to us. We embrace user-centered design, user research, and user testing to ensure that our AI solutions are aligned with the needs, preferences and expectations of our users.

We also continuously work on Discovery with our users to ensure they have a positive and satisfying experience with our AI and their feedback, suggestions and best practices directly contribute to further development of our products.

Specific - Tailored to Specific Documents & Scenarios

Our AI solutions are the best tool for the problem. We use a mix of AI techniques, such as rules-based systems, deep learning models, and large language models, to ensure that our AI solutions are tailored to the specific documents or scenarios that our users encounter.

We also use a modular and scalable architecture to ensure that our AI solutions can be adapted, updated and improved as the problems evolve and as new technologies emerge.

Conclusion

We believe that AI will not take your job, but people using AI will. That is why our goal is to provide you with the best AI solutions that can help you stay ahead of the curve and excel in your profession. DataSnipper is more than a product. It is a partner that supports you, empowers you, and grows with you.

If you are interested in learning more about DataSnipper and how it can benefit you, please visit our product page or contact us for a demo.