Trust, in-person interactions, reasonably good response levels, absence of alternative options – were some of the reasons that brought people to banks before the era of digital and banking domain monopsony. The strategy worked well and it helped create predictable growth and profitability – until the level playing field tilted.
It is no longer just banks that are able to leverage massive data volumes and technologies to provide better financial solutions. Besides from their peers, banks are now faced with intense competition from new quarters – mainly technology giants and fintech firms – who have been gorging away large portions of what was once their bastion.
Fintech start-ups and big tech firms from the FAANG group, who have forayed into the financial services turf have convinced vast numbers of potential customers to engage with them and existing customers to switch loyalties.
Consumers expect their bank to understand their needs and deliver personalized solutions similar to how they receive from FAANG. A recent study reveals most people who are considering changing banks are open to start banking with a fintech or a big tech firm!
A big factor in the success of the new players is personalization – a keystone of their business models.
Another recent study reveals that 63% of customers say that they will not switch loyalties if their FI provides great financial advice, hands-on help with problem resolution, and guidance on how to grow their money. 78% of customers say they will definitely use their bank if it provides additional services. But how do you do that when you don’t know enough about a customer’s goals or priorities? Only 6% of banks say they have the capability to provide highly personalized outreach.
Another critical factor that has customers switching to financial service providers that they have not used before, is the availability of new, exciting features.
The style and format of interactions have changed drastically and customers expect a lot more from their banks. They feel assured when the bank knows who they are, the history of their relationship with the bank, that the bank values their business, and that you can help them resolve any issue or concern they may have.
The current environment is extremely transactional. Instead of knowing their bank tellers by name, customers are more keen for superior real-time experiences (whether digital or in-person) and great deals (low / no charge maintenance fees, best rewards system for credit cards etc.).
In an intensely dynamic environment, it is vital to understand newer ways to take consumers to the pinnacle of satisfaction. Even though the presence of digital channels has made it easier for customers to communicate with their banks, there is growing frustration due to the absence of listening or personalization by FIs. Hyperconnected customers want their banks to speed up digital transformation and offer more security, advice, and digital and environmentally responsible products and services.
A ‘Segment of 1’ Approach
Decades ago, businesses learnt that they could sharpen their focus and tailor products and services for specific customer segments. A segment today can be trimmed right down to an individual.
A segment of 1 approach is the coming together of 2 independent elements – information retrieval and service delivery – to become a force multiplier. On the one hand is brilliant insights about customer preferences and purchase behaviors; and on the other – a meticulous service delivery that leverages the insights for crafting a unique service package for individual customers.
The advantage is simple yet powerful. Consumers are increasingly expecting to be treated as individuals and want customized products and services delivered at that precise moment of need. Add to this, the reassurance and trust of a relationship with a brand that understands and responds quickly to their specific needs.
When crafted well and deployed effectively, innovative personalization strategies, driven by a ‘segment of 1’ approach, can achieve substantial gains.
What Have Banks Been Doing?
Most banks are already customizing content based on demographic segmentation. They combine multiple demographic points to define customer segments more narrowly. The narrower the segmentation, the more targeted and effective the outreach.
Data such as web activity, email clicks and campaign engagement, helps target customers better. Campaigns developed using additional information about behaviors and choices are more impactful than ‘fits-all’ campaigns. Several banks have been able to drive growth using this approach.
Information about attitudes, interests, values, and lifestyles requires analysis of insights from diverse external sources – web / social media data, surveys, third-party data providers – making it a bit more complex. A few banks have been using psychographic data to segment customers for sharper targeting.
What Could Be Better
While segmentation helps targeted (and to a certain extent, personalized) marketing, personalization is about creating insights-driven real-time experiences. To compete and grow today, banks must have personalization as a strong new pillar in the overall growth strategy.
Customers expect their bank to understand their goals and preferences, and proactively deliver the right offers and services to help them achieve better financial well-being and are willing to share insights with their bank. This is in stark contrast to the quantity of insights most banks are willing to ask, collect, and utilize for the benefit of the consumer.
Data insights and communication technologies have become ubiquitous, affordable, and far more accessible. Banks regardless of size, can harness them to deliver the level of customization that today’s customer expects.
Personalization is much more than showing the customer’s name on the bank’s web or mobile page. To be genuinely impactful, banks must personalize the entire customer journey to engage with the brand. Banks must use customer insights to map customer journeys and identify opportunities for personalization.
The starting point lies in the goldmine of insights already residing across delivery channels, but in silos. No other industry has the kind of width and depth of insights available as much as the banking industry. In fact, only a bank (as opposed to any other business) literally has the complete ‘soul’ of the customer and is best positioned to monetize it.
Personalization is fast becoming a point of consumer differentiation between financial institutions, fintech firms, big tech firms and non-financial players. To create deeper personalized experiences, banks can do more from the insights available, for every single interaction with each of their customers.
When implemented well, personalization can take segmentation, targeting, monetization and customer experiences to the next level:
A strong personalization strategy requires far deeper understanding of everything about the customer, the experiences being delivered currently, the best channels necessary for personalized interactions. This means intense focus on insights about each customer and their individual universes. It helps to have customer information accessible in a single location, for collaborative development of personalization strategies.
Uses multiple information sources to create a 3D view of a single consumer. Banks must connect data from campaigns and other parts of the organization to create a unified view. For example, this is useful in the case of customers who were either referred, or are part of a remarketing goal. Banks need to discover the trail and craft their next touchpoint– whether they’re online or offline. The more the strategies are based on specific personas and defined outcomes (with unique approaches for each channel), the better / higher the impact.
Delivering personalized experiences requires multiple technology solutions working together, e.g., a bank’s contact center and CRM solution working in tandem for a richer, personalized chat interaction.
In 2022, about 97% of consumers used the internet to find information about local businesses. Customers also often include the city name or even a zip code in their searches. There are also potential customers looking for a new bank when they move to a new city. Also, only 35% of banks and credit unions use location data in their campaigns. Not leveraging location-based targeting means missing out on potential opportunities.
Popular search engines allow businesses to add location extensions and call extensions to text ads. This enables businesses to display their co-ordinates, phone number, and a map marker that gives directions. When this extension is enabled, the most appropriate branch locations are dynamically selected by the ad platform based on the customer’s location or search data. This option ensures a seamless experience for consumers and allows them to find branches closest to them. It also keeps business information up-to-date on major ad platforms, review sites, and mapping platforms.
Banks with multi-locational presence can create local (PPC) pay-per-click ads. They can use radius targeting to define specific areas around their branches and then drive customers in those areas to unique landing pages, to boost both relevance and personalization. Popular ad platforms offer the ability to target customers based on their physical location or even their search intent. Metrics can be determined by keywords in customers’ search terms or based on the implied location from previous searches.
