Biggest Challenges in Financial Sector and Tech Solutions to Overcome Them
The financial services market has seen radical technology-led changes over the past few years. Many leaders look to their IT departments to improve performance and promote game-changing innovation – while somehow reducing costs and, at the same time, continuing to use legacy systems.
“To succeed in this rapidly changing landscape, IT executives will need to agree with the rest of the management team on the posture they wish to adopt. Will they try to be industry leaders, fast followers, or will they just react? Whichever direction they choose, they will need to devise a clear strategy to move forward.” FS Tech 2020 and Beyond: Embracing disruption
Meantime, fintech startups are disrupting the established markets, leading with user-centric solutions developed from scratch and unencumbered by legacy platforms.
Customers have certain expectations and are now necessitating better services, seamless experiences regardless of channel, and more value for their money. Also, regulators demand more from the industry and have started to adopt new technologies that will transform their ability to gather and analyze data. And the pace of drastic change is not even at the peak.
There is no doubt that technology is affecting financial services in multiple ways. The PWC report suggests ten key influencers that IT executives need to address while strategic planning for 2020 and beyond.
Each of these drivers is likely to change financial services companies and their management teams in far-reaching ways. And while each can have a disproportionately strong effect on a given country, customer set, or industry sector, they all present opportunities for the thinking executive to go ahead.
Knowing a robotics era is coming, for example, you have a choice: to harness the innovation, or to see others benefit from a global shift. The section below sets up challenges around these ten influencers: to know them, get ready for them, and see how to employ them to get a competitive advantage.
Challenge #1: Eliminating Cybersecurity Risks
Financial institutions (FIs) are prime targets for cybercrime. Because of the confidential data they carry, they are more likely to be hit. FIs were attacked 300 times more than other businesses. According to Intsights Q1 2019 report, around 26% of all malware attacks last year were targeted on banks and financial organizations.
Banks are quickly allocating their budget to improve cybersecurity capabilities and protect against threats. A multitude of financial institutions reported sensitive data breaches, malware attacks, and other types of cyberattacks in 2019, which include:
- Capital One Financial Corporation, a bank holding company, revealed a data breach in July, which affected approximately 100 million individuals in the United States and nearly 6 million in Canada.
- First American Financial Corp leaked about 885 million personal and financial records associated with real estate transactions since 2003.
- Desjardins Group had about 2.7 million of its members’ data leaked (home addresses, names, email addresses, and social security numbers).
- Due to the cyberattack on Westpac/PayID, the banking data of 98,000 customers leaked.
Since each attack costs financial companies millions of dollars, they need to keep up with innovative solutions to be one step ahead of the cybercriminals.
Solution: Investing in the Newest Tech-Driven Security Measures
With a problematic stream of high-profile breaches over the past few years, security is one of the major banking industry challenges along with concern for bank and credit union clients. FIs have to invest in the latest technology underpinned by security measures to keep critical customers safe, such as:
Address Verification Service (AVS)
AVS allows checking the billing address submitted by the card user with the cardholder’s billing address on record at the issuing bank to identify malicious transactions and prevent fraud.
End-to-End Encryption (E2EE)
E2EE is a type of secure communication that blocks third-parties from accessing data while it’s transmitted from one end system or device to another. E2EE utilizes cryptographic keys, which are located at each endpoint, to encrypt and decrypt private messages.
Banks and credit unions use E2EE to guard mobile transactions and other online payments so that money is safely transferred from one account to another or from a client to a retailer.
Biometric authentication implies a security process that uses the unique biological characteristics of an individual to verify that person. Biometric authentication compares biometric data capture with stored and verified authentic data in a database. This data could be voice, facial, and iris recognition, as well as fingerprint scans. Banks and credit unions use biometric authentication instead of PINs, as it’s harder to fake and, therefore, more secure.
