It’s conference season, and DigFin has sat in on a slew of fintech demos. Here we highlight five companies using artificial intelligence to build digital assistants or chatbots for use by financial institutions, based on presentations at Finovate (a fintech demo event) and broader industry conferences. They share a common theme of using tech to help people working in finance to add more value – in sales and client service – by cutting out manual work. (See also our stories on how J.P. Morgan is using a Hong Kong chatbot maker, and meet the company behind China’s most successful banking chatbots.)
AlphaBot is designed to help people in the alternative-investment space to efficiently collect data on products, including crypto assets; and to help hedge fund managers sell to investors or improve their client-relation services.
The company behind AlphaBot is U.S.-based AlphaTech Investment Solutions. It argues that alternative fund managers find it hard to source and collate the data required for analysis of their portfolio models and construction. Once that work is accomplished, hedge funds then have only static PDFs as a means of presenting their arguments to their institutional investors.
AlphaBot presents itself as a network providing APIs to allow hedge funds and other alternative managers to pull data on asset classes from vendors such as BarclayHedge and Morningstar, as well as crypto-currency feeds. They can use the AlphaBot platform to visually compare and tweak data sets, benchmark results, generate reports, and present portfolio ideas.
This Hong Kong- and London-based chatbot company uses A.I. to help insurance companies sell online by automating underwriting. It’s designed to let them reach customers directly, rather than through agents or other intermediaries.
It’s chatbot advisor, “Anna”, selects suitable products for potential customers based on a few metrics, such as type of insurance policy, cover amount, gender, date of birth, annual income, and smoking habits.
This takes place via a user-friendly experience that is more akin to a chatroom conversation than a questionnaire. Anna will ask the customer their name, and then go into underwriting-related questions like your occupation and whether you, say, scuba dive or participate in other risky activities…and on through more items around health conditions and the like.
Users then input their government-issued I.D. details, contact information, and agree to the insurer’s T&Cs. Then Inzurer generates a policy and asks the user when it’s O.K. for the insurer’s human agent to get in touch. The entire sales process is designed to take 10 minutes, including for life and health insurance policies.
This India-based company‘s intelligent banking system combines voice and text to allow banks to communicate with customers. During the demo, a Payjo executive called the chatbot and demonstrated its ability to shift between languages, although the bot paused before every response; its voice was also robotic.
The chatbot’s scripts are designed to hook and upsell clients. For example, when asked if a credit card charges an annual fee, it knows to suggest alternatives in case the answer is “yes”.
The chatbot’s programming is embedded in the sign-up forms for products such as a loan or a card. It has been designed to help potential customers navigate a bank’s online paperwork, as a human person would do at a bank’s branch. Customers can ask it to clarify anything confusing about filling in a form. And it switches easily between text and verbal prompts. It can also be programmed to send a push message or phone a customer who drops out of the sales process mid-stream.
Payjo’s execs say it is about to be adopted by a large bank.
This company’s chatbot is designed to offer mass personalization to a bank’s customers, by making conversation sound natural. During the demo, although its response was a little slow, the robot did sound much more like it was a person having a normal conversation.
Israel-based Voca.ai designed its chatbot to help with lead generation, lead qualification, upselling, and scheduling appointments.
The technology involves a deep-learning process of feeding its call script with hundreds of thousands of human collection calls. The machine is a layer of call scripts, with trigger phrases and contexts designed to identify customers most willing to pay.
Users would have to similarly train the machine to handle their specific services. Voca.ai also comes with a visual dashboard so a bank or card issuer can predict how the system will respond, as well as to connect it to their external systems.
This India-based company has developed a personal digital assistant specifically for mobile use by sales reps, and says it now has 75,000 salespeople using it.
The app gives salespeople recommendations, suggested actions, and helps them log data back into a CRM like Salesforce.com. It integrates into a salesperson’s office calendar, suggests venues where people can meet prospective clients, identifies prospects who are in a salesperson’s vicinity, and keeps a file of the salesperson’s calls and meetings, as well as a bio or snapshot of customers and prospects, including tips on what products they might buy.
It also provides them with a dashboard showing their progress, a history of their interactions with each client, and a score of deals or fails. It monitors the length of calls, asks salespeople to rate the quality of each call, and let them add notes. This information feeds back to their managers, in real time.
Digital payments to the fore in Singapore
Google Pay, NETS, SmartStream and MasterCard announce new efforts at Singapore Fintech Festival.
One of the biggest themes at the Singapore Fintech Festival is digital payments. It’s a field full of innovation from fintechs, Big Tech, and lenders. DigFin presents some of the biggest announcements.