Geofencing and Beacons
Digital banking is expected to exceed 3.6 billion users by 2024 and contactless mobile payments will exceed 1 billion users in 2024 (Juniper Research). Banks that have realized the potential of mobile banking are actively trying to connect with the young population that mostly uses mobiles for banking. Many banks are now using geofencing and beacons to deliver campaigns on mobile platforms. So that when a customer enters a particular geographical area, display ads, content, or push notifications are sent to the consumer’s device. Geofencing content is delivered within a fixed radius of the location, based on the GPS data from the customer’s phone, while campaigns that use beacons are activated when a customer nears a Bluetooth device that has detected that the customer is in the vicinity. The only prerequisite is that they work only when the customer’s GPS or Bluetooth settings are turned on.
Innovations across data sciences, predictive analytics, AI and machine learning have all enabled banks to quickly transform information to insights to personalization. AI and machine learning help automatically create efficient self-learning models in real-time, which can be used to deliver contextual ‘in the moment’ experiences with each interaction. But, despite advances in technology, most personalization expectations remain unfulfilled.
Tech giants, fintech firms, telcos, e-tailers, social media, media & entertainment leaders have all set a lofty bar for personalization. Quite naturally, consumers have raised the bar on their expectations from their banks. With customers willing to share insights with their banks to receive more personalized services, it has never been easier than now for banks to create personalized experiences.
‘The’ Competitive Differentiator
Customers look up to banks as vital institutions that play a key role in their financial well-being. Personalized engagements not only differentiate a bank from other banks but also from fintechs and big tech firms. Technology advances has made it easier for banks to take advantage of the new reality. Banks can reap the benefits of personalization strategies faster than they previously did. But they will work best when deployed as an integrated ‘segment of 1’ strategy.
Eventually, it will also be possible to access a single source of insight that will enable seamless integration between back-office processes and real-time customer experiences. From a business growth point of view, the implications are dramatic. ‘Segment of 1’ personalization will activate a radically new way to engage and satisfy existing and potential customers. As a result, competitive advantage will tilt back to the original ‘owners’ of the banking space.
Financial Brand: Digital Banking Readiness Is Top Priority in 2023
Financial Brand: Economy Alters Retail Banking Outlook for 2023 and Beyond
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COVID continues to be in the news and it seems it will be a while before it completely disappears. Meanwhile fraudsters have been taking advantage of the socio-economic conditions triggered by the pandemic. Mule fraudsters in particular have been making hay while the virus shines.
In an operation conducted between mid-September and end-November 2022, the European Money Mule Action tracked down 8755 money mules, 222 money mule recruiters and arrested 2469 individuals world-wide. Involving 25 countries, the op identified 4089 fraudulent transactions and prevented USD $18.7 mn from being laundered by money mules.
Uncertainty caused by COVID and other macro-economic factors, rapid growth of faster payments and extensive digitalization have all contributed to increasing vulnerabilities to scams with more newer channels for fraudsters to exploit.
In the first half of 2022 the UK experienced a spike in online user generated posts encouraging people to become money mules. With over USD $739.5 mn lost to fraud and scams during the period, fraudsters have been exploiting the situation using a variety of tactics, including using money mules to launder funds. (UK Finance)
What is a Typical Money Mule MO?
Mules (people recruited to deposit illicit money into their bank accounts but masked as regular financial activity) are usually unaware that they are handling illegal funds. The term is a derivation of ‘drug mule’ – someone who transports narcotic substances across borders.
Recruiters convince mules that the activity is legitimate work for legitimate business and there’s also a reward for their ‘services’.
A person receives a communication apparently from a trusted source (i.e., their bank, a new acquaintance, the government, a health organization or their child’s educational institution) requesting personally identifiable information (PII); the communication has a link in which the customer is asked to provide their PII.
When they click the link, they’re taken to fraudulent online resources where they end up divulging their PII.
Mule recruiters enlist their mules online via dating sites, email, popular social media platforms, get-rich-quick advertisements, etc. grooming and convincing their victims to open bank accounts under the pretext of ‘helping’ send or receive funds.
Fraudsters (often those who have gained illegal access to business or consumer bank accounts) tend to recruit money mules via phishing emails, text messages, chat messages or social media messages.
Besides Good Samaritan and romance baits, money mule scammers also use work-from-home schemes to entice victims to open new bank accounts that can then be used to move laundered funds.
Fraudsters have been exploiting these vulnerabilities and increasingly leveraging faster payment options to launder money.
Banking on COVID to Target Unsuspecting Banking Customers
Besides the known types of money mules (Unwitting, Willing, Complicit), the pandemic has created a new type of mule – the ‘unwitting-willing’. This new mule variant is eager to help others overcome their financial distress during the crisis, unaware of the risks involved.
Types of Money Mules
Victims of money mule scams can be individuals or businesses including financial institutions. Some of the fictitious scenarios that fraudsters create to gain trust during the pandemic:
- Claiming that they are citizens quarantined overseas, requesting money to help them out.
- Claiming that they are citizens or service staff members working abroad, wanting to send or receive money on their behalf to help a family member battling COVID.
- Claiming to be a member of a medical organization and wanting to send or receive money on their behalf to help those in need.
- Claiming to be affiliated to a charitable organization and wanting to send or receive money on their behalf to help those in need.
Detecting Mule Scams in Banks
Traditional anti-mule fraud management such as monitoring, reactive remediation and preventive controls are not enough during the new normal.
- Monitoring helps identify suspected mule accounts – a key factor in any anti-money laundering system – but it doesn’t deter mule activity.
- Reactive remediation is when a bank shuts down accounts identified as mule accounts. While this is essential, it is only a basic deterrent.
- Preventive controls block known fraudsters from opening or operating accounts, but its effect on money mules is moderate, and it doesn’t impact COVID-motivated unwitting mules or regular unwitting mules.
However, there are certain measures that banks can implement to counter the threat.
Being Completely In-The-Know About Customer Activity
A stringent due diligence process involves identifying account owners and legal beneficiaries before the start of a business relationship. This helps reduce the risk of exposure to money mules vastly. If identification processes are lenient, then subsequent monitoring of transactions may not be able to identify individual suspicious activity effectively.
Vital therefore to utilize every chance to update customer information to consistently retain high monitoring standards. Documentation must be reviewed regularly and updated automatically when there are changes in address or jobs or personal status. Identification of suspect transactions based on customer information, helps trigger prompt enquiry. So, a strong KYC / KYCB record maintenance foundation and practice helps.
