In the fast-evolving landscape of wealth management, artificial intelligence (AI) is poised to be the next game-changer. It promises not just incremental improvements but a profound transformation of how wealth management firms operate, attract clients, and deliver services.

Attracting Ideal Clients
One of the most compelling benefits of AI in wealth management is the ability to attract clients that align with a firm’s ideal profile. By leveraging sophisticated algorithms, AI can analyze vast amounts of data to identify potential clients who fit specific criteria, such as investment preferences, risk tolerance, and financial goals.

How AI Achieves This:

• Data Analysis: AI can scan through social media profiles, financial transactions, and other relevant data points to build a comprehensive profile of potential clients.
• Predictive Analytics: Using prospect information and existing client profiles, AI can predict which prospects are more likely to engage with a firm’s services.
• Targeted Marketing: AI can help by crafting personalized marketing messages that resonate with the identified target audience, thereby increasing conversion rates.

Providing Personalized Service
Personalization is no longer a luxury; it’s a necessity. Today’s clients expect services tailored to their unique needs and preferences. AI enables wealth management firms to offer a highly personalized experience, enhancing client satisfaction and loyalty.

How AI Achieves This:

• Meeting Preparation: AI Copilots can review all your prior meetings with a client to determine key themes and questions to explore in your next client meeting. The Copilot can create a custom meeting agenda for your next client meeting based on this information. Copilots soon will also compare information across your clients to determine agenda topics based on similar client profiles.
• Personalized Communication: AI can analyze client interactions to determine the best times and channels for communication, ensuring timely and effective engagement. They can analyze information in your CRM about your client to create hyper personalized communications for each of your clients saving your team hours of time creating personalized emails.
• Customized Investment Strategies: AI can create bespoke investment plans based on individual client profiles, considering their financial goals, risk appetite, and investment preferences. Your financial planners can review this output to determine if it aligns with your firm’s investment thesis.

Conclusion
Artificial intelligence is set to revolutionize the wealth management industry by attracting ideal clients, offering personalized services, and enabling firms to service more clients efficiently. For C-Suite executives in wealth management, the integration of AI is not just an option but a strategic imperative for staying competitive in a rapidly changing market.

The Oasis Group identified 55 leading firms that specifically service the wealth management industry. The firms in our AI WealthTech Map are not existing wealthtech solutions that are developing AI capabilities – these firms are AI first and were built to support the wealth management industry.

The AI Map follows the sales cycle of a wealth manager by starting with prospecting, followed by writing assistants, note takers, proposal generation, AI assistants, investment research, next best action, and compliance solutions.

Ready to transform your wealth management firm with AI? Stay ahead of the curve and explore how AI can help you achieve unparalleled growth and client satisfaction.

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Security teams at large financial institutions are responsible for managing the execution of not only countless financial transactions spread across a myriad of IT environments, headquarters, branch offices, data centers, and remote work locations, but they must also be diligent in their efforts to detect threats that can be lurking in those environments. Due to the nature of financial services organizations, they are an attractive target for criminal gangs and state-sponsored cyber attackers. Just recently, the U.S. division of China’s biggest lender was hit with a ransomware attack, which disrupted trades in the U.S. Treasury market.
Combined with the responsibility for safeguarding sensitive customer data and critical infrastructure to meet required regulations, their hesitation to rely on automation when dealing with advanced persistent threats, and a crowded tech stack, creates a weighty challenge for Security Operation Center (SOC) teams. And unfortunately, many traditional security tools don’t provide full network visibility and critical evidence. These tools also often overwhelm security teams with false alarms.
Lacking Full Network Visibility Presents Risks

While most enterprise organizations utilize a combination of tools in their tech stack to detect the early warning signs of trouble, too often, the emphasis is put solely on Endpoint Detection and Response (EDR).

EDR primarily monitors and analyzes activities on individual devices (e.g.,servers, laptops and smartphones) – and it’s absolutely a core component of security. But, it ignores network traffic running in the cloud and on-premises environments. And, because it requires installing a software “agent” on every system it monitors, it is largely ineffective in environments with large bring-your-own-device user bases or proprietary operational technology systems.

Monitoring the network for anomalous traffic and other suspicious activity is one of the most impactful ways to detect threats. Because of this, financial services organizations can’t afford to ignore network traffic. Financial services organizations that lack full network visibility are at a greater risk of being attacked through network access points, allowing cyber attackers to remain undetected on their network for long periods of time. When this happens, bad actors can conduct reconnaissance on the network, start accessing more privileges, search for higher value assets, and then start exfiltrating them. They can even plan out larger scale attacks such as ransomware.

The most successful threat detection and response programs combine EDR capabilities with Network Detection and Response (NDR) solutions, which continually monitors network traffic for cybercriminals and suspicious behavior.

Cutting Through the Network’s Noise

Understanding the importance of network visibility is one thing. Actively monitoring it and responding is another challenge. Detecting threats early and having the actionable insight needed to respond before damage can be done is the ultimate goal for security analysts. With so much network activity taking place each day, legacy security solutions are bound to trigger a high-volume of event alerts.

With networks running at very high capacity, it’s difficult for security analysts to determine which threats are false alarms, and which need immediate attention. In this situation, it’s far too easy for cybercriminals to slip through the cracks and onto company networks.
A natural response to this overwhelming volume of alerts would be to eliminate the human element, and look for an automated response mechanism. Of course, in the case of mission critical systems run by financial institutions executing many high-value monetary transactions, any error in an automated response would be costly.

Advanced NDR tools, however, monitor network traffic for suspicious behavior, and then, once detected, they prioritize alerts based on confidence level and urgency. The response to the high-confidence, serious, and imminent threats can be automated, but others must still be reviewed by professional analysts. The built-in automated event triage helps security teams cut through that noise so they can focus on the most important security events, immediately. Advanced NDR tools also provide proactive threat hunting with actionable insights, so security professionals can respond quickly and strategically before any sensitive corporate, financial, or customer data can be stolen.

