News

• The voice fraud threat to banking
• Treasury announces Quantum-Readiness Task Force
• The Clarity Act will put Main Street banks at a disadvantage
• Investment account fraud: Red flags and mitigation
• ABA Banking Journal: ABA urges agencies to publish guidance for trust, estate income tax reporting
• CISA News: Round 2 of the Target data breach? Hackers threaten to leak data

SDBA Events

• 2026 SDBA IRA School
• 2026 SDBA LEAD STRONG: Women in Banking Conference
• 2026 SDBA Annual Security Seminar

Online Education

• Additional Educational Opportunities

The voice fraud threat to banking

August 21, 2026

A finance worker at a multinational firm received what appeared to be a legitimate call from someone claiming to be the company’s CFO. The person receiving the call ended up transferring $25 million. The reality: The CFO’s voice was AI-generated. The CFO never made that call.

That incident is no longer an outlier. Voice fraud in banking increased by roughly 30 percent in 2025, with AI-powered synthetic voices capable of fooling even experienced professionals. Synthetic voice attacks against financial institutions rose sharply in 2024, increasing by a factor of approximately 20 compared to the prior year, as data from the same period indicated that roughly one in 750 banking calls was flagged as potentially fraudulent.

Commercial AI voice-cloning tools have significantly reduced the barrier to entry for attackers. As synthetic voice technology becomes more affordable and accessible, attacks can scale more easily and adapt in real time. These capabilities support voice cloning, deepfake impersonation, and synthetic identity schemes. While such attacks are not yet universal across the industry, reported incidents are increasing rapidly, and many industry observers expect them to become a major concern for banks by 2030.

Traditional methods of detection, rules-based systems, statistical modeling, and manual review have struggled to keep pace. Rules-based systems often produce high false-positive rates. Statistical approaches can be time-consuming and resource-intensive. Manual review cannot scale quickly enough. Many existing workflows also lack the capacity for real-time analysis of the large volumes of voice data involved.

Banks have begun warning customers about increasingly sophisticated impersonation attempts, and customers themselves now expect stronger fraud protection. The practical question for many institutions is no longer whether they will encounter synthetic-voice attacks but how effectively they can distinguish genuine callers from generated ones under everyday phone conditions.

Where current defenses are losing ground

A core concern for many banks is the erosion of trust in the voice channel. Surveys indicate that roughly 85 percent of consumers no longer answer calls from unknown numbers, effectively limiting the usefulness of outbound and inbound voice contact. Call-center impersonation, spoofing, and deepfake voice fraud are frequently cited as contributing factors.

Branded calling, which displays the caller’s identity and purpose before the phone is answered, improves transparency, yet it addresses only legitimate caller visibility. It does not prevent deepfake impersonation once a call is connected, nor does it stop social-engineering tactics that follow. From a commercial standpoint, the pricing of branded call services and related analytics reflects that trust in the voice channel has become both a security issue and a revenue issue.

Some carriers and technology providers are shifting emphasis from post-call detection to earlier trust signals, embedding verified identity at the network level so that authentication information is visible before the call is answered. In the United Kingdom this approach has reached nearly full subscriber coverage, illustrating how infrastructure-level solutions can operate at scale. Pre-call validation of this kind offers a practical complement to detection tools that operate only after a conversation has begun.

Data quality remains a practical constraint. The effectiveness of any fraud-prevention system depends on the accuracy and completeness of the underlying information. Clean, verified, and well-structured data continues to be essential for voice-related detection as well as for broader identity verification and anti-money-laundering processes.

Resource limitations also vary considerably across the industry. Institutions with smaller fraud teams, more limited technical infrastructure, or tighter technology budgets can face a slower path to evaluating and deploying specialized tools, a dynamic that affects banks of various sizes, not only the largest commercial institutions.

Finally, many real-time voice detection systems that perform well in controlled laboratory settings show reduced accuracy under everyday phone conditions. Background noise, audio compression, and channel distortion commonly degrade performance. As a result, institutions are examining approaches that combine voice characteristics with behavioral cues and transactional context rather than relying on voice signals alone.

How banks are approaching detection:

Call center impersonation
Call-center impersonation has become one of the faster-growing forms of identity fraud. Using synthetic audio, attackers pose as trusted organizations, banks, payment processors, or even law enforcement agencies to obtain account details or personal information from customers or employees.