While the primary responsibility for identifying suspicious transactions lies with the bank staff processing or checking items, banks should, as an additional safeguard, have in place intelligent real-time, cross-channel technology for suspect behaviour that can be inspected and investigated instantly.
More Closer Monitoring of Suspect Transactions
Account monitoring on an ongoing basis is critical to ensure that bank accounts are reviewed for unusual and suspicious activity. The bank should be aware of high-risk transactions in these accounts, e.g., activity that has no business or apparently lawful purpose, funds transfers to and from higher-risk jurisdictions, currency-intensive transactions and frequent changes in ownership or control of a non-public business entity.
If a customer who claims to be working with an online firm or a money transfer agent receives multiple cash deposits into his / her account, and those funds get wired out shortly thereafter, the bank must verify the purpose of the transactions as well as the actual business of the majority of the beneficiaries.
The bank’s fraud risk team must also ensure that the automated monitoring systems record not just the amount and date of a transaction, but also the identity or geographical location of the persons sending / receiving the wire transfers. Not doing this could lead to a situation where the bank is unable to identify and investigate potentially suspicious transactions based on critical risk factors, such as jurisdiction and the potential involvement of PEPs (politically exposed persons).
Observing the Country of Origin
Banks may be able to detect informal value transfers involving unwitting participants by paying close attention to the country of origin of the money in question.
These funds are likely to originate from the domicile country of individuals who have been indicted by the US DoJ for romance scams and / or from countries with low Corruption Perceptions Index (Transparency International) scores.
A few years back, the DoJ had indicted 80 individuals for executing a massive business email scam and money laundering scheme valued at approximately $3 bn. In this case, the nationalities of the indicted persons should have raised red flags and prompted the bank’s fraud risk officers to question the customers involved about the purpose of the transactions and the sources of funds.
Since the customer is unlikely to be aware that he or she is laundering money, they should be able to provide valuable information to their bank. E.g., the customer may inform the bank that the funds are coming from a high-risk country and that he or she was asked to provide the account number so that individuals in that country can transfer funds to the account domiciled in the US.
The money mule might also tell the bank that the funds are for investing in a profitable business. The bank must inquire further into the nature of the business, including any relevant addresses. After investigation, if a bank suspects that the funds are proceeds of criminal activity, the bank must file an STR (Suspicious Transaction Report).
Checking Where the Money Is Headed
Fraud risk / compliance officers can identify money mules by scrutinizing where the money is being sent. Illicit funds are quite likely to be transferred to countries with low scores in the Financial Action Task Force’s (FATF’s) Mutual Evaluation Reports. When a bank discovers that funds are moving to geographies having weak AML systems and controls, red flags should be instantly raised and the customer must be asked about the source of the funds and the purpose of the transactions.
Monitoring High Net Worth Customers
Criminal networks convince high value bank customers with accounts in US or UK banks to create shell companies and trusts as ‘legitimate’ activity. The illicit funds may have already been deposited into the account of the high value mule by another victim who is part of the larger operation. This modus operandi masks the beneficial owner of the account with a shell firm or another legal entity. Shell companies or PICs (Private Investment Corporations) typically operate from countries that are renowned secrecy havens.
When such dynamics are at play, it becomes important for the bank to (a) establish the legitimacy of transactions and (b) be able to follow the trail to determine the identity of the UBO (Ultimate Beneficial Owner).
Just like any other pre-meditated financial crime, money mule fraudsters plan and coordinate their moves very carefully. For detecting suspicious patterns, banks must aim to gain a holistic, enterprise-wide, contextual picture, instead of siloed, channel-centric views.
Creating detailed and holistic data viewpoints and strategies help create an effective money mule strategy. Also, AI and ML-based analytics enables monitoring transactions on an exponentially greater scale with far lower false positives.
Subscribing to research insights that profile potential mule fraud victims by demographics and psychographics also helps. This enables ‘intelligently’ discovering insights and elusive trends that would have been otherwise difficult to spot.
Money mules used to be seen as small-time felons, transferring small amounts. Organized, sophisticated money mule schemes of the day have become a professional money laundering mechanism.
“Money mules are an essential part of organized crime and international fraud schemes, be it a romance con, business email scam, or a work-from-home ploy.” (FATF)
Whether as complicit players or as victims, money mules are now also laundering funds for organized COVID-related crime.
Every year, banks shut down tens of thousands of accounts for suspected fraudulent practices. A substantial chunk of these accounts is suspected to be mule accounts and conventional anti-mule fraud systems have had little impact to stop the problem. With the pandemic providing more opportunities for fraud, banks must now consider boosting their real-time, enterprise-wide monitoring and investigation capabilities to counter this growing threat.
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How Can Banks Take The Next Leap To Improve Financial Crimes Compliance?
Survival and success for banks, especially in the new normal, demand they operate with intelligence, agility and speed to keep pace with evolving customer preferences and technologies. Meanwhile, there’s a remarkable spike in customer interactions and financial transactions (online and mobile payments, customer onboarding and account opening) going digital.
While digital provides an opportunity for innovative services, they also pose new challenges, including stress on back office operations and increased regulatory scrutiny. Automated interactions generate more data to analyze, demand higher volumes of sample testing, and make the compliance burden heavier. Imperative therefore for back office functions to keep pace to deliver a frictionless customer experience.
From a regulatory point of view, prevention requirements are stringent. With the exponential increase in regulatory demands over time, banks today have a wide spectrum of compliance priorities to deal with.
At most banks, legacy compliance processes built to combat financial crimes have grown so complex that they have become unwieldy and almost unmanageable. Multiple iterations, multiple handovers and several manually controlled processes prevent banks from achieving compliance efficiency. Excessive complexity has also led to higher operational risks and enormous regulatory penalties.
Why the conundrum?
1. Processes. There’s a lack of an end-to-end vision of compliance with respect to financial crimes regulation. Most processes continue to have high levels of manual efforts for screening, alerts processing and other activities. For example, staff at many banks copy and attach computer screenshots to protocols. Each manual step is not quite efficient and error-prone. A related problem is the fragmented, siloed nature of most compliance processes, with frequent manual interventions and delays. Also, communication between the onboarding teams, commercial due diligence analysts and transaction monitoring teams is sporadic.
Commercial due diligence at most banks contains other flaws, namely that the set of questions often are not aligned with the regulatory objectives, or enable a seamless and coherent customer experience, or linked to a system that provides a better understanding of the client. Example: an address on Arab Street, Singapore could trigger an alarm in the first instance, but subsequently the bank’s process should learn that this is not a threat.