Location-based authentication (geolocation identification) is a process that proves an individual’s identity and authenticity on appearance by merely detecting its presence at a distinct location. Banks use this kind of authentication along with mobile banking to prevent fraud by either sending out a push notification to a client’s cell phone authorizing a transaction or by triangulating the client’s location to determine whether they’re in the same place in which the transaction is taking place.
Out-of-band authentication (OOBA) means a procedure where authentication requires two different signals from two various networks or channels. By using two separate channels, the authentication system protects against fraudulent users that may only have access to one of these channels. Banks use OOBA to create a temporary security code, which the client receives through the automated voice call, SMS text message, or email. The client then enters that security code to log into the account, thereby proving their identity.
Risk-based authentication (RBA) is a method of applying varying levels of stringency to authentication operations based on the possibility that access to a given system could result in its being compromised. RBA enables banks and credit unions to adapt their security measures to the risk level of each customer transaction.
Challenge #2: Keeping Up with Technology
Business growth is significant for financial companies, but in order to grow, they must invest in renewing their technology. According to a Protiviti report, financial institutions must continue to spend money on technology such as robotics and other automation tools to increase their productivity and cut the costs related to operational, risk management, and compliance.
Firms must also update their technology platforms and data storage so they can enable big data solutions such as AI-supported digital customer support assistants. Financial institutions need also to consider connecting platforms and provide a more efficient, user-friendly experience across the internet, mobile, and physical locations.
Solution: Growing Through Innovations like AI, ML, and Robotics
While blockchain may still be too immature to realize significant returns from their adoption soon, cloud computing, AI, and robotics can provide good advantages for FIs looking to reduce costs, enhance customer satisfaction, and grow revenues.
Use of AI and Cognitive Opportunities
Cognitive analytics (CA) is a new approach to information discovery and decision-making. Inspired by how the human brain processes information, draws conclusions and systemizes instincts and experiences into learning, CA can bridge the gap between the intent of big data and the reality of practical decision-making.
Machine learning systems, artificial intelligence (AI), and natural language processing (NLP) are now no longer experimental ideas but potential business influencers that foster real-time decision-making.
Components of AI and Cognitive Technologies
The field of AI has produced many cognitive technologies. Some of them are getting better at doing specific tasks that only humans could do. We outline some of these cognitive technologies for business and public sector leaders to focus their attention on.
- Natural Language Processing – Ontology-Based information extraction and Speech recognition
- Natural Language Generation
- achine Learning – Neural networks / Deep learning
- Computer Vision – Image recognition
Cognitive computing solutions offer various capabilities that enable the above technologies to do tasks as a human brain will do.
Cognitive Engagement means boosting customer understanding and activation using personalization, influencing desired actions.
With the rise of cognitive computing, people can now get fast and customized services. Cognitive systems reveal the power of unstructured data (industry reports, financial news) using in-depth text /image/ or video understanding. They offer personalized communication between banks and their clients by dealing with each client and focusing on their needs.
Spanish bank Santander announced that it would provide secure transactions using voice recognition through its banking app. At the same time, Scottish Royal Bank has introduced Luvo, an AI-powered customer service assistant, to communicate with staff and potentially serve clients in the future.
In Sweden, Swedbank’s Nina Web assistant held on average 30,000 conversations per month and a first-contact resolution of 78% in its first three months. Nina can handle over 350 different customer questions and answers. Several other banks in the UK and globally have similar systems in place or are trialing them.
Cognitive Automation implies automating repetitive, knowledge, and natural language-rich, human-intensive decision processes.
Automation powered by AI has become possible due to the combination of new types of software and recent inventions in computing. Business benefits include cost savings, better use of highly skilled employees, faster actions and decisions, better outcomes, and more. Intelligent automation using optical character reader (OCR) and machine learning capacities can be helpful in back or middle office work delivering high volume and rules-based work.
For example, NLP technologies develop semantic rules to extract useful information and utilize OCR scan account opening forms, Know Your Customer (KYC) documents such as PAN Card. However, back-office is not the only sector where intelligent automation can be an essential factor in reducing risks and costs.
