Intelligent Automation Challenges for Finance in 2020
Why do companies want Intelligent Automation?
Intelligent Automation is increasingly becoming a staple in every industry, e.g. Banking, finance and insurance. With the presence of Intelligent Automation becoming the norm to lead the way in business, companies must make sure that their implementation of the solution goes as smoothly as possible. Looking into previous trials, Intelligent Automation has shown its benefits by increasing revenue while achieving improved customer satisfaction, all while having the potential to expand at scale.
In knowing this, finance companies are now racing to implement these solutions to reap the benefits. However, these companies must be aware of the potential challenges and how to tackle them before making the step into the Intelligent Automation sphere.
With the obvious benefits of Intelligent Automation, it can be very tempting for finance companies to jump to try and introduce the solution quickly. This is not necessarily a wrong choice but to succeed with Intelligent Automation; businesses have to be aware of the challenges and learn from others failure.
The first mistake many firms have made in the past is to expect the application of the solution to be easy/ instantly solve issues. Specifically, in finance, this is a significant issue as the main priority for many companies is to solve very complex problems such as anti-money laundering detection and portfolio management. Although resolving these challenges is achievable, they can take time to bed in compared to the more medial tasks that have a smaller impact but show improvement quickly. In testing Intelligent Automation on these more complex tasks and not fully committing to them, companies frustration forces them to stop.
The key to a successful implementation of Intelligent Automation is preparation, awareness and patience. If one of these parts is missing, then it is likely that the solution will struggle to reach its full potential or possibly fail to show any positive results.
The challenges to achieving this success can be split into three areas, business, tech and people.
Starting with the business challenges, it is essential to know what process needs automating before introducing the technology and whether that is a realistic target. Without defining a process that needs Intelligent Automations support, the approach can become scattered and lead to confusion and ultimately, failure.
By starting small with a method that can instantly relieve some pressure, further changes can be soon be added with gradual change. Making and committing to a decision even if the benefits initially seem minimal is crucial to Intelligent Automation success. This is because Intelligent Automation requires cooperation to work successfully.
Tech challenges pose another area that businesses must approach correctly to get Intelligent Automation right. Companies have struggled to integrate automation platforms with their original systems. Ensuring the original system in place is compatible with Intelligent Automation must be confirmed before taking the next step.
The main difficulties firms have found ensuring that data management, security and privacy are adhered to correctly. With these areas being at the top of finance teams priority lists, decision-makers are sceptical of potential errors and may delay implementing the technology. The introduction of stricter data protection laws a few years ago had a massive impact on several industries, none more so than the finance sector. Knowing that a single error can cause a fine of millions of pounds, further steps are taken in the decision processes to ensure the solution is capable. This is where it should be advised to pick low-risk areas to improve initially, giving confidence to the decision-makers to scale the solutions up.
Another issue to mention is data management. The amount of data finance companies store is monumental, so ensuring it is arranged and delivered correctly through Intelligent Automation can be difficult. Starting small and building up the integration is key to supporting the solution from a machine learning perspective.
The final main area that can cause challenges for finance teams looking to introduce Intelligent Automation is the people behind the bots. These challenges can be broken down into two points.
- The need for more skilled workers
- The effects on the original workforce
With any Intelligent Automation solution, it is essential to hire staff that already have in-depth knowledge of RPA and AI. They are necessary to ensure the process of implementing the solution goes smoothly. However, it can be challenging to find the right members of staff that can fit the balance between technical expertise and business process. As mentioned in previous points, planning before introducing the solution makes a great deal of difference to the success of the solution. In the hiring process, the same applies. Having a clear idea of who your business is going to hire to support the solution will only help the transition of adding the solution.
The second area concerns the staff that currently work in positions that involve repetitive manual processes. When talking to staff about Intelligent Automation, there may be some initial resistance to the proposal as the idea of implementing bots can be viewed as a solution to remove specific jobs once done by humans. This resistance would not be unusual; however, it can be the last big stumbling block when trying to progress the companies Intelligent Automation goal. This challenge can be made more complicated if the solution is added without consultation with the staff.
Ultimately using Intelligent Automation will provide benefits to the team and business, but to make sure the transition is smooth, it is always best to be transparent from the outset.