2. Data. Low-quality and unstructured data resides within most banks without being fully integrated. This leads to challenges with client reference data and documentation sharing, as well as data extraction or aggregation from voluminous and flawed databases. While some third-party products have been useful, certain popular databases lack essential customer data. Example: a large volume of accounts with customers’ date of birth or ultimate beneficial owner missing.
3. Model. When data quality suffers, so does the quality of the model. Hard-coded or static transaction monitoring algorithms makes it difficult to adjust for policy changes or client behaviours. This increases the volume of investigations and results in unusually high false positive rates, often exceeding 90%.
4. People. If banks staff transaction monitoring processes with inexperienced employees, especially when offshoring, the quantum of investigation efforts will only increase. Lacking expertise, they will either tend to highlight risk reduction over efficiency, or vice versa. They may not gauge the nuances and intricacies involved and may overlook the risks. They may also tend to solve process issues instead of understanding the root causes of problems. And when there’s no probability-tuned risk assessment, using inexperienced staff results in high escalation rates.
Several banks are yet to solve these challenges. Oversized teams, slow onboarding processes, high false positives (even high false negatives in some cases) have all been impacting existing models. Measures to improve financial crime compliance processes have been reactive and tactical at best. Example: hiring hordes of people, pairing them with external contractors and applying multiple technology solutions further raising complexities.
However, a few progressive banks have been taking action in response to these challenges. After initially cautiously approaching technology-based solutions, regulatory compliance functions in banks have begun adopting technology to drive regulatory compliance.
Leveraging technology for regulatory requirements is not new, but the immediacy has become more evident given the current circumstances. Levels of regulation are increasing for banks and to address this, they must adopt smarter regtech solutions to automate reporting and information management to address regulatory requirements.
RegTech enables managing the cost of regulatory compliance, as it grows in tandem with the bank’s overall data strategy.
How Banks Can Shine in Financial Crimes Compliance?
Executing compliance flawlessly is a must-do for any bank, besides also to avoid unnecessary fines and penalties. Banks with below-par regulatory compliance risk management operations have suffered reputational damage, with mixed rates of recovery.
Banks are also stressed with higher costs, M&As and more competitive environments. They are challenged to deliver better returns to their shareholders and therefore require exceptionally superior productivity and efficiency across all critical functions, including regulatory compliance. Regtech can help change the way banks perform compliance.
A resilient financial crimes compliance strategy will require some type of partnership with specialist regtech firms that have invested in and developed expertise that most banks would find expensive or time-consuming to develop themselves.
Regtechs range from KYC specialists, enterprise financial crime management specialists and AML specialists, to customer onboarding and workflow process firms, to major technology firms. There are also utilities firms, that function as intermediaries or data providers to other companies. Many banks outsource certain activities to regtechs, while some banks have bought out regtechs to acquire a specific competency.
There are also banks that partner with other banks to buy an equity stake or build a new regtech firm. After a bank has redesigned its end-to-end financial crimes compliance process, transitioning to a successful regtech partnership requires focus on certain fronts.
1. Mindset. Banks will have to shun the traditional mindset of building systems themselves, and instead explore how to work with regtech firms that are smaller, but more proficient in their area of expertise.
2. Operations. Most regtechs are proficient in using agile methodologies. To collaborate effectively with them, banks will have to become nimbler as well – with fewer handoffs, fewer workarounds and clear metrics for each milestone in the process.
3. IT. Banks will need to adapt their core system interfaces to work seamlessly with multiple plug-and-play applications. As testing cycles accelerate, the risk of fraud could rise; IT teams should focus on system stability and security.
4. Project management. Given that regtechs use agile methods, banks’ IT and operations teams will have to adopt a similar mindset and greater level of flexibility. When a regtech proposes an innovative solution or approach, banks must avoid taking an inordinately long time for internal approvals.
5. Legal and regulatory compliance. Securing the confidence of regulators may be essential for certain partnership strategies in some geographies. Regulators require to be convinced that a bank can outsource certain activities without hampering reliability and quality. So regtechs must prove that their business and operating models are sound, and that customers’ data will be kept confidential.
Even as regulators step up their scrutiny of bank compliance, fraud and money-laundering schemes are getting more and more sophisticated. Banks therefore have no choice but to elevate their crime-detection and crime-fighting capabilities. Defence mechanisms will increasingly include more powerful analytical models, AI and the aid of financial crime regtech specialists. Banks that eventually achieve financial crimes compliance excellence will be those that adopt newer, more efficient approaches, with an optimum balance of people and technology, for a seamless, streamlined compliance function end-to-end.
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Though the term deepfake came about in 2017, the ability to modify and manipulate videos dates back to the 1997 Video Rewrite program. It allowed modifying video footage of a person speaking to depict that person mouthing the words from a completely different audio track. The technique of blending images, videos and altering voice has been used in cinema for even longer, but it was expensive and time-consuming.
A deepfake algorithm can convincingly impersonate a real person’s appearance, actions and voice. With the growth of social media and digital technologies, the technique has now become something of an art form with usage growing rapidly. Scams using deepfake technology and AI pose a new challenge for businesses, as conventional security tools designed to keep impostors out of corporate systems are not designed to spot fake voices or manipulated videos.
Anti-fraud technology companies are in the process of developing defenses to detect deepfakes, while organizations have begun to take deepfakes very seriously. Google has built a database of 3,000 deepfakes to help researchers and cybersecurity professionals develop tools to combat the fake videos. Facebook and Microsoft are working with leading US universities to build a database of fake videos for research.
Two years ago, the New York Times, the BBC, CBC Radio Canada and Microsoft launched Project Origin to create technology that proves a message actually came from the source it purports to be from. In turn, Project Origin is now a part of the Coalition for Content Provenance and Authenticity, along with Adobe, Intel, Sony and Twitter. Some of the early versions of this software that trace the provenance of information online already exist, the only question is who will use it? (Forbes).
The risk has now become so real, that the US government has been debating the growing threat posed by deepfakes and other AI-generated false information and what it could mean for the country’s national security. In June 2022, the US government tabled a bill to be enacted by the Senate and House of Representatives to combat the spread of disinformation via deepfake video alteration technology (Congress.gov).
The Lethal New Kid on the Block
Deepfake is being used today to create astonishingly convincing digitally manipulated voices, photos and videos, even fake identities.
Deepfake photos are used to create non-existent persons (aka sock puppets), who are active online and in traditional media. A deepfake photo appears to have been generated, along with manipulated but genuine looking metadata, for a non-existent person.
Deepfake apps that enable users to substitute their faces onto those of characters in films and TV shows are already popular on social media platforms.
New deepfake software allows adding, editing, or deleting words from the transcript of a video, and the changes are reflected seamlessly in the video.
