Article | April 13, 2020
Artificial intelligence (AI) has become integrated into our everyday lives. It powers what we see in our social media newsfeeds, activates facial recognition (to unlock our smartphones), and even suggests music for us to listen to. Machine learning, a subset of AI, is progressively integrating into our everyday and changing how we live and make decisions.
Article | March 12, 2021
2020 has been a challenging year for all industries. As COVID-19 continues to create uncertainty, many FinTech brands are under stress for a number of reasons. However, FinTech brands can use this opportunity to build their reputation and emerge as a substantial entity after the crisis has passed. Many FinTech organizations are putting in their thoughts on big ideas and innovative digital offerings that meet customer demand for a frictionless and seamless banking experience.
This article aims to list down the challenges faced by FinTech brands and effective ways to resolve them:
Challenges Faced by FinTech Brands in Generating Demand
In this unprecedented time, lead generation is on high priority to acquiring new customers. The pressure is to get on board with working remotely, adapting to new challenges, changes, and dealing with customers having urgent & new requirements. FinTech companies have faced unique challenges over the past year. They are using complex technologies to develop better products & services for businesses. Replacing traditional methods to improve financial services need strategic planning, technological advancement, and original content marketing ideas to survive in the digital age.
Read on to find out the challenges faced by FinTech brands in generating demand for their solutions.
Impact of Covid-19
COVID-19 continues to create uncertainty due to the widespread lockdown. Many FinTech brands are under the stress of counting recent losses, cost-effectiveness, and rethinking their offerings to adapt them to changing needs. The banking & finance industries are now shifting from response to recovery. They are now investing in introducing new FinTech apps for the post-pandemic world.
According to a recent survey, almost 82% of the citizens don't want to visit their banks and try digital apps to carry out financial transactions. FinTech brands are grabbing this opportunity to reach out to a new demographics by testing and adding new product range. Today, popular FinTech apps include mobile banking, e-wallets, contactless payments, international money transfer, retail banking, stock trading, FinTech loan app, InsurTech, etc.
Go mobile Go digital.
As a FinTech brand develops innovative solutions to be used during the pandemic, they also need to figure out ways to promote these products and services to reach their target audience. You are getting acquainted with various social media platforms, and understanding your target audience will help you reach wider. Identifying the top social media platform that works best for your product and service through content marketing will boost your customer base, reduce churn, and attract potential customers. Other functional content marketing solutions that you can think of includes web – content syndication, social media, mobile app – advertisements, and brand awareness content.
Inefficiency to maintain a healthy lead pipeline
Several FinTech brands are reassessing their approach, their budget, goals, and their offering. Those quickest to adapt to this change will lead the market and continue to grow. According to a research report, B2B specialists make 48% purchases online, up from 38% before the COVID-19 outbreak; this trend is likely to increase.
FinTech companies need to generate more new leads than ever to maintain a healthy lead pipeline. To do so, they need to be where their audience is.
• Finding the best social media platform for your industry
• Rethinking events – Online & Offline
• Exploring online opportunities – Webinars/Podcasts/Live Streaming/ Live Q&A/Online Sessions/ Live Feeds
• Publish demo videos
One of the most significant issues and struggles with a FinTech brand is to gain the trust of their consumers. Consumers usually select financial service providers as they are trusted by their families for generations. These financial brands should be able to handle issues such as security, confidentiality, and digital fraud. The brand should also comply with the latest financial regulations that need to be communicated. Social media is an ideal platform for brands to connect with their existing and potential customers. To build trust & loyalty between the company and the end-user, brands must focus on helping their customers rather than selling.
Inadequate tech stacks to work remotely
The inability to work remotely gave rise to new entrepreneurs with knowledge of finance who developed innovative solutions to help FinTech brands connect remotely. Another essential aspect that has evolved this industry is remodeling the user interface and customer experience. FinTech brands are largely coming out with innovative solutions that can help with:
- Financial close
- More visibility and transparency to financial transactions
- Centralized data
- Cloud support
Cybersecurity is a common problem across industries. With the advent of advanced technologies rises the need to develop stronger security. Considering the threat posed by cybercriminals and fraudsters, the financial system needs to handle this risk smartly. All the financial information remains sensitive, whether it's your social security number, card number, PINs, or password.