Provider of voice and text management tools Fonetic partnered with Banco Bilbao Vizcaya Argentaria (BBVA) to roll out the Fonetic linguistic analysis and trading compliance solution. The latter proactively tracks and prevents trading violations at its London and New York headquarters.
Another tech-based company specializing in AI, Narrative Science, automates its investment and earnings reports using software that takes data and converts it into a narrative. Many financial firms such as Credit Suisse, USAA, and even publishing houses like Forbes and Associated Press use Narrative Science’s Quill platform.
Cognitive Insights are critical insights derived from billions of data sources in real-time.
Personalization is a vital talking point for banks. Therefore many of them are experimenting with innovations to match products and services with consumer needs. There are also some companies adopting new apps in personal financial management (PFM), which help customers make more intelligent purchase decisions, handle their finances, and save costs while they are out and about spending money.
UBS used AI when giving personalized advice to the bank’s wealthy clients by modeling 85 million Singaporean individual’s behavioral patterns. Tailored to financial services, the technology enables Sqreem (Sequential Quantum Reduction and Extraction model) to build a profile of a person showing potential match-ups with various types of wealth management products.
Cognitive Sensing & Shaping strategies is about building an in-depth knowledge of the company, market dynamics, and top trends to shape strategies.
Advanced analytics technologies can aid banks in using excess data at their disposal to get granular, real-time insights into every aspect of banking operations. These technologies allow banks to define their clients, based on their values, expectations, and needs, rather than generated demographics. Clients share information, too much of which is out there. Identifying, sorting it, and getting a sense of what a particular news item or expert view means is a tedious task.
Cognitive analytics can add value in almost every banking operation, be it real-time insights on loan, treasury, or investment portfolios. Banks can keep discovering real-time insights on clients’ portfolios and thus develop their portfolio strategies.
Goldman Sachs spent money on Kensho, a cloud-based solution that can instantly find answers to more than 65 million question variations by scanning more than 90,000 actions. These may be drug approvals, economic reports, monetary policy changes, political events, and their impact on nearly every financial asset over the globe.
Automating Processes Through Robotics
Automation capabilities extend from simple rule-based automation to advanced cognitive and AI automation. Therefore, the task of studying and understanding automation can often seem more intimidating than it is.
Robotic Process Automation
Robotic Process Automation or RPAis a technology that simulates the actions of a human doing simple rule-based activities. In other words, RPA is the natural evolution of labor arbitrage, as it literally ”takes the robot out of the human”, offering cost-effective, scalable, and easy to implement solutions.
This is what sets RPA apart from traditional automation methods based on backend automation requiring cumbersome IT transformations, high costs, and complex decision-making, given its susceptibility to security issues.
RPA perfectly suits those repetitive and deterministic processes, that have a minimum level of ambiguity, and almost no exceptions. Most of these processes can be characterized as following, making them very favorable for RPA implementation:
- All processes have predefined rules with minimal or no human intervention.
- The manual labor in these repetitive steps is high.
- The processes are standardized in terms of input, process steps, and output.
- Most processes have input data that is digital rather than physical.
- Transaction volumes are high enough to justify automation.
RPA has proven to be industry agnostic thus far. As long as there is manual and repetitive work being done in a company, there is good potential for automation using RPA.
- Global Investment Banks: RPA has helped customers improve case handling productivity to address the existing case backlog and meet regulatory requirements.
- Insurance & Annuity Insurance Firms: RPA has helped enhance customer experience by decreasing inbound calls and “indexing” turnarounds with digital interactions.
- Financial Services: Complex manual processes pose a quality issue, and RPA has aided in overcoming such errors and dramatically improved quality.
- Leading Professional Services Firm: Erratic and seasonal volume peaks for a specific type of work (e.g., input salary data for workers into Talent Management System) needed hiring and training of temporary personnel. RPA not only helped in effectively handling this seasonal volume work at a lower cost but also improved the transparency and general quality of the process.