Audio deepfakes have already been used in social engineering scams, tricking people into believing they are speaking with a trusted person. An energy firm’s CEO was scammed over the phone when he was instructed to transfer €220,000 into a Hungarian bank account by a fraudster who used audio deepfake technology to mimic the voice of the firm’s parent company’s chief executive.
The volume of deepfakes grew at an exponential rate – from around 14,000 in 2019 to 145,000 in 2021 (TechCrunch). Recently, in one of the most significant deepfake phishing attacks, a bank manager in the United Arab Emirates fell victim to fraudsters, who used AI voice cloning to trick the bank manager into transferring $35 million. (Forbes). Fraudsters are also breaking into video conversations. A recent survey reveals that more than 30% of companies experienced attacks on their videoconferencing systems in 2021.
Deepfake Frauds in Banks: A Few Scenarios
New Account Fraud
Aka application fraud, this type of fraud occurs when fake or stolen identities are used specifically to open bank accounts. A fraudster can create a deepfake of an applicant and use it to open an account, bypassing most of the usual checks. The criminal could then use that account to launder money or run up large amounts of debt. Once they become proficient in this, they can create fake identities at scale to attack financial services globally.
With ghost fraud, criminals use personal data from a deceased person for access to online services, tap into savings accounts and gain credit scores, as well as apply for cars, loans or benefits. Deepfake technology lends credibility to such applications, as the bank officials checking an application see a convincing moving, speaking figure on screen and believe that this is a live human being.
Synthetic Identity Fraud
Amongst the most sophisticated deepfake tactic, synthetic identity fraud is extremely difficult to detect. Rather than stealing an identity, criminals combine fake, real and stolen information to ‘create’ someone who doesn’t exist.
These synthetic identities are then used to apply for credit/debit cards or complete other transactions to help build a credit score for the new, non-existent ‘customer’.
Costing businesses billions each year (Pymnts.com), synthetic identity fraud is the fastest-growing type of financial crime, and deepfake technology adds another layer of validity to these types of attacks.
Fraudulent Claims by Deceased Persons
Using deepfakes, fraudsters can also make insurance or other claims on behalf of deceased individuals. Claims can successfully continue to be made on pensions, life insurance and benefits for many years after a person dies and could be done either by a family member or professional fraudster. Here, deepfakes are used to convince the bank that a customer is still alive.
A Tempting Target for a Deepfake Heist
Where there’s money, there’s crime. Trust fraudsters to leverage new technology in their commitment to gain access to accounts, or to set up accounts or steal money. It is just a matter of time before deepfake becomes another new normal for digital rogues to defraud banks.
Most banks demand a government-issued ID and selfie to determine a person’s digital identity when creating a new account online. An impostor can use deepfake technology to easily create a photo to meet the requirement.
Deepfake technology that mimics human voice is already being used to target call centers. We will soon start seeing signs of deepfake technology being used to bypass face recognition controls, including those using state-of-the-art liveliness tests. Banks will have to develop invisible behind-the-scenes controls that can compensate for the vulnerabilities in current authentication processes and protocols.
Even as banks widen the span of their digitisation efforts to cater to increasing online action, it is vital to put equal (if not more) emphasis on stronger measures to protect assets and reputation from newer, emerging threats.
Critical therefore to recognize this emerging threat and proactively implement smarter and enterprise-wide defense mechanisms.
How Can Banks Combat Deepfake Fraud?
Many banks are already using automated deepfake detection software. While these auto-detection technologies work well today to detect amateur deepfakes, it will not suffice going forward. Very soon, deepfakes will have ultra-realism, and existing technologies will not be able to detect them.
As with any security measure, employee training and vigilance is paramount. Banks must invest time and effort in making staff aware of deepfakes with examples (getting an unexpected call from a senior bank executive asking them to perform an urgent, unexpected, non-standard task. Banks can have internal security questions to help employees confirm a caller’s identity if required.
There are also advanced identity verification solutions with embedded ‘liveness’ detection to detect advanced spoofing attacks, including deepfakes, and check if a remote user is physically present. But deepfakes can bypass these methods and imposters can still game the system unless the ID verification technology has certified liveness detection validated by a competent authority.
As of now, in most cases the attempts have had flaws with enough tell-tale signs about manipulations. There are also tools that help tell fact from fiction. Social and traditional media can use these tools to identify deepfakes, delete or label them, so that users from other industry sectors who rely on the information do not end up becoming unsuspecting victims. Another solution is for imaging technologies is to add ‘digital noise’ to image, voice and video files, making it harder for a fraudster to use them to produce deepfakes.
Biometrics provides financial services institutions with a highly secure and highly usable means of verifying and authenticating online users.
Biometric face verification enables an online user to verify their face against the image in a trusted document (such as a passport or driver’s licence). This is ideal for the first interaction with a new customer, for example at onboarding.
Online face authentication then enables a returning customer to authenticate themselves against the original verification every time they want to log in to their account.
Financial Institutions must also:
Invest in newer technology. Reverse image search technologies have enabled tracing original versions of images. However, research is scarce about reverse video searches, and it does not exist in a way that is freely available to all. Banks must collaborate with niche fintech solution vendors to make it possible to develop this technology and publicly release it.
Enrol social media firms. The massive volume of information that social media companies have, could potentially provide solutions. Regulators, banking industry leaders and policymakers can encourage social media companies to disseminate their data to social scientists (while preserving social media user privacy), to enable discovering new solutions to fight deepfakes.
Push for legal reforms. Banks and fintechs can spearhead the need for a stronger framework that makes deepfake technology application vendors accountable for enabling deepfake crime.
Altering voices, videos and photos have become an effortless affair and it has already become a challenge to determine a person’s identity with 100% accuracy. The latest addition to the list of appearance-modifying technologies – deepfake, is also the most formidable one because of its astonishing capabilities.
From having to replace customer funds to incurring penalties to losing trust and reputation, deepfake-led data breaches or account takeovers, can have a devastating impact for a bank.
And as is historically evident with any form of crime, especially financial crime, it usually stays a step ahead, so yesterday’s solutions will simply not be enough to solve today’s newer challenges.
Image courtesy: Sandeep Singh on Unsplash
The pandemic continues to have a significant socio-economic impact with cases, fatalities and intermittent related / variant outbreaks occurring.
Since early 2020, the banking industry worldwide has been bearing the impact. A substantial section of the sector’s workforce has been furloughed, with existing workers forced to telecommute. With branch visits continuing to shrink, usage of digital channels is now at an all-time high. Call volumes at contact centers have spiked with more anxious customers seeking support, and on a wider variety of issues.