Banks are exploring detection tools that analyze voice characteristics in real time to help distinguish genuine human speech from generated audio. These tools are typically deployed as one layer within broader authentication and fraud-monitoring processes rather than as a stand-alone defense and are designed to support secure handling of high-risk transactions, including wire transfers, digital wallet payments, and ACH activity.

Account takeover (ATO) via voice spoofing
Account takeover through voice spoofing occurs when criminals use synthetic or deepfake voices to gain unauthorized access to a customer’s banking, payroll, health savings, or other accounts. The goal is typically to move money or extract personal information (O’Driscoll, 2021; TrustBuilder, 2025).

Both banks and customers feel the effects. Institutions can face reputational harm and increased operational costs from investigating and remediating incidents. Customers often experience direct financial losses, and time spent resolving the problem and, in some cases, secondary damage such as compromised accounts across other platforms.

To address these risks, some providers have introduced multi-layer detection approaches that combine signal-based analysis, behavioral monitoring, and AI-driven detection to identify suspicious activity. Banks evaluating such tools typically view them as one component within a broader authentication and monitoring framework rather than a complete solution in themselves.

Social engineering amplified by synthetic media
Social-engineering schemes increasingly rely on synthetic media. Attackers can generate realistic voices and place calls that impersonate bank executives, customer service staff, or IT support personnel. In some cases, generative AI is also used to test or bypass existing voice-detection systems and to support large-scale credential-stuffing campaigns.

Banks are examining detection platforms that analyze multiple signals rather than voice alone, combining audio analysis with broader contextual information to improve performance under everyday phone conditions. Institutions typically treat these tools as one element within a layered fraud-monitoring process.

Ongoing challenges and emerging approaches
Banks evaluating AI-based voice-fraud tools continue to encounter several practical limitations. Detection systems that work well in controlled settings often lose accuracy when processing real-world phone audio that includes background noise, compression, or long-duration calls. Many models also remain difficult for front-line staff to interpret, and the underlying training data can lack the variety needed for consistent performance across different conditions and attack methods.

Industry and research efforts are therefore focusing on several practical directions:

• Developing lighter-weight detection methods that can operate efficiently on everyday call center audio
• Improving the ability of systems to generalize across different synthesis techniques and noisy environments
• Making detection results more transparent so that fraud teams and call-center staff can understand and act on the output
• Combining voice analysis with additional signals, behavioral cues, and transactional context to create multilayered defenses
• Exploring digital audio watermarking as a way to identify content generated by legitimate tools, or to flag its absence
• Two related trends are also drawing attention. First, some fraudsters now coach victims in real time during calls. Behavioral signals such as changes in speaking intensity or response patterns may help distinguish these coached interactions from ordinary conversations. Second, a few organizations are beginning to consult behavioral specialists to better understand human responses during fraud attempts and to test whether those insights can strengthen detection models.

These developments remain works in progress. Institutions that have tracked how detection tools perform under their own call conditions, documented false-positive rates, and evaluated multi-signal approaches have found themselves better prepared as the technology and the threat continue to evolve.

Deepfake voice fraud is still viewed by many institutions as an emerging rather than fully operational threat. Banks are nonetheless examining how detection and authentication practices may need to evolve as the technology becomes more accessible.

By the end of the decade, the cost of running large generative models is expected to fall substantially—estimates suggest inference costs could decline by more than 90 percent compared with 2025 levels. Lower costs could make sophisticated synthetic-media attacks more widely available and potentially more adaptive when combined with large language models.

Current detection systems often perform adequately in controlled settings but lose accuracy under ordinary phone conditions that include noise, compression, and channel distortion. As a result, attention is shifting toward approaches that combine voice analysis with behavioral cues and transactional context rather than relying on voice signals alone. Digital audio watermarking is another area of interest: legitimate generative AI providers may embed markers that identify content as synthetic so that the absence of such a marker becomes an additional signal worth investigating.

Institutions that have tracked the real-world performance of their existing tools, documented false-positive rates, and evaluated multi-signal methods have found themselves better positioned as both the threat and the available defenses continue to change.

Institutions that have tracked the real-world performance of their existing tools, documented false-positive rates, and evaluated multi-signal methods have found themselves better positioned as both the threat and the available defenses continue to change. Industry exercises such as the UK Home Office Deepfake Detection Challenge illustrate increasing collaboration among government, academic, and private-sector participants.