- Global Pharmaceutical Company: RPA implementation drastically improved operational efficiency and helped in the overall cut of operational costs.
RPA lets companies automate processes that were tricky to automate using existing tools. Since RPA is easier to implement and has a quicker payback period, it has the potential to help companies get profits quickly. Together, with other rising technologies (e.g., blockchain, IoT), RPA and Cognitive Automation can redraw the competitive landscape of many industries.
However, there is no ‘one-size-fits-all’ solution to RPA. Business executives worldwide have to try out this evolving technology in their financial forms with an ambitious intent to transform their business outcomes and value proposition fundamentally and thus strengthen their competitive advantage in the rapidly changing global economic environment.
Challenge #3: Complying with Regulations
Regulatory compliance has become one of the major fintech challenges as a direct result of the dramatic growth in regulatory fees relative to earnings and credit losses since the 2008 financial crisis.
From Basel’s risk-weighted capital requirements, Dodd-Frank Act, to the Financial Account Standards Board’s Current Expected Credit Loss (CECL) and the Allowance for Loan and Lease Losses (ALLL), there are too many regulations that FIs must comply with. Compliance can significantly reduce the resource burden and often depends on the ability to match data from different sources.
Major Banking Regulations
Basel III – Since2009, Basel III is regulation for banks set by the Basel Committee on Banking Supervision. According to Basel III, risk-weighted capital requirements determine the minimum capital adequacy ratio that banks must comply with.
Dodd-Frank Act – Released during the Obama presidency, the Dodd-Frank Wall Street Reform and Consumer Protection Act set regulations on the financial services business and created programs to stop predatory lending.
CECL – Created by the Financial Accounting Standards Board, the CECL is an accounting standard that requires all companies that issue a credit to predict losses over the rest life of the loan instead of incurred losses.
ALLL – TheALLL is a reserve that financial firms create based on credit risk assessments within their assets.
Faced with drastic consequences for non-compliance, banks have incurred additional cost and risk (without a proportional enhancement to risk mitigation) to keep up with the latest regulatory fluctuations and to implement the tools necessary to meet those requirements.
Overcoming regulatory compliance difficulties requires banks and credit unions to develop a culture of compliance within the organization, as well as the introduction of formal structures and compliance systems.
Solution: Using RegTech to Streamline Processes
RegTech (regulatory technology) is already influencing regulatory compliance. It is an emerging industry that helps to ease the burden of compliance. By using the newest fintech technologies to address regulatory compliance, RegTech startups are setting a connection between regulators and the financial sector.
According to Deloitte’s research, regulatory fines exceeded US$ 345 billion since 2009. The cost of regulatory compliance grows substantially, and organizations coping with this problem are developing rapidly. Deloitte suggests five categories of the RegTech Universe based on analysis of 360 companies, including compliance (41%), risk management (14%), identity management & control (23%), regulatory reporting (14%), and transaction monitoring (8%).
Solutions RegTech companies are offering according to each category
- Compliance. Real-time monitoring and tracking of the current state of compliance and upcoming regulations.
- Identity Management & Control. Facilitate Know Your Customer (KYC) procedures and counterparty due diligence. Screen and detect AML (anti-money laundering) and anti-fraud.
- Risk Management. Identify compliance and regulatory risks, assess risk exposure, and anticipate future threats.
- Transaction Monitoring. Solutions for real-time transaction tracking and auditing. Use the benefits of distributed ledger through blockchain and cryptocurrency.
- Regulatory Reporting. Enable automated data distribution and regulatory reporting using big data analytics, real-time reporting, and cloud.
Technologies Supporting RegTech Solutions
The rise of emerging technologies, such as advanced analytics, RPA, cognitive computing, and cloud, is allowing the creation of differentiated RegTech solutions to help handle some of the compliance, regulatory, and risk management issues.