The situation has put certain critical aspects of the banking ecosystem in the spotlight, especially that of digital customer experience – a vital factor during challenging times. Imperative therefore to explore how customers’ digital experiences can be made frictionless during an exceptionally difficult phase.
Understanding Digital Friction
Quite a lot of things have changed in response to the ongoing situation. So merely having/managing multiple digital channels is not enough. Banks are already overwhelmed by the number of delivery channels they need to manage. To provide a stellar digital experience, banks require to reduce some of the digital friction points that conventional approaches have created.
From mobile banking to internet banking to ATMs to contact centers to branches – customers use multiple channels to transact. Banks need to have better self-service support options to make transactions faster and more efficient, with heightened security levels and without compromising convenience.
Having a predictable and seamless digital experience across channels is key. Banks must examine the roadblocks in the user’s path to provide a superlative experience for delivering a consistent experience and access to information across all channels.
For instance, a net banking customer shouldn’t have to call the contact center for an answer to a simple ubiquitous question. Be it mobile or online banking, users should get instant answers to queries on that very channel itself. A customer using an ATM shouldn’t have to call the contact center or go to internet banking for queries. A mobile banking customer shouldn’t be made to visit a branch if formalities can be performed via mobile banking itself. In a digital era, and more importantly because of the current situation, a branch can no longer be a primary channel.
Friction escalates when inconvenient instances are compounded over time. Besides impacting customer experience, digital friction also has a domino effect – it adversely affects call volumes, productivity / efficiency levels and conversion rates. Friction is especially high in digital banking sales, with prospective customers encountering friction when trying to open a savings account (Bain & Company).
Can More Be Done To Lessen Friction?
The banking industry has never before faced such intense competition both from within and outside the industry. Even as banking becomes more unbundled, Fintech start-ups are increasing their slice of the banking pie. On the other hand, global technology giants have already moved into payment services replacing legacy organizations that had previously dominated the domain. Not so long ago, large financial institutions were competing on price and physical delivery networks. Today, digital players are competing on the same turf with CX and UX as their trump cards.
In response, banks have been heavily investing in digital transformation. We now have a variety of channels to access services anywhere / anytime. However, despite the positive trend, that vital aspect which these channels were designed to deliver, i.e., customer experience – seems to have taken a back seat.
Banks that meet changing customer expectations with personalized experiences that are fun, engaging and omnichannel can increase acquisition, engagement and loyalty and keep pace with agile Fintech competitors (CapGemini World Retail Banking Report, 2022).
However, a few banking leaders have been able to see digital transformation from a customer experience perspective and quite literally have a finger on the customer’s pulse. Going beyond basic hygiene factors, they have made it easier, faster for customers to engage, are able to anticipate customer needs and even ‘think’ for the customer.
Doing Away with Digital Friction
Digital transformation, but with minimal customer friction as the core tenet, has become a need of the hour. A few ways how banks can deliver frictionless experiences:
A challenge faced by most banks is ownership of various channels. In most cases, IT owns mobile banking, retail ops own online banking and marketing owns the website. As a result, departments work in isolation and are not in 100% sync to provide a consistent and superior digital experience to customers. Seamless interdepartmental collaboration therefore is one of the vital factors to removing digital friction.
The Need for Speed
Make customers effortlessly navigate your digital universe – provide multiple ways for them to easily access information and perform transactions faster across all channels. Use of clear, consistent and intuitive titles – be it website, mobile, or online banking – makes it easier for customers to navigate interfaces. Adding a search functionality to enable users to find answers to their queries on the very channel they are on. Reconfigure AI-powered chatbots to answer queries in real-time instead of near real-time.
Intuitively Foreseeing The Next Move
If a digital interface knows what the customer wants or is about to do, based on behavioural analytics, it can then accelerate tasks and conveniently. The same can be achieved while increasing technology adoption by delivering a contextual ‘segment of 1’ guidance. This also helps lower contact center inquires and increase conversion rates. Financial institutions do a great job of level 1 – i.e., answer a customer’s primary question.
Step 2 involves specific next actions such as scheduling an appointment, applying online, or watching a tutorial. As step 2 anticipates the true intent behind the questions, it is critical to streamline / optimise it to reduce digital friction. For new customers, banks must implement an effective onboarding process that helps effortlessly navigate existing and new features. They must continually provide contextual support to users in research, consideration, and finalizing stage. Contextual and intuitive FAQs that anticipate common questions are effective.
Ensuring Consistent Experiences Enterprise-wide
A bank may have intuitive digital interfaces with a wealth of information available to customers. But, if the experiences are inconsistent across channels, then it contributes to increasing friction. By leveraging additional content, links, and chatbots from other digital banking platforms, banks can deliver the same access to information across all channels. Insights on customer behaviour from a particular channel can be re/cross-purposed for other channels.
A portmanteau of physical and digital, phygital banking combines a variety of banking types including branch banking, mobile banking, internet banking and personalised banking. Leveraging human workforce as well as digital technology to serve customers, phygital banking blends trust with experience – both critical parameters for customers. At a time, when open banking regulations are being debated to make banks become more compliant, transparent, and data secure, phygital banking can work as a trust multiplier cum friction mitigator.
Taking The Bank To The Customer
Banking as a Service (BaaS) need not be only for rural or unbanked populace. The same concept can be applied in an urban context as well. From answering simple queries like ‘what is my savings account balance?’ or ‘transfer funds to my relative’ to helping customers in remote locations locate the nearest ATM to withdraw money during emergencies, AI-powered voice-assisted applications can help customers consume banking services with a higher experience quotient. Smart wallets monitor customer behaviour and spending trends, and then alerts / guides them on how to save more, while making smarter spending decisions.
Harnessing Machine Learning
Robust ML models can predict what customers want, before they know they want it. ML tools capable of analyzing large data sets across categories such as buying patterns, demographics, transaction volumes and service requests can help banks create targeted credit, loan or savings offers that are low-risk for banks but high-value for customers. Also, credit and loan applications historically took weeks to process.
With ML, many banks have been able to reduce timelines to days. But expectations too have increased simultaneously, with more customers demanding faster responses to sales or service queries. ML-driven application assessment and approval helps here. With access to financial data sets, ML tools can evaluate multiple credit factors and reach an unbiased decision, and do it much faster than with human involvement. Implementing ML enterprise-wide helps banks analyze / solve problems at scale. Improved ML algorithms can help banks significantly improve customer experience.
Leveraging Existing Anti-fraud Systems
Advances in real-time, cross-channel anti-fraud technology can also help provide better customer experiences even while preventing potential losses to fraud. A real-time, cross-channel anti-fraud system is already designed to synthesize contextual intelligence from across all of the bank’s delivery channels and deliver the essence of the insight in real-time within the very short transaction window for necessary intervention (i.e., allow, hold or block). However, instances of fraud are few and far in between.
