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By Dan Barta, Principal Solutions Architect, SAS Global Security Intelligence Practice


Analytics and artificial intelligence uncover the real challenge – synthetic identities

The financial services industry won’t soon forget the headlines of 2013, when a 63-year-old New Jersey jeweller was charged with leading a fraud ring that colluded with merchants getting kickbacks. One of the largest credit card fraud schemes prosecuted by the US Department of Justice, this one involved more than 7,000 fake identities and 25,000 fraudulent credit cards obtained through banking application fraud, resulting in more than $200 million in losses.

Early-detection analytics can redefine the odds of discovering banking application fraud. For example, in our work here at SAS with an Asia Pacific bank, network analysis found:

  • 60,000 contact phone numbers referencing immigration agents.
  • 5,000 contact numbers referencing casinos.
  • 2,500 phone numbers referencing the bank branch at which the application was made.
  • 1,500 numbers referencing a meat processing plant.

These signs pointed to fraudsters flying below the radar with high-volume, low-value credit applications. Using SAS® software, the bank found four times more banking application fraud, valued at $3 million a month, compared to its former techniques.

The analytic methods that help detect banking application fraud also apply for other credit-granting organisations, such as telcos, online retailers and auto finance organisations.

Synthetic identities: The gold standard for banking application fraud

Fraudulent applications can start with stolen or manipulated identities, but the preferred approach is to use synthetic identities – a combination of fabricated credentials not associated with a real person. Hence, no one complains about a new unauthorised account, credit card or line of credit.

This dissociation from a real person makes banking application fraud with synthetic identities particularly attractive to fraudsters – and more challenging to detect. Gartner estimates that synthetic identities are behind 20 percent of credit charge-offs and 80 percent of credit fraud losses.

A common pattern in the US is to create fake Social Security numbers or get them off the “dark web” – preferably SSNs of the deceased or children, not likely to notice unauthorised credit activity. Once an identity is created, the fraudster builds the appearance of a real person by:

  • Applying for credit, which triggers a credit bureau record whether the identity is real or not.
  • Adding the synthetic identity as an authorised user on an existing account, which may itself be a sham.
  • Getting merchants, real or fake, to collude in creating bogus credit accounts and credit bureau reports.

For all three approaches, the underlying theme is the same: The fraudster exploits the services of the credit industry – banks, other creditors and credit bureaus – to build a credible identity to gain access to yet more credit. That’s banking application fraud at its core.


How to detect bust-out fraud

That New Jersey ringleader and his associates had honed the art of a bust-out scheme: open a line of credit for a fake identity, cultivate a good history for that account, then grab the big payoff. In insider terms, it’s “make up,” “pump up” and “run up and cash out.”

Analytics and machine learning are empowering banks and other creditors to fight back more effectively – and earlier in the game. The trick is that the best analytical methods will vary depending on available data, the type of fraud and the phase of the endeavour. Multiple methods used together can very effectively find fraud while managing false positives.

At the make-up stage, the fraudster manufactures identities and uses them to gain access to credit. Financial institutions can spot the seeds of future fraud by:

  • Monitoring application data to see if the same information or device is being reused across multiple identities that otherwise appear unrelated.
  • Assessing past experience for existing or closed accounts that shared the same data element, such as device ID, address or SSN.
  • Searching for “proof of life,” well-rounded details for the identity, such as driver’s license, voter registration or property ownership.
  • Analysing the social network to spot unusual or suspicious connections (or lack thereof) among applicants, devices, accounts, credit files and application data.


At the pump-up stage, the fraudster uses credit lines in a normal fashion, making small purchases and paying off the account each month, thereby creating the appearance of good credit, which is used to request further credit.

Even though the fraudster is building a good credit file, there are ways to identify suspicious or high-risk activity on these accounts through rules and models. For example:

  • Are payments from the same source (bank and account) being used to pay otherwise unrelated accounts?
  • Is the same device being used to access and/or make payment on what appear to be unrelated accounts?
  • Are credit lines fully used soon after account opening?
  • Is the bank offering the credit line increases, or are the requests coming from the “customer”?
  • Given the demographic data on the credit application, would the credit-holder be likely to purchase from the type of merchants where the account is being used?


At the run-up and cash-out stage, the fraudster (or organised fraud ring) maxes out the cards and disappears. In some cases, the fraudster will make a final payment with a counterfeit check and quickly max out the accounts before the bank realises the payment is worthless. This results in an even higher loss than the credit limit on the card.

