BFSI leaders weigh in on the ingredients to accelerate growth with AI


Daniel Lee


By now, most of us would be familiar with the benefits that artificial intelligence (AI) can have for organisations. Cost reduction, revenue growth, and customer satisfaction forms the three largest buckets. What we are experiencing today and, in the years, to come will be the benefits of intelligent process automation in every department of your organisation. When asked what might the future hold after intelligent automation, Sudhanshu Sawlani, Head of Robotics and Intelligent Automation at ING suggested that citizen development will likely be it.


Visualising the organisation of the future

Citizen development has been around for years now. In fact, IT research firm Gartner is generally credited with coining the term “citizen developer” in about 2009. However, just as how AI was first coined by John McCarthy in 1995 and only made huge in recent years, maybe the same might happen with citizen development. What Sudhanshu suggested was the scale of citizen development. A future where we’ll see a deeper integration between humans and automation.

Imagine a future where AI is democratised and every individual is empowered by AI. A bot on every employee’s desktop. Automation not just for organisational processes but democratised and available at the disposal of every individual to build their own automation. While we are still far from building any type of automation one desires, we can already see the start of that trajectory with the development of low-to-no code platforms mostly offering a drag-and-drop development approach. TAIGER’s Omnitive Studio is one such example. TAIGER is democratising their document reading expertise to any business user. With Omnitive Studio, anyone can build their own AI models to read any document in any language or domain.

Meanwhile, as citizen development matures and scales, there are things leaders in financial institutions need to do to prepare for that future and accelerate their journey there.


1. Enhance knowledge set

As technology advances, business leaders are faced with higher expectations. They are expected to understand the capabilities of emerging technology, be quick to identify use cases and plan their strategy to deliver on that transformation. Business leaders need to understand how to involve various stakeholders such as customers and internal tech teams at different stages of their technology adoption. It is therefore helpful that business leaders stay up to date with the latest technology. Recently, the Dubai International Financial Centre (DIFC) organised the DIFC  Innovation Month where they brought together over 200 speakers to share and discuss the various technologies. TAIGER took part and organised four panel discussions to discuss the impact and opportunities of AI in financial institutions. Being an AI company, TAIGER shared how its NLP-driven hybrid AI approach to document extraction could help organisations unlock better automation.

Currently, AI adoption has usually been driven by technology and tech teams instead of the business units.


2. Change mindset

There needs to be a change of mindset. As former Chief Digital Information Officer of Al Fardan Group, Shafique R. Ibrahim mentioned, “technology should be an educating factor but the key driver of digital transformation should be the business units. There is a need for cultural change and to define what AI means to the business overall. Most of such initiatives fail because the technology team is driving them. The feeling of insecurity felt by business units of introducing AI and automation that could impact their role becomes one hurdle in adopting innovation. Jobs are not lost by innovation and digital transformation; rather, they are redefined and people have to upskill themselves.”.

Organisations need to find ways to address employees’ fear that AI will take away their jobs. As Ankur Pandey, Head of the International Banking Group Technology at Mashreq Bank highlighted, “it’s not about reduction in jobs but more about using our human efforts in more appropriate ways. Don’t call it human reduction. Call it human avoidance instead”. Accenture found that companies that communicate clearly that they are deploying AI to help employees rather than to replace them, significantly outperform companies that don’t.

For organisations that have overcome that hurdle, they then need to adopt an agile mindset. As AI is still a nascent technology, it is still on its journey of maturity. AI implementation is a long game and business leaders need to be committed to it despite bumps along the way. “Things don’t always go as planned and your diagnoses may not be spot on. Being agile allows you to correct rapidly in such cases”, said Varun Bhatia, Head of Managed Services at KPMG Lower Gulf. “This holds true for any organisation embarking on a transformation journey – not just financial services entities,” he continued.

Jameel, Head of Digital & Innovation, Corporate & Investment Bank at Mashreq Bank also said that when organisations begin a proof of concept (POC) with a vendor, they “need to have an open mind that these are learning processes, the bots themselves are also learning processes. What organisations need to do is to closely monitor the implementation and ensure there’s a constant feedback loop to see if you are making the right steps.”.


3. Hire a mix of skill sets

No organisation can grow without the right talent. To successfully drive AI projects, the ones taking responsibility need to have an understanding of both the tech and the business and gel those two together. This is because employees with this mix of skill sets would be able to assuage decision makers who might be skeptical about the project. It goes without saying that these talents need to be trusted by the stakeholders to deliver the AI project. Dr. Ferdinando Samaria, independent technology advisor who was formerly both an investment banker and computer scientist, said that “organisations need to have people if necessary who are able to do the implementation”.

Sri Lakshmi, Head of Analytics and AI at First Abu Dhabi Bank added that “when you pick people who have that technical background and they know how to do it, it becomes easier to convince management because they’ll be able to answer all the questions asked during the business case discussions or ROI discussions.”

That being said, employers should not just focus on hiring talent with such skill sets. Instead, as Rajeev Tummala, Director, Digital and Data, Markets & Securities Services at HSBC pointed out, “the number one question should be how open and curious they are to learn”.



Building an organisation empowered by AI isn’t just about technology. It requires an open and changed mindset which often serves as the hurdle towards AI enablement, coupled with the right talent. Once those things are squared out, we can talk about technology. While AI technology matures, leaders will need to calibrate their processes and identify quick wins to gain confidence quickly.

TAIGER’s NLP-driven hybrid AI approach has been recognised by industry leaders like Gartner and IDC. Their document reading AI solution, Omnitive Extract, has been integrated into the activity of multiple global financial institutions such as AIA Group, Standard Chartered Bank, Otkritie Bank and Banco Santander. Arrange a product demo today.


*Quotes in this article were taken from our #UnlockBetter Banking with AI Conference held during the DIFC Innovation Month. The conference was organised by TAIGER for industry experts to discuss how they’ve been leveraging AI to unlock “better” for their organisation. This means better in any form or structure, be it better customer experience, better efficiency, better ROI, and so on.


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