With the growing number of smartphone users, FinTech becomes cheaper and easy to use. The process and services that were once monopolized by the banking sector are now available for all, helping develop innovative solutions, lower operating costs, and improve financial organizations' efficiency.
FinTech brands should target millennials. They are fueling the market among money transfer applications and personal investment applications. Financial brands need to focus on financial management, lending, financing, and insurance applications. According to a report, 33% of millennials believe they won't need a bank at all in 5 years.
Expanding FinTech press/media
The increasing use of financial technology has given rise to a number of media houses covering them. Over the year, dozens of FinTech focused media sites, podcasts, and newsletters have been launched. Several authoritative publications have hired beat writers to pump up stories on trending topics and subject interest.
The FinTech market is growing in numbers, and the industry is heading towards the trillion-dollar industry. To grow as a FinTech brand, you need to ensure that you are better than your competitors. These challenges are temporary and can be overcome through practical approaches and technological advancements. While the challenges in deploying a FinTech firm continues, we have given a clearer perspective on how to overcome them in this blog. Overall, digital transformation for customer satisfaction is what is necessary.
Q1. What risks are associated with FinTech products and/or services?
A1. Cybersecurity, consumer data privacy & security, consumer data rights, online frauds and scams; cross-border transactions, anti-money laundering and countering terrorist financing; and digital identity risk are the key factors in the FinTech market.
Q2. What are the benefits of FinTech?
A2. FinTech has helped us drive positive change in the traditional financial services and foster innovation by creating products and service that benefits customers and small and big enterprises. Some of the benefits of FinTech products and services include convenience, digital resolutions, hassle-free practices, flexibility, high rate of approval, upgrade payment systems, customer services, and revenue, user-centric, transparency, and many more.
Q3. What are the challenges for the financial services industry?
A3. As mentioned in the blog, there are 7 key challenges faced by the FinTech Market they are:
Inefficiency to maintain a healthy lead pipeline
Inadequate tech stacks to work remotely
Need to expand FinTech press/media
"name": "What risks are associated with FinTech products and/or services?",
"text": "Cybersecurity, consumer data privacy & security, consumer data rights, online frauds and scams; cross-border transactions, anti-money laundering and countering terrorist financing; and digital identity risk are the key factors in the FinTech market."
"name": "What are the benefits of FinTech?",
"text": "FinTech has helped us drive positive change in the traditional financial services and foster innovation by creating products and service that benefits customers and small and big enterprises. Some of the benefits of FinTech products and services include convenience, digital resolutions, hassle-free practices, flexibility, high rate of approval, upgrade payment systems, customer services, and revenue, user-centric, transparency, and many more."
"name": "What are the challenges for the financial services industry?",
"text": "As mentioned in the blog, there are 7 key challenges faced by the FinTech Market they are:
Inefficiency to maintain a healthy lead pipeline
Inadequate tech stacks to work remotely
Need to expand FinTech press/media"
Article | June 4, 2021
Digital transformation can mean different things to each financial institution (FI). For some, it’s a push to modernise legacy systems and acquire fresh talent. For others, a journey to adopt an organisational strategy that unites departments and teams. No matter the motive, nearly all FIs want the same result—to drive efficiency, revenue and cost savings. For many forward-thinking FIs, artificial intelligence (AI) is a key part of this process.
At first, implementing AI can feel like an arbitrary effort that requires too many stakeholders, too much technology, and too big a transformation. Yet, as AI in banking matures, it brings the potential for higher-complexity solutions that generate positive ROI across business segments. A recent financial services study showed that 85 percent of respondents had successfully implemented AI within their organisation. [i]An additional 64 percent plan to use AI across a wide variety of use cases including process automation, risk management, and new revenue generation.