A Real-World Use Case

Here’s a look at NDR in action: At a large European central bank malicious spyware evaded endpoint defenses and company-wide browser restrictions, moving undetected through the financial institution’s network.

Thankfully, the bank’s NDR solution helped its security team uncover never-before-seen network communications – illustrating the importance of monitoring network traffic – which allowed them to respond before any sensitive customer, state, or country data was breached.

Here’s how it worked. While testing a new feature of the bank’s NDR solution, the organization was alerted to never-before-seen network communications. Upon further review it was determined that a laptop belonging to a member of the infrastructure team had unknowingly installed an adware program. To make matters worse, the malicious agent was attempting a spyware-like exfiltration.

This activity was only detected at the network-level. Ultimately, the discovery of unusual traffic allowed the organization to open an incident, evaluate the impact and determine if any additional points of quarantine were needed.

Addressing Imminent Threats with NDR

In summary, given the extremely sensitive nature of that data financial services work with, ignoring network traffic is too big of a risk to take. By leveraging an NDR solution, security analysts at these organizations can ensure a proactive approach to threat detection and response. And this is a core component of building a comprehensive, multi-layer cybersecurity strategy and protecting company and customer data.

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Table of Contents

• Introduction
• 1. What is Biometrics in the BFSI industry?
• 2. Why Does BFSI Need Biometric Technology?
  • 2.1. Comply with Regulatory Requirements
  • 2.2. Prevent Fraud
  • 2.3. Provide Convenience
• 3. How Are Biometrics Used in Banking
  • 3.1. Customer Re-Authentication
  • 3.2. Branch Banking
  • 3.3. ATMs
• Conclusion

Introduction 
In the ever-evolving landscape of banking, the financial services and insurance (BFSI) industry requires security and convenience to protect sensitive information and enhance customer experience. Consumers demand seamless access to their finances while banks and other financial institutions grapple with continuous threats of fraud and data breaches. Traditional knowledge-based authentication methods like passwords, PINs, or OTPs are proven to be easily compromised, forgotten, or stolen, which increases vulnerability to data and money theft. Thus, adopting innovative solutions like biometric authentication stands out as a transformative force that will help reshape the future of the BFSI industry.

In this article, we will understand the concept of biometric authentication in the BFSI industry.
1. What is Biometrics in the BFSI industry?
The inherent strength of biometrics lies in their uniqueness and non-repudiable nature, unlike passwords, which can be easily stolen. Biometrics, like fingerprints, iris, and voice recognition, are intrinsically tied to an individual, making biometric authentication significantly easier to bypass, and offering robust protection against unauthorized success and fraudulent activities. This rise of biometrics technology has leveraged the BFSI industry to fight against fraud and create a more secure ecosystem for both customers and financial institutions.

BFSI industries around the world are using biometrics in their core financial systems to authenticate customer information.
2. Why Does BFSI Need Biometric Technology?
Biometric technology is a valuable tool for the BFSI industry as it offers numerous benefits that increase the level of security and convenience when compared to traditional authentication methods, like signatures, passwords, PINs and tokens, and in-branch services, to get access to net banking and ATMs.

Here are some of the key benefits that encourage the BFSI industry to implement biometric authentication technology:
2.1. Comply with Regulatory Requirements
When an individual opens an account, financial organizations utilize biometric identity verification to confirm their identification before allowing them to access their services. As a strong protection, biometric technology helps banks reduce the risks connected to financial crimes and money laundering. It also provides an efficient way for financial institutions to comply with KYC and AML regulations. 
2.2. Prevent Fraud
In addition to strengthening identity assurance for regulatory compliance, biometric identity verification provides a strong barrier against fraud. Banks implement multi-factor authentication (MFA) systems, which combine biometric verification with additional authentication methods like a password or PIN, to thwart identity theft and other fraud-related incidents. 
2.3. Provide Convenience
Biometric authentication eliminates the need to remember and type passwords, which can be a frustrating and time-consuming process for users. This can improve the user’s experience and make it easier for them to access their account. Biometrics can also help streamline in-branch banking procedures and make transactions smoother and more efficient.
3. How Are Biometrics Used in Banking
Biometric technology can be used in a variety of ways. It can be used in conjunction with other authentication techniques to build a multi-factor or step-up authentication system. Let’s look at some of the most common applications:
3.1. Customer Re-Authentication
Financial institutions can employ biometrics to develop a quick and safe re-authentication procedure that eliminates the need for consumers to use standard passwords when logging into their accounts. This is critical since valid accounts can still be compromised later in the customer life cycle.
3.2. Branch Banking
Using fingerprint, facial, or iris recognition at financial institution branches offers quick and reliable biometric authentication. When consumers visit financial service institution branches, they can authenticate themselves at the service counter by matching their biometrics, which are often maintained in the institute’s database. In addition, banking institutions use biometrics to allow access to safe deposit boxes, ensuring that only authorized individuals have access to their contents.
3.3. ATMs
ATMs that use biometrics are increasingly common in both developed and developing nations. As a result, a few banks and financial institutes have equipped their ATMs with fingerprint recognition technology. Customers can link their fingerprints with their bank accounts, and when they visit an ATM, they simply place their finger on a biometric sensor. 
Conclusion 
To summarize, the power of biometric authentication technology has and will continue to benefit both customers and the BFSI industry. By offering quick, accurate personalization and secure techniques, this technology is poised to reshape the way users can manage their finances. As the BFSI industry embraces biometrics and navigates the associated challenges, it has unlocked a future where financial transactions are secure and easy for consumers.

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