These RegTech solutions, underpinned by new technologies, offer richer and faster insights, drive performance in compliance procedures via automation, reduce costs, and anticipate foresight into emerging risk issues.
To choose the right solution (and provider) and most impactful areas for transformation, companies need an in-depth knowledge of regulatory requirements, extensive experience with existing enterprise compliance processes, a robust understanding of the RegTech solution, and its practical application.
Challenge #4: Rising Customer Expectations
Modern customers are smarter, tech-savvier, and better informed than ever before. They expect a high-level personalization and service out of their banking experience. Changing customer demographics plays a crucial role in these heightened expectations. Each new generation of banking customers has a deeper understanding of technology and, as a result, a higher expectation of digital experiences.
Millennials have led the charge to digital financial services. Five out of six millennials reported their preference to interact with brands via social media. When surveyed, young people were also found to make up the biggest percentage of mobile banking users, at 47%.
Based on this trend, banks can expect future generations (i.e., Gen Z – through 23 years old), to be even more invested in omnichannel banking and attuned to technology. Baby Boomers and older members of Gen X (40-54 years old people), by comparison, usually value human communication and prefer to visit physical branch locations.
Solution: Establishing Hybrid Banking Model
The above-referenced survey data sets a unique challenge for banks and credit unions: to satisfy both at the same time – older and younger banking customers. The solution is a hybrid banking model that integrates digital experiences into traditional bank branches. Imagine you have a physical office with a self-service station with the cutting-edge smart devices, which customers can use to access their bank’s knowledge base.
If clients require additional help, they can use one of these devices to schedule a meeting with one of the bank’s financial advisors. During this meeting, the advisor will answer the customer’s questions, as well as connect them with a mobile AI assistant that can provide them with further recommendations based on their behavior.
On the one hand, there are countless opportunities when switching to online banking like enhanced user experience, more control over money, easy access from any device, more personalization. On the other hand, main street banks are leading on the market and for a good reason.
That is why the synergy of digital and traditional banking is highly required in the current days. Hybrid banking is bridging a gap between generations of banking customers and might be a step to a new era of online banking.
Top Priorities for Financial Firms to Succeed in 2020 and Beyond
The pace of change is accelerating and doesn’t seem to slow down. Financial businesses are looking to the IT provider to do more to help make sure they have a competitive advantage to succeed in the future. Macroeconomic trends are embracing the world, and technologies are buffeting the industry. So what is the best solution to move forward?
The Financial Services Technology 2020 and Beyond study states, that there are six priorities for success in 2020 and beyond:
To succeed in this fast-paced fintech sector, IT leaders will need to agree with the rest of the management team on the position they want to take. Whether they will try to be industry leaders or fast followers, they will need to design a clear strategy.
Most likely, there will be a need to partner with innovative FinTech startups and change their business practices based on lessons from other industries. They will undoubtedly need to maintain a laser-sharp focus on their customers’ preferences, both stated and unstated. Frankly, each priority is essential.
The good news is that each one is also achievable. The answer is to combine short-term tactical actions with long-term initiatives that tie to both a broader and strategic vision. This is how financial institutions can succeed in 2020 and beyond.
How Innovecs Solutions Can Help
Innovecs keeps pace with emerging technologies in financial software development and quickly adapts to changes in the industry. By outsourcing your project to Innovecs, rest assured, you will get a full-featured fintech software solution that fits all your business needs.
Automating Business Processes
We can help your business facilitate manual procedures related to paperwork (filling out documents, storing data in spreadsheets) through automation, and therefore improve the quality of your financial service.
Forecasting and Preventing Fraud
Innovecs exploits ML algorithms based on vast amounts of data to predict future industry trends, to detect fraudulent activities in the system, block them, and minimize associated risks.
Delivering Transparent and Secure Products
Innovecs has exceptional experience in developing blockchain-backed financial apps, distributed data management, and money transfer solutions. We develop secure, cost-effective, and transparent products.