With a name like Tookitaki, it goes two ways – people make snap judgments and write you off. Or they decide that a company that had the gumption to name themselves after a children’s game in a serious business is confident about its ability to deliver. The inspiration for the name came from ‘Luka Chori’ – Bengali for ‘Hide and Seek’ But change the context and things fall in place like a charm.
Tookitaki started out as an ad platform from an apartment in India’s startup neighborhood – Koramangala in Bangalore. Abhishek Chatterjee, one of the founders said in an introductory video in 2013: We built Tookitaki to help advertisers shift from traditional media modeling and align campaign strategies to changing audience interests. In short, Tookitaki brings in the next generation of ad platforms, listens and reacts to consumer behavior in real-time.
With his background in JP Morgan and Double Click as a software engineer, he felt that India was fertile ground for the next wave of advertising platforms and ad technology. But fate had other plans. By 2017, Tookitaki shifted its HQ to Singapore and radically changed its business model to a field VCs were taking a keen interest in – Regtech
What exactly is Regtech?
Rewind to the financial crash of 2008 and the US Government put in place strict regulatory reporting norms for financial companies. Companies had to invest huge amounts of money in reporting and compliance. The problem was, regulations were changing faster than they could keep up. According to Deloitte, there are 220 regulations to keep track of every day. Financial companies in the US have paid over $345 billion in fines since 2009 for non-compliance. They wanted technology-based solutions to automate compliance.
Banks on their own did not want to invest in technology because compliance will never be a core function – but they wanted companies that could deliver. This was the field that VCs stepped into – the addressable market was huge and this problem was a perfect fit for automation. No human experts could keep track of changes and as the volume of transactions surged every year, the search for solutions ramped up. The market that Tookitaki pivoted to was a far cry from the crowded ad tech market. A niche that had the potential to become a new sector all by itself – because once a function is automated, it never reverts to a manual state. Like trading and ad tech, compliance and regulatory reporting will soon be transformed.
The size of the opportunity
Deloitte listed five areas where there is a substantial shortfall in the preparedness of companies to deal with the situation. In compliance – 41%; in Risk Management – 14%; in Identity Management and control – 23%; in Regulatory reporting – 14% and in Transaction Monitoring -8%. These are huge gaps to be filled and companies that create automated solutions to tackle these problems will dominate the market.
For machine learning to work, the quality of data it is trained on has to be top-notch. Financial system data is structured – but the volume is stupendous. Hundreds of millions of transactions a day. Human sleuths can catch deviations but they are limited by the speed and the depth they can mine, even within a system they know well.
Tookitaki focuses its algorithms on two areas – transaction processing and transaction reconciliation to detect money laundering as opposed to genuine transactions in the bank’s data. All data creates patterns and deviations from the norm have to be flagged off. The accuracy is determined by a low false-positive rate generated by the algorithms to reduce both work pressure and risks because every deviation has to be investigated.
The maze of reconciliations
Banks and financial institutions have to deal with hundreds of different types of reconciliations in the course of a normal working day. These include credit card statements, cash transactions, ATM transactions, front office, back office procedures and so on. Matching all these transactions manually drives up the financial institution’s operating costs.
Money launderers do their best to camouflage the money they pass through the legal financial system, making it appear as if they were transactions between genuine entities. It has grown highly sophisticated and keeps evolving – making it harder for financial institutions to keep track or even discover because when a rule is implemented within systems to flag such transactions, ways are worked around it.
A financial institution’s profitability is impacted by stopping money launderers to the extent possible as well as reporting diligently to regulators. And that is a global trend – regulators are piling on the pressure to automate and reduce manual processes. Giving Tookitaki a leg up to grow its business and placing it in the unique position of having regulators and governments act as sales drivers!
Building brand Tookitaki
In a specialised B2B space within fintech, the solution becomes the brand. It is quite likely that outside of its core business partners, Tookitaki may not even be known – and that’s perfectly fine. The best places to show up are the exhibitions and keynotes where senior bankers and financial institution heads converge. The information to be conveyed is dense and not easily assimilated. The risks of making the wrong decision are irrevocable, so the path to a sale is a long and protracted process. Bankers are even more careful when it comes to spending their money instead of lending it.
One of the overlooked strategies for building credibility early on is to win awards for specific achievements. In 2019, Tookitaki’s AI technology won the Singapore Business Review’s Technology Excellence Award. Winning against established names gives young brands a foot in the door – and that can be an enormous advantage in a tightly integrated world where entry is difficult. The press release on the prize went on to note:
Tookitaki AMLS is a paradigm shift from such legacy systems as it was created with a design philosophy of providing maximum detection coverage and low false alerts whilst being fully scalable and transparent. The proven platform reduces false positive alerts by 40-60% and increases the detection of new suspicious cases by 5%.
Tookitaki scores in another area that is not immediately apparent – on ‘explainability’. That means that the AI provides explanations in clear audit terms for predicting or flagging off a set of suspicious transactions. Which makes it infinitely easier for financial institutions to make the case to regulators and customers.
Another requirement in this ecosystem is that any new product or solution has to ‘play nice’ with the existing modules – no client is going to disrupt their ongoing processes to accommodate a new player – even if the payoffs are substantial. Tookitaki is another piece that fits into an evolving financial jigsaw – by playing ‘hide and seek’
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Author short bio: I head Ideascape, an agency that I started in 2004. I have over 35 years of experience building brands in businesses as diverse as payroll services, software, cycles, HR services, hospitals, hospitality and project management.
We’re a boutique creative agency but we provide the full range of branding services in partnership with several associates in digital marketing, web development, and event management. This blog is a collection of my experiences and my point of view on marketing and advertising
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