The voice channel remains an important customer-contact method for many institutions. Maintaining its usefulness will depend on clearer authentication signals, more reliable detection under everyday conditions, and continued attention to the human elements of social engineering.

Anat Goldstein is the founder and CEO of FinOptima Solutions, an AI-driven fraud intelligence company, where Farook Sattar is a senior researcher and advisor.

Go to aba.com’s fraud resource section for updated information and analysis concerning threats to banks and bankers.

Link to original article.

Back to Top

Treasury announces Quantum-Readiness Task Force

August 24, 2026

The Treasury Department today announced the launch of a new public-private initiative “to help accelerate the U.S. financial sector’s transition to quantum-safe technology.”

Quantum computers theoretically would be more powerful than most modern computers and therefore pose significant cybersecurity challenges. The Quantum-Readiness Task Force will bring together government, financial institutions, financial market infrastructures, technology providers and other private-sector leaders to support coordinated preparation for quantum-related cyber risks, Treasury said in a statement.

“America must lead in securing the technologies that power our economy,” Treasury Secretary Scott Bessent said. “This task force will help ensure our financial system remains strong, secure and competitive as new technologies reshape the global landscape.”

The Task Force will operate through three workstreams: Sector alignment and post-quantum computing transition; third-party and vendor readiness; and digital assets and emerging technology risk. The new effort expands on a “roadmap” for post-quantum cryptography in the financial sector previously published by the G7 Cyber Expert Group, according to the department.

Treasury did not announce the task force members.

In related news, the American Bankers Association is participating in a post-quantum task force formed by the Financial Services Sector Coordinating Council and the Financial and Banking Information Infrastructure Committee. Earlier this year, the ABA established the Quantum Security Working Group to provide a forum for ABA members to discuss strategies to integrate post-quantum encryption standards.

Original Article

Back to Top

The Clarity Act will put Main Street banks at a disadvantage

The Blockchain Association’s Summer Mersinger dismisses the harm to community banks in defending the stablecoin rewards language in the Clarity Act, says community banker Nate Franzén.

Summer Mersinger is right about one thing: stablecoins have the potential to make payments faster and more global. She is also right that the United States should not regulate this technology out of existence.

But as a South Dakota community banker, I was disappointed to see her dismiss the voices of banks like mine, suggesting in her recent CoinDesk op-ed that concerns about deposit flight and the loss of local lending were raised by “big banks” and too late in the legislative process. While that may be a convenient political narrative, neither is true.

This issue matters to me and other small South Dakota banks, and we have been shouting it from the rooftops for more than a year. If Congress doesn’t tighten the Clarity Act’s restrictions on stablecoin rewards, small banks and the communities we serve will pay the price.

Mersinger argues that concerns about stablecoins draining bank deposits are largely hypothetical. If a customer moves $100,000 from a bank account into a stablecoin, she points out, that money does not disappear. The stablecoin issuer must hold reserves, potentially including bank deposits and Treasury securities. The money remains in the financial system.

That is true — and it misses the point.

Some people may view our banking system as an abstraction where money and institutions are interchangeable, but the U.S banking system is the envy of the world because of its breadth, depth and diversity. The vast majority of our nearly 4,500 banks are very small, ensuring that every town in every corner of this country can access basic financial services. 

The reality is that most community banks will never hold a dollar of stablecoin reserves, but most community banks will lose deposits to stablecoin wallets. If my customer moves $100,000 from my bank into a stablecoin, and the stablecoin issuer buys Treasury securities to back it, I have lost $100,000 of funding for local credit — my bank and my community will see no benefit from that Treasury bill. 

The distinction matters enormously in a state like South Dakota, where community banks are deeply connected to the agricultural, ranching and small-business economies. The loans we produce may not be the nation’s biggest, but they are the economic lifeblood of the communities we serve.

Smaller banks in this state currently hold about $47 billion in deposits at local branches. The American Bankers Association conservatively estimates that as much $4.7 billion of those community bank deposits could be drawn away by stablecoins if Congress doesn’t put reasonable guardrails in place. That would reduce lending capacity in our state by as much as $3.7 billion. Every one of those lost loan dollars means starting a business or getting a home loan in South Dakota will be that much harder.