The bulk of the transaction data therefore becomes a veritable goldmine of monetizable insights that can be used for instant real-time cross sell or upsell – at the precise moment when the customer is in her / his most receptive frame of mind. While the bank benefits from the advantage for generating additional revenues, customers are pleasantly surprised with the highly contextual ‘segment of 1’ interaction.
Reducing digital friction invariably tops the objectives in most banking executives research today and for a good reason. From layers of data input screens to avoidable delays in service issue resolutions, customers are bound to experience some friction or the other at some point when engaging via mobile or online. Customers simply do not have patience for sub-optimal digital experiences – many abandon transactions on at least one occasion due to friction.
Besides trust, security and data privacy, customers rightfully expect fast and frictionless digital experiences. With smooth, highly secure and intuitive experiences right from the very first interaction, banks must make frictionless experience the primary growth driver, especially during tough times. To convert satisfaction to loyalty, banks that deliver great digital experiences will be the ones that will emerge winners.
Image courtesy: Freepik
In Chinese philosophy, yin and yang (also yin-yang or yin yang, ‘dark-bright’) explains how seemingly opposite forces may actually be complementary, interconnected, and interdependent in the natural world.
This intriguing idea actually applies perfectly in the context of banking, if we were to see the yin as saving money (from losses), and the yang as making money (from sales).
Banks can monetize their anti-fraud solution for generating revenues
The fundamental idea is that the very same investment in real-time decisioning for monitoring, detecting and preventing fraud can also be monetized for earning additional revenues.
Imagine an intelligent system that studies customers’ behavioral patterns to detect fraud, is also creating precise personas for the bank’s marketing teams to target campaigns to. The same real-time, context-aware logic/approach used to combat cross-channel fraud can also help enable intelligent, hyper-precise targeted and contextual customer engagements.
At the heart of the idea lies the fact that banks have the ‘soul’ of the customer.
Banking is the only industry where the entire life of the customer flows through it. A bank knows how much its customers earn, where they live, where they travel to, how much they spend, who’s part of the family, whether they own their home, even how much fuel they put in their vehicle every month.
Banks have the customers’ ‘soul’, yet they don’t fully monetize the resident wisdom
No other industry (not even telco or retail or OTT platforms) has this extraordinary privilege of having a 360-degree view of a customer’s life. Therefore, only banks have the advantage and ability to actually convert this ‘resident wisdom’ to their benefit.
A true real-time, enterprise-wide, cross-channel fraud management solution ensures that every banking transaction is available in-memory and in real-time.
But since only a relatively small percentage of transactions are fraudulent and since the data is available in the system memory, the bank can run positive scenarios in real-time, after having assigned fraud risk to certain transactions, during the negative-scenario test-run.
The solution can therefore use the same data captured per transaction and analyze the spending and behavior patterns to throw up potential cross-sell and up-sell scenarios in absolute real-time. Precise data analytics on behavior patterns helps create intelligent and efficiently targeted customer interactions and campaigns to grow topline.
So, while the anti-fraud solution helps the bank’s larger enterprise fraud management initiative with:
- a unified case management system for fraud/AML investigation with a 360-degree view of behavior across products and channels
- extreme real-time, context-aware, fraud detection and prevention
- monitoring financial and non-financial transactions of customers, accounts, users, and employees across branch and channel transactions in real-time to detect suspect transactions and respond with the right decision in real-time and generate alerts for investigation.
. . . it can also be used for:
- motivating customers to use POS/E-com channels for digital transactions for generating extreme real-time, ‘in the moment of truth’ cross-sell and up-sell alerts.
- identifying customers who usually travel internationally and offering them custom products in real-time.
- monitoring salary accounts to identify increase in salary credits or a drop in usage of the accounts
So altogether the bank benefits from:
- a smart, intelligent, extreme real-time solution that manages fraud detection/prevention as well as enables customer revenue maximization.
- a non-invasive, bolt-on solution that integrates seamlessly with source systems and reduces TCO.
- lowered cost of compliance of fraud and AML regulatory requirements.
- a single, unified platform that helps protects the bottom-line as well as grows topline.
How does it work?
When the transaction hits the system, it forks, the fraud and AML engine is running the negative scenarios, while the same computing space is also being used to run positive scenarios for cross-sell and upsell.
Such behavior patterns are automatically picked up for a campaign targeted towards these customers.
Additionally, the system can be used to deliver merchant offers in real-time. For example, if based on a card transaction, the system learns that a customer is shopping at a specific location, it can send him/her an offer, (e.g. 20% off) from another merchant a nearby location.
Insights from the system are picked up by a specialist campaign management system that further enriches the information with its own data to come up with the right offer.
It works near real time by running batches every few minutes. If a customer is entitled to an offer (the bank’s alliances / partnerships sources the offers), then he / she receives a text message, a mobile banking in-app notification, or an email.
A leading innovative bank that tried this approach, not only prevented more than $ 9 million in potential fraud, but also delivered over 1 million notifications across various channels such as Internet Banking, email, SMS, and mobile app push notifications. The bank observed much higher click rates (4 – 5%) and conversion rates (3.5%) for these targeted notifications, than regular messages.
Leading innovator bank used same fraud risk management system to perform real-time cross-sell / upsell
Encouraged by the success, the bank is now contemplating using the same system to aid frontline digital customer engagement, such as performing KYC and enabling customers to open accounts in real-time.
Siloed, channel centric anti-fraud solutions cannot see fraud prevention and revenue generation as 2 sides of the same coin, because they do just what they are built for – monitor/detect/prevent fraud for that particular channel.
Innovative fraud management platforms on the other hand have the ability to leverage the same context-aware, real-time decisioning to enable real-time customer cross-sell and upsell.
They can handle exceptionally large data volumes across multiple channels and source systems in real-time, and process transactional as well as non-transactional events in real-time and generate alerts in real-time that can be leveraged for both fraud management as well as revenue enhancement.
This helps banks because that what is meant to protect/save money (curb fraud losses) is also being used to make money (upsell / cross-sell).
Having the same common platform for both critical systems also helps a bank streamline its IT operations in terms of common system interfaces for consistent data quality, maintenance and reduced TCO.
If banks can view their topline and bottom-line as the yin and yang of their business risk management strategy, then a single solution that helps achieve both, becomes the proverbial one stone to target two birds.