ATM for rides
NETS Group runs Singapore’s payment rails. The company has a track record of innovating: it was the first in Asia to adopt an electronic debit network, even while global payment companies like Visa and Mastercard still relied on franking. (Franking is referring to postal stamps to confirm a payment was sent by mail.) Other “firsts” followed.
Today the company is now helping Singaporeans use their bank debit and credit cards to pay for transportation, says Jeffrey Goh, group CEO. It has just introduced NetsClick, the first ATM card tokenized for taxi rides, with the user’s bank account debited for the journey. And it just followed this up with allowing bank customers to use contactless ATM cards to pay for rides on the city’s MRT subway system.
OCBC partners with Google
OCBC Bank has entered a partnership with Google to reintroduce the Google Pay app to Singapore. Starting in January 2020, OCBC customers will be able to make C2C or C2B transfers between mobile phones using Google Pay.
Bank customers won’t need an electronic wallet to make mobile payments, says Ching Wei Hong, the bank’s COO. The bank is using the partnership to boost users of Singapore’s new PayNow digital payments network.
Users of Google Pay can also earn rewards when they use it for transferring money or making payments, which go directly to the user’s OCBC bank account.
Google Pay offers a similar feature in India, where it gained rapid adoption on the back of India’s interbank payments system, United Payments Interface (UPI). PayNow, which went live in Singapore in 2017, is a similar peer-to-peer transfer service. The Association of Banks in Singapore estimates the first half of 2019 saw 28 million PayNow transactions worth S$4.6 billion. With Google Pay now supporting PayNow-based payments, the company expects volumes to grow rapidly.
Adding A.I. to payments
SmartStream Technologies is developing artificial intelligence solutions to improve banks’ digital payments capabilities, says Andreas Burner, chief innovation officer.
The technology company is applying machine learning and neural networks to identifying patterns in the data that banks already possess. Banks hold the lion’s share of customer data, and SmartStream is helping them access it and make sense of it.
Digital payments solutions enable acquirers, card networks, issuers, gateways, ISOs and others to get a holistic view of their payments. “Our innovation lab is working with banks to understand how to apply machine-learning tools to payments innovations,” Burner said. “Volume, velocity and variation in digital payments is changing at an unprecedented rate.”
The company has established a dedicated practice to collaborate with all participants in a client’s digital payments world, creating innovation solutions to bridge the gaps in the areas that matter to end users – and to build models that can handle exceptions workflows that kick in when a payment fails or doesn’t go as planned.
All aboard the express
Mastercard has launched Fintech Express, a program to work with third-party fintechs to support them as they help grow the digital payments world, says Rama Sridhar, executive vice president for regional digital partnerships and new payment flows. Mastercard’s first partner is Rapyd, a fintech that uses APIs to provide customized payment solutions to regional and global e-commerce companies, among other corporations.
The partnership gives Rapyd access to Mastercard’s product, partnerships, licensing and legal teams, and helps Mastercard service Rapyd’s corporate clientele. This gives the fintech fast licensing as a card issuer, integration into the Mastercard network, and advice. Rapyd will be able to quickly issue cards for its corporate clients in Asia Pacific. Mastercard hopes its Fintech Express platform will attract more payment-oriented fintechs.
MAS: make fintech sustainable
Data localization, reconciliation and open APIs leading themes at Singapore Fintech Festival’s first day.
The Monetary Authority of Singapore uses its humungous Singapore Fintech Festival (SFF) to drive the government’s agenda. And because of Singapore’s pole position in the industry, and the scale of its conference extravaganza, the MAS can use the event to shape its message.
And its message this year is sustainability. “We need to make the world greener,” said MAS managing director Ravi Menon. And that means a greener financial system, he said.
Data governance doubts
While Singapore’s government pushed green fintech, bank CEOs expressed concern about data and how it’s being regulated in some countries. Noel Quinn, CEO at HSBC, said local laws requiring customer data to remain within the country put at risk the global services that financial institutions are trying to create to serve financial inclusion goals.
Bill Winters, CEO of Standard Chartered, said storing data in local countries wasn’t a problem, but when the data can’t be transmitted abroad, it undercuts cloud computing and global data analytics.
DBS chief executive Piyush Gupta noted that such barriers obstruct progress in KYC, AML and other security requirements – although he also noted that governments and policymakers in some markets realize their localization laws need to be updated.
Companies used SFF to announce new initiatives. One of the areas that fintech has struggled to reach is reconciliations in payments and securities – a huge goal across the industry because of the intensely manual nature of such work. SmartStream Technologies used the exhibition to promote a new product, SmartStream Air, which uses artificial intelligence to carry out reconciliations in almost real time, by comparing and matching data, highlighting any disputes.