The most important issue isn’t whether stablecoin reserves technically stay within the banking system, as Mersinger argues. It is whether stablecoins become a substitute for bank deposits.

That is where the proposed rewards regime becomes consequential — and tremendously damaging to the broader economy.

The GENIUS Act prohibits stablecoin issuers themselves from paying interest. But unless the Senate tightens the yield language in the Clarity Act, an exchange or wallet provider can potentially provide rewards that are similar to interest. That ambiguity may appeal to Coinbase, but it will lead to years of litigation and uncertainty for the broader crypto sector. Even worse, it will put the economy at risk.

If a consumer can earn several percentage points on a stablecoin while receiving the same basic dollar exposure and payment functionality, the product begins to compete directly with deposits. And unlike a community bank, the stablecoin issuer does not turn those funds into mortgages, farm loans or working-capital loans to generate its return. It can simply hold Treasuries. They also don't need to meet all of the rules and regulations that banks like mine face.

That creates an uneven playing field: community banks would be forced to compete for deposits against products that can effectively pass through Treasury yields without performing the credit-intermediation function that banks perform. The end result will be fewer loans and less economic activity.

None of this means Congress should stop stablecoin innovation. Quite the opposite. A sensible policy would preserve stablecoins as payment instruments while preventing exchanges and other intermediaries from using interest-like rewards to recreate high-yield deposit accounts outside the banking system. Transaction-based rewards, similar to what credit card companies offer, seem fair and reasonable to me.

As someone who grew up in South Dakota before holding several important jobs in Washington, Mersinger should recognize the unique role that community banks play in our state and across the country. When a deposit leaves my bank, the question isn’t merely where that dollar goes next. The question is whether I still have the funding to say yes to the next local farmer, rancher or small-business owner who walks through my door.

If Senators, including South Dakota’s two respected lawmakers, want me to keep making those loans and fueling our local economy, then they need to strengthen the Clarity Act before any final vote in September.

Innovation deserves a level playing field. So does Main Street.

Note: The views expressed in this column are those of the author and do not necessarily reflect those of CoinDesk, Inc. or its owners and affiliates.

Original Article

Back to Top

Investment accounts fraud: Red flags and mitigation

Investment account fraud is an evolving threat to individuals and businesses. Scammers use social media, messaging platforms, spoofing and increasingly artificial intelligence to make fraudulent investment opportunities appear legitimate. The schemes vary, but most rely on the same tactics: building trust, promising high returns with little risk, creating urgency and moving money before the victim has time to verify the opportunity.

Understanding common schemes and their warning signs can help investors and financial institutions identify and prevent fraud.

Common investment fraud schemes

Relationship investment scams (sometimes called “pig butchering”): Scammers build relationships through dating apps, social media or messaging platforms over days, weeks or months. Once trust is established, they introduce a seemingly lucrative investment or trading platform. Victims may see fabricated account statements showing significant returns and are encouraged to invest more. When they attempt to withdraw funds, they may be blocked or told to pay additional fees or taxes.

Red flags: An online relationship that quickly becomes financial, with often guaranteed or unusually high returns, unfamiliar trading platforms and requests for additional money to access supposed investment proceeds.

Pump-and-dump scams: Fraudsters promote a stock or cryptocurrency through social media or private messaging groups, often claiming that investors are receiving exclusive or early access. The resulting buying activity drives up the price. The fraudsters then sell their holdings, leaving other investors with losses.

Red flags: “Insider” investment opportunities, pressure to act quickly, anonymous recommendations, and claims that an asset is about to increase dramatically in value.

Rug pull scams: Typically involving cryptocurrency, a fraudster creates and promotes a new digital asset, often creating the appearance of strong demand. Once enough investors contribute funds, the fraudster withdraws the money or liquidity, leaving investors with an asset that has little or no value.

Red flags: New or unverifiable digital assets, anonymous developers, unexplained price increases and promises of extraordinary returns.

Impostor scams: Fraudsters impersonate trusted individuals, investment professionals, financial institutions or legitimate companies. They may use spoofed email addresses, fake websites and documents or AI-generated voices and videos to make the investment appear legitimate.

Red flags: Unexpected investment offers, slightly altered email addresses or websites, requests to move communications to private messaging platforms and instructions to send money to unrelated or personal accounts.