Image courtesy: Estudio Polaroid on Pexels
The digital transformation wave in financial services gave birth to a whole new segment of startup digital banks. Challenger Banks (aka Neo Banks in certain countries) now have an enviable number of customers worldwide, thanks to exceptionally superior customer experiences.
Many Challenger Banks didn’t actually begin as banks. They had alternate delivery channels that made it very convenient for customers to transact money. Eventually, they either partnered with existing banks or obtained their own banking licenses. Challenger Banks score high on transparent, low fees and many offer basic accounts for free. They have also launched premium accounts with different services for business customers. With an impressive spectrum of innovative services and product offerings, Challenger Banks are today serious competitors to legacy banks.
While their innovative customer-centric strategies make them agile and responsive, it also makes them more vulnerable to the growing threat of financial crime.
While Challenger Banks strive to keep customer delight at supreme levels, they are at a greater risk than conventional banks when it comes to financial crime risk. Fraudsters can create new crime channels by exploiting the fast and convenient digital services of Challenger Banks. Not assigning the priority that financial crime risk management deserves, lowers the barrier for criminals seeking to perpetrate fraud.
Challenger Banks must do more to insulate their amazing customer experience from potential financial crime threats. With sub-optimal fraud risk management, Challenger Banks face the risk of either increasing customer friction by increasing false positives, or lessening customer trust – should there be a fraud incident.
Challenger Banks can be seen as easy targets by technology savvy fraudsters, who can cleverly exploit vulnerabilities. Also, with the growth of better controls and new regulations to prevent fraud successes, fraudsters constantly seek newer soft spots.
With the assurance of frictionless customer onboarding and customer experience, Challenger Banks face issues of proper scrutiny of customers during onboarding and periodic screening of customers after onboarding. Onboarding processes often involve tiering customers or limiting their spending ability based on the amount of due diligence conducted. Given the high reliance on technology rather than staff, onboarding processes in most Challenger Banks are rather hands-off. Challenger Banks can thus unwittingly onboard undesirable customers at lower tiers.
Challenger Banks have also been targeted by money mules looking to exploit process vulnerabilities. Fraudsters have been exploiting the pandemic situation using a variety of tactics to mask their activity, including using money mules to launder funds.
The global advance of open banking initiatives means customers’ online platforms are now getting connected to Challenger Banks and fintechs that lack the ability to provide robust fraud protection measures. Such weak points can provide fraudsters opportunities to access open banking participants’ data.
There’s also the massive worldwide money laundering problem that has pressurized banks of all sizes, globally. With complex, region-specific regulations, sanction screenings and multiple watch lists, even legacy banks with well-established processes and expert compliance teams, struggle to ensure compliance. A prominent Nordic bank was recently levied a hefty fine for failing to correctly monitor fraudulent transactions. It would be only a matter of time before Challenger Banks face the same intensity of regulatory scrutiny.
New banks have a limit on the transfer of funds in a single transaction, but it doesn’t prove much effective in preventing money laundering. If KYC / CDD processes are lenient, fraudsters can create multiple fake accounts easily and launder large amounts in small parts.
Challenger Banks have undoubtedly been a great idea, as they have redefined banking with a brand-new model. But they cannot side-step the foundational principle, i.e. banking is a business of trust -something that can be impacted with just one unexpected incident.
Striking an optimal balance between delight (from great customer experiences) and trust (from stronger financial crime risk management measures) therefore becomes vital.
For starters, anti-fraud efforts must be built on a unified, cross enterprise foundation, by breaking down silos between channels, products, and fraud types.
Challenger Banks already have a good thing going for them from day 1 – advanced IT systems. This is an advantageous start, because the business can easily adopt best-in-class real-time transactional fraud and anti-money laundering (AML) prevention / detection solutions.
Conventional siloed, channel-centric fraud monitoring and prevention solution options are not ideal for growing Challenger Banks, as they don’t provide an enterprise-wide contextual view of customer / account transactions, besides impacting customer experience by increasing friction and costs.
A robust enterprise-wide real-time financial crime prevention system that monitors all activity from across all channels therefore becomes the keystone in the overall fraud risk management framework.
Monitoring individual customer profiles in real-time along with Machine Learning and Adaptive Behavioral Analytics to assess complex data sets helps Challenger Banks do more to detect fraud and financial crime. Monitoring customers in real-time and across all channels helps accurately detect fraud ‘in-the-moment’ and reduces customer friction, by recognizing genuine activity.
Smarter real-time solutions provide a significant reduction in false positives (genuine transactions declined incorrectly), reduce operational costs, and help meet compliance requirements without compromising customer experience.
Advanced analytics in innovative anti-fraud solutions help integrate data across silos, automates / enhances expert knowledge, and prevent, predict, detect, and remediate fraud. It won’t be an overnight miracle, but it can payback faster benefits while creating the foundation for an anti-fraud framework of the future.
Fraud interventions driven by advanced analytics help in predictive detection, covering user authentication (e.g., determining whether the transacting party is actually a customer), customer due diligence (e.g., low/high-risk fraud profiling as a factor in exception decisioning), and transaction risk (e.g., if indicators of fraud are present in the context of other transactions for the account or customer).
This helps enhance internal process efficiencies, including capacity forecasting and enabling analysts with more context detailing the reasons a transaction failed an initial screen.
Given that it is fundamentally a financial institution, it becomes obligatory for a Challenger Bank to protect its customers from financial crime and fulfil AML / KYC compliance obligations just like any other bank. The rush to make customer onboarding as effortless and as quick as possible leaves digital challengers vulnerable to fraud. Challenger Banks should determine the risk level of their customers by implementing AML / KYC controls during onboarding processes and perform a customer monitoring process appropriate to the customer’s risk level.
Also, the slow progress of AML controls causes delays in customer transactions and consequently reduces customer satisfaction. Checks should be performed quickly and without impacting customer delight that Challenger Banks are known for. Another good measure is to ensure that KYC / customer due diligence processes are frictionless but watertight to help weed out potential fraud at the account origination stage itself.
Fraudsters are experts at exploiting advances in technology, collaboration, and specialization. On the other hand, legacy approaches to fraud prevention have not entirely kept pace, with many banks still obstinately dependent on siloed defense mechanisms and manual processes. Challenger Banks looking to maintain their competitive edge and avoid unnecessary losses to fraud, must be aware of these factors.
Ensuring customer trust is critical for Challenger Banks, and it hinges on going beyond merely implementing an affordable fraud system or upgrading the existing fraud detection system. If customers have to stay thrilled about exceptionally superior services, then it is imperative to achieve the right balance between delight and trust. To be as fraud risk secure as any other bank and by having innovative new-age financial crime risk management approaches, Challenger Banks can successfully scale and conquer the ultimate peak (of trust).