These studies prove that AI is not only becoming more mainstream, but is necessary to help FIs achieve their business goals, strengthen customer relationships, and remain competitive. To demystifying AI and reap its benefits, FIs must embrace a multi-functional strategy that sparks innovation and encourages collaboration. The three use cases below show how AI can be implemented to most immediately impact a financial services organisation.
Elevating employees, not replacing them
AI has historically created fears of job loss and obsolescence. However, within financial services, AI is well equipped to automate manual and repetitive tasks - such as rekeying data - rather than autonomously make critical financial decisions on behalf the organisation. Due to the complexity of the decisions, degree of regulation, and importance of qualitative factors these tasks are – and for the foreseeable future will be – better managed by employees.
A key use case of AI for automation is the utilisation of optical character recognition to streamline the process of spreading financials when underwriting commercial loans. Previously, credit analysts would have to invest hours painstakingly transferring borrower financial data into various systems, reducing time for holistic credit analysis and increasing loan underwriting times. However, by employing AI-driven solutions in combination with powerful workflow automation, banks have been able to significantly increase efficiency in lending processes, reducing processing and cycle times by more than 50 percent and seeing a 10 percent increase in front-office capacity to focus on true value-add analysis and customer relationships. [ii]
Additionally, AI has the ability to empower bankers, not only by eliminating manual tasks, but also by being able to equip them with powerful insights around relationship profitability and credit risk. By refining sophisticated, machine-learning based models, banks can more accurately predict and leverage metrics such as probability of default and loss given default within risk-based pricing models to provide competitive lending rates to borrowers, while still maintaining healthy profitability at the relationship and portfolio level.
Reshaping customer engagement
The acceleration of digital banking due to the COVID-19 pandemic and the rise of customer-centric titans have put significant pressure on financial institutions to modernise and reshape their approach to digital banking to appease rising customer expectations.
Customers not only expect a frictionless and seamless onboarding process, but for their bank to act as an ever-present financial advisor, offering personalised insights on spending habits, money management and financial decisions. AI-powered virtual assistants and chatbots offer new levels of accessibility to common questions by utilising natural language processing to find past transactions, access credit scores, and view balances. However, institutions can take a further step of both anticipating customer needs and offering targeted product suggestions based on propensity scoring models. Proactively offering recommendations can be helpful to customers due to the complexity of different financial products and enables banks to simultaneously satisfy customers while unlocking new revenue opportunities.
FIs can leverage AI to operate as a dedicated advisor, offer a differentiated customer experience, and reduce customer churn. However, equally important to the underlying predictive models is having a single, end-to-end platform to drive direct actionability by delivering insights to the right banker at the right time.
Boosting back-end efficiency
In addition to empowering employees to focus on true value-added activities, AI offers enhanced methods to improve operational efficiency and risk management. Analysis of IDC data shows that AI technologies can improve the cost efficiency of financial institutions by over 25 percent across IT operations[iii].
As a part of fraud detection, institutions can leverage AI to oversee thousands of transactions and efficiently flag anomalies that are indicative of fraud. Historically, transaction monitoring has struggled with false positives, through which genuine transactions are incorrectly flagged. However, through machine learning, actual, fraudulent transactions can be compared to false positives, which can then be fed into the model, improving accuracy over time as the system incorporates learned, differentiating factors.
Finally, the COVID-19 pandemic has caused institutions to revaluate how they assess credit risk and problem loan management. Lenders have had to segment their portfolio by geography and industry to differentiate sectors which were more severely affected by the pandemic versus those that were less challenged. Additionally, there is now a greater emphasis on utilising real-time and transactional data in addition to other data sources to truly understand business performance and borrower resilience. As the uncertain pandemic recovery continues, leveraging AI-powered predictive models in combination with delinquency tracking, credit migration modelling, and other tools will continue to be critical to align actual portfolio risk with the risk appetite of the institution.
As AI adoption continues to mature, FIs should avoid sporadically focusing on isolated use cases. Instead, organisations should strive to align strategy, organisational culture, and digital infrastructure under a united AI strategy. This will help enable them to capitalise on revenue growth, operating efficiency and cost savings, from the front to the back office, and across all lines of business.