Ponzi schemes: Fraudsters use money from new investors to pay earlier investors, creating the appearance of legitimate returns. The scheme eventually collapses when new investments are insufficient to support withdrawals.

Red flags: Consistently high or guaranteed returns, difficulty withdrawing funds, limited verifiable information and pressure to recruit additional investors.

Pre-IPO scams: Fraudsters offer victims exclusive access to shares in a company before it becomes publicly traded. Professional-looking websites, documents and unsolicited communications are used to create credibility and urgency.

Red flags: Claims of exclusive access, pressure to invest quickly, inability to independently verify the offering and requests to send funds to offshore or unrelated accounts.

Affinity fraud: Affinity fraud exploits trust within identifiable communities, including professional, religious, social or other organizations. Fraudsters may claim to belong to the group or use respected community members to promote the investment.

Red flags: Investment opportunities promoted primarily through personal relationships, claims that a group has been given special access and discouragement of independent research.

Mitigating investment fraud
Engineer a pause. Fraudsters want victims to act quickly. Creating a pause before sending money is one of the most effective defenses.

Investors should independently:

• Research the investment, company and individuals involved
• Verify licenses and registrations
• Contact the purported company using trusted contact information
• Verify references rather than relying on information supplied by the solicitor
• Search for complaints, enforcement actions or other warnings
• Seek advice from an independent financial professional when appropriate
• If an investment appears to come from a friend, family member or trusted professional, contact that person directly using a previously established communication method.

Investors should also protect their credentials and sensitive information. Never provide passwords, authentication codes or other security information to someone claiming to assist with an investment.

Strengthen financial institution controls. For financial institutions, customer education should be paired with transaction monitoring and effective intervention.

Investment fraud may produce transactions that are inconsistent with a customer’s normal behavior, including:

• Unusual transaction amounts or velocity
• New or unusual payees
• Transfers to cryptocurrency exchanges
• Transfers to newly established external accounts
• Unusual international or cross-border transactions
• Liquidation of established assets followed by rapid transfers
• Sudden changes in account behavior following a new relationship or communication pattern
• Detection models should be supported by a clear customer-intervention strategy. Employees should be trained to recognize potential investment fraud and engage customers using active listening and empathy.

Questions can help uncover fraud without putting the customer on the defensive, such as: How did you learn about this investment? How do you know the person receiving the money? How did you independently verify the investment?

The objective is not simply to stop a transaction. It is to help the customer recognize the deception and prevent additional losses.

Investment fraud continues to evolve as criminals adopt new technology and increasingly sophisticated social-engineering techniques. Despite the variety of schemes, the warning signs are often consistent: unusually high returns, urgency, exclusivity, unfamiliar investment platforms, difficulty verifying the opportunity and pressure to move money quickly.

Investors can reduce their risk by slowing down, independently verifying investment opportunities and protecting their financial information. Financial institutions can further reduce losses through effective transaction monitoring, employee training and empathetic customer intervention.

When an investment opportunity creates pressure to act immediately, the safest first step is to pause, verify and then decide.

Original Article

Back to Top

ABA Banking Journal: ABA urges agencies to publish guidance for trust, estate income tax reporting

The Treasury Department and IRS should issue guidance on income tax reporting for trusts and estates under the One Big Beautiful Bill Act to ensure consistent application of the law and avoid a confusing mix of state interpretations on how to implement it, the American Bankers Association said today.

Among the many tax provisions in the OBBBA was new language on trust and estate income tax reporting, which took effect at the end of last year. In a letter to the agencies, ABA said that because banks and other financial institutions administer a substantial share of fiduciary assets, prompt guidance is essential to ensure consistent application of new tax policy.

“The need for timely guidance is further heightened by the ongoing state conformity process following enactment of OBBBA,” ABA said. “If states adopt differing conformity positions while federal treatment remains uncertain, fiduciaries and financial institutions could face significant compliance and reporting challenges resulting from inconsistent federal and state tax treatment.”

ABA offered several recommendations on what the guidance should include, such as clarifications about the treatment of deductions, and suggested the agencies implement them well before the April 15, 2027, filing deadline for the current tax year.

Original Article

Back to Top

CISA News: Round 2 of the Target data breach? Hackers threaten to leak data

US merchandise giant Target may have been hit by another breach this year, with hackers claiming to have stolen source code.

Target, a major US general merchandise retailer, has once again appeared on the dark corners of the internet.

