How Two Guys Are Enhancing Online Banking For Millions Of Indians With IBM

Not way back, banking was synonymous with lengthy queues, go ebook entries, cashier tokens, bored safety guards and woefully ineffective air-con. Many would argue that it’s nonetheless the case, particularly for the final two factors, however there is no such thing as a doubt that banks are quickly modernizing behind-the-scenes.

An instance of this might be ICICI Bank’s “fully digital banking” adverts — which I endured throughout the latest India vs England cricket series on Disney+ Hotstar. Everything from opening a checking account, making use of for a bank card, submitting KYC paperwork, and assembly financial institution executives — all achieved on-line, via the smartphone app no much less. Sounds too good to be true?


Deekshith Marla of Arya.ai and Afaq Hussain of Intense Technologies Ltd

Deekshith Marla and Afaq Hussain don’t suppose so. In truth, in some ways, they’re the joint architects of the silent technological upheaval taking place inside a few of India’s largest banks.

AI makes all the pieces higher

Deekshith Marla is the Co-Founder & CTO of Arya.ai, Mumbai-based startup that builds AI functions with deep studying algorithms to automate and pace up loads of duties in any course of, whereas Afaq Hussain is the President of Global Strategic Alliances and Enterprise Business at Intense Technologies Ltd, which designs and builds enterprise software program suites and functions for among the largest firms in India and the world. Both of them are ISVs (impartial software program distributors) which are intimately concerned in India’s banking and finance sector, by no means stunned by the incoming digital banking wave.

In truth, in accordance with PwC India’s December 2020 report, 70% of Indian enterprises have carried out AI in a roundabout way or the opposite of their enterprise course of, of which banking and monetary companies is among the highest AI-enabled sectors with 82% course of enhancement.

long bank queues india
Reuters // Inside a financial institution department in India

“Banks are leveraging AI through chatbots and voice assistants at the front end to mimic live employees, and everything from customer identification and authentication to delivering real-time communications,” in accordance with Afaq Hussain, who says customer support is the best contributing section for the proliferation of chatbots and digital assistants, with a 43% banking business market share.

Echoing Afaq’s evaluation, Deekshith Marla says, “AI chatbots span across a wide category and isn’t restricted to just conversational bots. It also includes many process automation where various services are provided via integration with applications like WhatsApp.”

With a rise within the scope of duties that may be automated in a banking atmosphere, Deekshith estimates, “AI chatbots handle almost 70-80% of first-level customer queries and enquiries — everything from creating an account to uploading KYC and getting statements and current balance, a person doesn’t need to visit a branch or even an ATM for these things anymore. Visiting a branch or calling a customer care number is now necessary only for rare scenarios or for expert assistance.”

From good processing of cheques

In most Indian banks, Deekshith mentions how sure duties associated to cheque processing are automated — studying the MICR data or account quantity on the cheque, as an illustration — and that’s the place Arya.ai’s cheque automation product suits in. “We automate all inward and outward cheque processing levels while reducing human intervention, and design workload to only focus on the percentage of cheques where AI may fail so it can be flagged to appropriate bank employees. At a couple of banks where our product is deployed, daily at least 40% of cheques are completely processed without any human intervention,” he says.

The software that Deekshith’s Arya.ai startup has constructed scans a cheque deposited for processing at any financial institution and cross-checks all the pieces from identify, date, account quantity, quantity in numbers, quantity in phrases, signature, and different bank-related data that depositors write down on the cheque manually — so a significance chunk of the answer is OCR (optical character recognition) and picture processing which incorporates matching the signatures on cheque and verifying it with the signatures saved in opposition to the account within the financial institution’s inner database.

Cheque processing application
Representative Image

“Where it would take a bank employee anywhere between 30 seconds to 1 minute to manually verify every single cheque in the past, our application processes 18 cheques per second,” in accordance with Deekshith Marla. That’s no small feat.

“Our signature validation accuracy is at 94% right now,” Deekshith tells me, which is just about the best quantity anybody may attain until now. For the AI mannequin to attain this feat it wants at the very least 15 lakh cheques to coach on, knowledge which is offered by the banks.

“A large private sector bank in India used to get four lakh cheques in a day, which they would take about eight hours to process manually and clear overnight by submitting them to RBI or NPCI’s systems, and we have brought that time down to just two hours,” says Deekshith Marla, additional elaborating how if the system isn’t assured of processing any single cheque routinely — due to illegible handwriting points, for instance — it nonetheless has the choice to flag it to a human banker for guide processing. The cheque processing software that Deekshith helped construct at Arya.ai is now deployed at considered one of “India’s largest public sector banks, helping clear eight lakh cheques per day” in his personal phrases.

