Digiterre’s Rajesh Jethwa is named in the top 30 of the 2023 CIO 100
The revenue benefits to financial services of intelligent automation (IA) are staggering – a recent Cap Gemini survey showed growth due to IA in the sector is expected to reach well over £400 billion globally by 2020 alone. And these are additional to the multiple cost saving benefits. Improved customer satisfaction, faster time-to-market and improved cross-selling are some of the headline reasons for revenue growth. The doorway to automation nirvana is well and truly open, but why are so many players struggling to walk through it? And what exactly is intelligent automation?
IA is a spectrum or continuum of capabilities ranging from robotics at one end to artificial intelligence at the other, as shown below:
At its most fundamental level, RPA is associated with “doing” capabilities and following pre-programmed rules, whereas ML and AI is concerned with simulated “learning” and “thinking” capabilities respectively. And all fall under the IA umbrella.
At the heart of both robotics and AI is the same thing that drives today’s businesses: data, but in very different ways. Automated machines ‘collate’ data, whilst AI systems ‘understand’ it. Coupling software systems capable of automatically collecting incredible amounts of data with systems that can intelligently make sense of that information is the nirvana mentioned earlier. But why is this coupling proving so hard to get to for so many?
The majority of FS firms are struggling with a range of business, technology, and people challenges to implementing IA successfully. The heat is growing on them too to get on with this, especially with many expecting BigTech players like Amazon and Alphabet to be their major competitor in only a few years’ time. Only around one in four organisations has the technological maturity to implement cognitive automation technologies comprising machine learning, computer vision and biometrics. Most organisations still have RPA, or – at best – Natural Language Processing (NLP), forming the backbone of their automation initiatives.
There are four recurrent reasons for this slow take-up for many:
To break through these barriers and blockages to IA empowerment and prepare your organisation for IA, there are five key steps to impacting on the business areas which will yield the greatest and most immediate benefits:
There are many hurdles for financial services organisations to realising the benefits of a successful IA programme, but with the know-how and expertise developing so fast, once the biggest challenges of developing the business case and persuading the leadership team to adopt a programme are tackled, the doorway to IA nirvana can be crossed.
By: Rajesh Jethwa
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