DBS Bank, for example, is using SmartStream products to bolster the digitalization of its institutional and trade-finance business, said Raof Latiff, managing director for the institutional banking group. Streamlining its operational workflows allows DBS to focus on new innovations for its customers.
Open banking options
Another major topic at the event was open banking, and open APIs. The rise of digital banking has given way to a need for open banking, said Francesco Simoneschi, co-founder of London-based fintech TrueLayer, which provides verification tools. Banks will begin to use APIs to communicate with other players in order to be able to verify customer identities, rather than rely on people providing bank statements – particularly in developing markets.
“Digital identity is the holy grail,” said Michael Tang, leader of global financial digital services at Deloitte. But financial institutions engaging in open banking will need to ensure trust, which requires a business model that values the customer, instead of seeking to take advantage of their data.
Banks seeking data insight turning to gini enterprise
The trend of open API is making it easier for fintechs to deliver data-based solutions to banks and lenders.
Banks and other financial institutions possess a wealth of historical data about their customers but are struggling to convert that into ways to generate new revenues. As the trend of “open API” sweeps Asia, some banks view it as a threat to their operating models. But commonly used APIs might also be the key to helping banks unlock the value of their data.
Pioneering fintech companies such as Hong Kong’s gini enterprise have developed solutions to help commercial banks, credit card companies and other lenders turn data into insight – and insight into action.
“Banks struggle to understand the information they have on their customers, and we help them make the right decisions and create the right products that their customers want,” said Ray Wyand, CEO and co-founder at gini.
The company began three years ago as a consumer-facing business, offering individual users of its app a holistic look at their finances, from savings to spending, across financial institutions and merchants.
It has developed the technology behind this to help banks and lenders derive the same insights. While banks may have plenty of historical data about their customers, until now they have been flying blind in terms of seeing a customer’s entire portfolio or behavior.
First gini acquires transaction data and “cleans” it, eliminating errors, and “enriches” it, making it machine-readable. That data is now being turned into analytics and use cases for banks that need to either reduce their operating costs, or generate new revenues.
We help banks make the right products that their customers wantRay Wyand, gini enterprise
One of the earliest benefits gini is delivering is removing costs from chargebacks. In Hong Kong, over 10% of calls to banks’ call centers involve questions about card transactions at venues that people do not recognize. This is because many merchants operate under confusing holding-company names.
This may sound simple, but each investigation costs banks on average around US$100, which adds up to tens of millions of dollars, for every one million customers, over a year. However, gini’s data includes geolocation, enabling it to map venues to corporate names – and even to identify individual stores among chains, which are often impossible for banks to figure out. Such data insights not only save banks money on investigations, but also reduce the number of incoming calls.
“If you give us the raw data, we can clean it, structure it, enrich it, and tag it, so our clients can build a set of structured data,” said gini enterprise COO and co-founder Victor Lang. “That’s the first step for a bank looking to use machine learning and AI to improve customer experience and lower operational costs.”
Helping banks grow revenue
The same kind of structured data can also be used to make money, not just save it. One of the biggest demands among banks is to personalize rewards and offers, delivering the right product to the right customer at the right time.
To date, banks have relied on their proprietary demographic information to come up with new product offers, which tend to be one-size-fits-all pitches. Gini augments this with behavioral data built from many sources, a process far more complex than merely “scraping” information from websites used by a customer.
If you give us the raw data, we can clean it, enrich it, structure it, and tag itVictor Lang, gini enterprise
For banks to be able to leverage more data better, the advent of open API is a game-changer.
Harnessing open APIs
APIs, or applied programming interfaces, have been around for a long time: they are the bits of code that let two software programs talk to each other. APIs power every app. “Open” means these are developed in an open-source environment, making the sharing of data a two-way street. Indeed, more banking regulators are mandating that (with consent) consumer data be shareable among banks, merchants and the customers themselves.
For banks used to serving as guardians of customer information, open API is a scary prospect. In many cases, they do not want to share their data. However, gini allows them to work with third-party data without necessarily having to give away their own.
Because gini works with so many sources to enrich the data, it can deliver insights that no bank or lender could derive on their own. A financial institution can work through gini to access the data from, say, an e-commerce site or a merchant, and develop new products for those customers. And as banks become more comfortable with data exchange, they will begin to embrace the greater value from open API collaborations.
Even better, companies like gini don’t need to see any personal identifying information (PII) in order to deliver this kind of insight to banks. Gini doesn’t know who a given customer is: the company just knows that this app user has a certain profile that can be categorized.
“Acquiring and analyzing this data fits with our mission to make anyone in the world great at managing their finances,” said Lang. Now gini enterprise is partnering with banks and lenders to power them with similar insight.