A newcomer to the ransomware scene, going under the name Xpl0itrs, is behind the claims.

The gang created the leak site on the Dark Net on June 17th and started listing victims on August 15th. The threat actor claims to have stolen 8.6GB of Target’s source code.

It has set a deadline for the company to reach out and negotiate within 2 days, threatening to leak the data if it doesn't.

The legitimacy of the claims remains unverified. Cybernews has reached out to Target and will update this article once a response is received.

With over 2,000 stores across the United States, the Target Corporation boasts $104.78 billion in annual revenue.

Has Target been breached again?
At this point, there is no confirmation if it is a new data breach affecting Target. However, Cybernews researchers believe that the claimed 8.6GB dataset may be connected to a data leak that hit Target in January this year.

An unknown threat actor created multiple repositories on Gitea, a self-hosted Git service, purportedly containing portions of Target's internal code and developer documentation.

The listing was more than 57,000 lines long and advertised a total archive size of approximately 860GB.

Target locked down git[.]target[.]com behind VPN on January 9th. Reportedly, the breach was traced to an infostealer that hit an employee workstation in late September 2025.

Xpl0itrs has not provided any data samples to help define what data has been stolen. While significantly smaller than the previously stolen dataset, it also includes source code, as the threat actor claims in the listing.

Target has leaked 40 million credit cards before
Target has been associated with a tremendous data leak before. In 2013, Target suffered a massive data breach.

After credentials were stolen from a third-party contractor, the credit and debit card information of 40 million people was stolen.

Target later acknowledged that the attack had also exposed contact and identifying information for as many as 70 million individuals.

Xpl0itrs has previously claimed OpenAI and Spotify
The gang has previously claimed high-profile victims, but the legitimacy of these alleged breaches raises questions.

In June, Xpl0itrs conducted a staged, 2-post campaign on X (formerly Twitter), publicly naming Spotify, the US Department of the Treasury, OpenAI, and Trustpilot as its victims.

According to analysis by Dataminr, attackers had an affiliate account, @xpl0itrsturtle2, which posted a teaser – a winking emoji next to a 4-logo image grid showing Spotify, US Treasury, OpenAI, and Trustpilot logos.

After a week, the primary @xpl0itrs account followed up, confirming the same 4 targets by referencing the previous post.

Shortly after, X suspended the @xpl0itrs account. No formal dark-web forum listing with actual data samples for any of the 4 targets has been found since.

Among the gang's other victims is the Australian company Oz Hair & Beauty. The Aussie company was listed with an alleged 2.1M customer records. The company confirmed that some customer data was affected by a breach at a third-party provider.

The threat actor also claimed to have stolen 800 motorcycle and dealership documents from BMW. However, Cybernews researchers discovered that the data was partly publicly available anyway.

Original Article

Back to Top

2026 SDBA Annual Security Seminar

October 8 | Hyatt Place | 4935 W. Lake Shore Blvd | Sioux Falls, SD

Bank security teams face an increasingly complex threat landscape—one that extends far beyond traditional robbery response. This full-day training program is designed specifically for bank security professionals responsible for protecting people, facilities, and operations in today’s dynamic banking environment.

Hileman Security Training Group (HSTG) has been providing training for several years, and this program reflects the evolution of both the threat environment and the lessons learned from working closely with financial institutions across the region. While building on proven principles, this course delivers new content, updated case studies, current trends, new video analysis, and a fresh perspective—ensuring value for both first-time and returning attendees.

Who should attend? Bank security teams, physical security professionals, risk management, investigations staff, operations, leadership and those responsible for workplace violence prevention and response.

Review the agenda & register here.

Online Education

Participating in learning opportunities outside the bank can be challenging. Take advantage of the SDBA's extensive selection of webinars and on-demand training to enhance your banking expertise directly from your computer.

GSB Online Seminars
OnCourse Learning
SBS Institute
ABA Training

Learn how to put compliance management solutions from Compliance Alliance to work for your bank, by contacting (888) 353-3933 or [email protected] and ask for our Membership Team. For timely compliance updates, subscribe to Bankers Alliance’s email newsletters. 

Back to Top

---

SDBA eNews Archive

View past issues of the SDBA eNews

Advertising Opportunity
Learn more about sponsoring the SDBA eNews

Questions/Comments
Contact the SDBA at 605.224.1653 or via email