Article | June 1, 2021
The axing of third-party cookies by Google and the other major browser companies will require a major readjustment by financial services organisations.
The decision, coming fully into force next year, will effectively choke off the data that has enabled personalisation, optimised website interactions and driven much internet advertising. It is no comfort that the browser companies have acted because of fears about infringement of privacy and data protection legislation such as the EU’s GDPR (General Data Protection Regulation) and the CCPA (California Consumer Privacy Act) in California.
The move will affect how UK financial services organisations interact with millions of people. More than three-quarters of Britons now use online banking and 14 million use digital-only banks, expecting a slick, light-touch interaction. So it appears that just as many people go digital, financial services organisations will no longer have access to information they need for personalisation, being unable to track where customers go on the internet after they have visited a bank’s website. All that data about individuals’ habits and preferences will be unavailable.
It seems catastrophic, but in reality, it is not. Financial organisations have a new opportunity to radically improve how they interact with web visitors and customers. AI-powered behavioural analytics offer far superior, real-time capabilities, using the data from the first-party cookies on their own website domains and where available, data from customers’ transaction histories.
The result is a solution that is faster, more accurate and responsive than conventional technology relying on cookie data owned and stored by third-party organisations. Instead of relying on such data for relatively rigid profiling and personalisation, behavioural analytics enables real-time interactions based on a more dynamic picture of how an individual’s requirements are changing.
The technology analyses all the browsing characteristics including time on site, speed of movement and page views, as well as more obvious features such as interest in specific products. Historical data added to the analysis includes what customers did on previous visits and the interval between those visits, establishing patterns where possible.
The flexible advantages of behavioural analytics hubs in financial services
Segmentation allows a bank to identify customers as soon as they arrive on its site, according to whether they are a new or existing customer. Their behaviour then indicates what they want. Knowing what customers are interested in is important. Customers visit financial services websites for a host of reasons – from seeking information, to opening accounts, exploring loans and mortgage offers, making or setting up new payments. They may also want advice about investments and savings, pensions or small business finance. Almost all of these requirements involve quite complex mental processes which financial organisations can influence while consumers are on their sites.
Collecting the data is not difficult – the skill is in making it actionable in an effective way, replicating the ability of a perceptive employee to read a customer’s state of mind. Banks can do this by setting up a behavioural analytics hub to understand what a customer’s behaviour means and how it can be optimised.
Using customised parameters, the hub will, for instance, trigger a screen notification that prompts the web visitor to fill in a form requesting an appointment. In the case of existing customers, the technology can correlate health insurance offers with spending on fitness, and, in general, savings and investment recommendations can be tailored to the client’s concerns or goals as revealed by their navigation of a bank’s website or mobile app.
Banks can set up analytics to see when consumers are behaving in a way that indicates they about to leave the website, allowing them to intervene with a notification that could include an offer. This provides a positive outcome and avoids the blanket use of offers that undermines profitability.
It is a more sophisticated and personalised approach that avoids annoying pop-ups or recommendations that fail to match individual preferences. As part of a single AI-powered segmentation platform, the technology enables banks to personalise marketing content in SMS messages and emails sent to consumers (who consent), which deliver far better results through precise targeting.
Solutions for last-mile interaction in the open banking era
The single platform approach also has another major advantage. It is much easier to implement and far more efficient and streamlined compared with separate solutions for different parts of the customer journey.
The benefits of using AI-powered segmentation solutions should be part of the financial sector’s broader strategy to transform its systems for the open banking era as we approach the end of third-party cookies. For established banks, the reality for some time has been that complexity of systems has undermined their ability to deliver a high-quality last mile. This they can now address without huge disruption or investment.
The alternative is for financial services organisations to become lost on an ocean of data, losing track of customers. Behavioural analytics will bring banks new insights into customers that surpass third-party cookie data, being actionable and accurate and in real time. To provide a streamlined and profitable experience for themselves and their millions of customers, banks must now employ the latest advances in AI-powered behavioural analytics.