To dashing up KYC verifications

With respect to digital KYC, “AI and ML play a key role in areas of face recognition, fingerprint recognition, digital onboarding of a customer, among other things,” mentions Afaq Hussain of Intense Technologies Ltd, additional explaining how a “greenfield Indian telecom operator” was in a position to benefit from this to scale from zero to 100 million customers in under six months — no prizes for guessing which Indian telecom operator is being hinted at right here (after all, it’s Jio).

The digital KYC based mostly buyer onboarding journey Intense Technologies helped create can be utilized in quite a lot of situations, in accordance with Afaq Hussain — from telecom to authorities citizen companies, for banking and insurance coverage functions, amongst others.

“We were able to bring down a customer’s onboarding time from six hours to 15 minutes and now less than one minute,” Afaq mentions, whereas referring to a banking situation. In one other instance, Afaq factors out, “Tax notifications which used to take up to 63 days for the IRS to send to its customers now take less than a day.” All of that is attainable as a result of Intense Technologies have AI-enabled functions that ship out and handle over 200 million notifications in a single day, in accordance with Afaq Hussain.

Biometrics KYC Aadhaar registration
Reuters

Constant studying and adapting to shifts in buyer behaviour is the place AI and ML drives effectivity, Afaq believes. “If a bank primarily communicates with a customer over email and the customer actually responds faster over SMS alerts, then probably reducing emails and sending SMSes first is an inference drawn by the bank based on artificial intelligence and machine learning capabilities,” he says.

“For loan requests, there has been an increasing adoption of AI usage, especially for KYC verification and the borrower’s general profiling. Automation of KYC verification offers a big improvement in customer experience and reduces the need for manual paperwork,” says Deekshith Marla of Arya.ai.

Both Deekshith Marla and Afaq Hussain agree that every one of that is made attainable by pc imaginative and prescient functions and AI-enabled sample recognition instruments that may be educated and regularly improved via deep studying fashions. And their partnership with IBM, by way of operating their functions and AI workloads on IBM PowerPC — notably Power 9 and Power 10 methods.

Every developer wants a tech-savvy pal

Deekshith Marla, co-founder of a younger startup like Arya.ai, in all probability is aware of this truth greater than Afaq Hussain’s time-tested Intense Technologies Ltd which is over 30 years outdated, though each allow banks, insurance coverage firms and different monetary establishments to leverage IBM’s {hardware} and software program infrastructure.

“You need high-performance computing infrastructure to run AI (artificial intelligence) and ML (machine learning) workloads, where each GPU — like a V100 — can cost $10,000 or more,” Deekshith highlights, which is difficult for each startups and their shoppers to justify at a proof-of-concept stage. This is the place firms like IBM helps, Deekshith says, “IBM already has a good connect with all the leading banks in India, and when they saw our AI application they readily loaned us their Power 9 systems, initiated a dialogue for us with their banking customers so we could run the application tests inside the bank’s data centre for them to see process improvements and efficiency gains first-hand.”

Afaq Hussain additionally attests to this tried-and-tested partnership mannequin that IBM (and different know-how giants) operates to speed up innovation throughout completely different enterprise sectors. “The real work for us actually starts after aligning yourself to a customer’s vision, where you move beyond the proof-of-concept stage, and that’s where IBM has truly shined for us,” Afaq mentions, declaring how the expertise of deploying IBM machines in buyer premises, startup premises, to aiding Intense Technologies with testing and making certain issues are shifting ahead has been nothing wanting sensible.

Ravi Jain IBM
Ravi Jain, IBM

In specific, Afaq factors to the IRS answer deployment which impacts $12 billion of annual income and the opposite being the AI-enabled journey of considered one of India’s largest personal sector banks, “In both these instances, the way IBM Systems team collaborated with us was just awesome,” he reiterates.

Ravi Jain, Director, Server Sales, India South Asia, IBM, tells me how discussions round AI and ML in firm boardrooms have shifted from shoppers asking about proof-of-concept workloads and lack of significant startup case research (again in 2017) to companies speeding to drive course of efficiencies and accelerating infrastructure digitization plans all via the 2020 pandemic hit yr — the necessity for which is just going to extend within the coming weeks and months, believes Ravi Jain.

“With the infusion of AI and ML workloads, you aren’t looking at 20% or 30% process improvement — which are tiny — but often 4x, 5x or even 10x (1000%) efficiency gains,” says Ravi Jain, “at which point making a case for these applications becomes extremely easy for the IT teams inside organizations because they can clearly demonstrate to their leadership team about the stakes involved.”

Afaq Hussain echoes Ravi Jain’s views, whereas summing up what the long run holds for digitization not simply within the banking and monetary sector however past, when he says, “As much as Covid-19 pandemic has disrupted our lives negatively, it has forced every company and business to digitize fast and in a smart way without burning a hole through their wallet, including your neighbourhood bank’s branch to provide meaningful customer relationship journeys.” Which is simply nice by me, to be trustworthy — no extra woefully ineffective air-con to sit up for, thanks very a lot. 

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