It would be optimal to uncover the scheme before the run-up and cash-out stage. Rules and models can detect late-breaking indicators, such as:

  • Increased transaction frequency.
  • Repeatedly maxing out a credit line and paying it off in full without carrying a balance.
  • Payment on a card significantly before the payment due date.
  • Payment by check when prior payments were made online.
  • Network association with other accounts showing high-risk activity.

If a charge-off occurs, forensic analysis of the account can help you tune the rules and models for ever-greater precision and support smart collection efforts. You can use the experience from previous scenarios as inputs for unsupervised or supervised machine learning, where the algorithm finds and learns from patterns in the data. By uncovering what you didn’t know to look for, machine learning has been shown to detect more fraud, even rare events that don’t follow common patterns.

On the positive side, fraud detection analytics can also affirm legitimate applications that can then be fast-tracked to approval for a more positive customer experience, lower friction and fewer abandonments. With better application screening, good customers get expedited service, and bad ones are detected before they cash out.

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Wealth Managers and the Future of Trust: Insights from CFA Institute’s 2022 Investor Trust Study



Author: Rhodri Preece, CFA, Senior Head of Research, CFA Institute


Corporate responsibility is more important than ever. Today, many investors expect more than just profit from their financial decisions; they want easy access to financial products and to be able to express personal values through their investments. Crucial to meeting these new investor expectations is trust in the financial services providers that enable investors to build wealth and realise personal goals. Trust is the bedrock of client relationships and investor confidence.

The 2022 CFA Institute Investor Trust Study – the fifth in a biennial series – found that trust levels in financial services among retail and institutional investors have reached an all-time high. Reflecting the views of 3,588 retail investors and 976 institutional investors across 15 markets globally, the report is a barometer of sentiment and an encouraging indicator of the trust gains in financial services.

Wealth managers may want to know how this trust can be cultivated, and how they can enhance it within their own organisations. I outline three key trends that will shape the future of client trust.



ESG metrics have risen to prominence in recent years, as investors increasingly look at environmental, social and governance factors when assessing risks and opportunities. These metrics have an impact on investor confidence and their propensity to invest; we find that among retail investors, 31% expect ESG investing to result in higher risk-adjusted returns, while 44% are primarily motivated to invest in ESG strategies because they want to express personal values or invest in companies that have a positive impact on society or the environment.

The Trust Study shows us that ESG is stimulating confidence more broadly. Of those surveyed, 78% of institutional investors said the growth of ESG strategies had improved their trust in financial services. 100% of this group expressed an interest in ESG investing strategies, as did 77% of retail investors.

There are also different priorities within ESG strategies, and our study found a clear divide between which issues were top of mind for retail investors compared to institutional investors. Retail investors were more focused on investments that tackled climate change and clean energy use, while institutional investors placed a greater focus on data protection and privacy, and sustainable supply chain management.

What is clear is that the rise of ESG investing is building trust and creating opportunities for new products.


Technology has the power to democratise finance. In financial services, technological developments have lowered costs and increased access to markets, thereby levelling the playing field. Allowing easy monitoring of investments, digital platforms and apps are empowering more people than ever to engage in investing. For wealth managers, these digital advancements mean an opportunity for improved connection and communication with investors, a strategy that also enhances trust.

The study shows us that the benefits of technology are being felt, with 50% of retail investors and 87% of institutional investors expressing that increased use of technology increases trust in their financial advisers and asset managers, respectively. Technology is also leading to enhanced transparency, with the majority of retail and institutional investors believing that their adviser or investment firms are very transparent.

It’s worth acknowledging here that a taste for technology-based investing varies across age groups. More than 70% of millennials expressed a preference for technology tools to help navigate their investment strategy over a human advisor. Of the over-65s surveyed, however, just 30% expressed the same choice.



How does an investor’s personal connection to their investments manifest? There are two primary ways. The first is to have an adviser who understands you personally, the second is to have investments that achieve your personal objectives and resonate with what you value.

Among retail investors surveyed for the study, 78% expressed a desire for personalised products or services to help them meet their investing needs. Of these, 68% said they’d pay higher fees for this service.

So, what does personalisation actually look like? The study identifies the top three products of interest among retail investors. They are: direct indexing (investment indexes that are tailored to specific needs); impact funds (those that allow investors to pursue strategies designed to achieve specific real-world outcomes); and personalised research (customised for each investor).

When it comes to this last product, it’s worth noting that choosing advisors with shared values is also becoming more significant. Three-quarters of respondents to the survey said having an adviser that shares one’s values is at least somewhat important to them. Another way a personal connection with clients can be established is through a strong brand, and the proportion of retail investors favouring a brand they can trust over individuals they can count on continues to grow; it reached 55% in the 2022 survey, up from 51% in 2020 and 33% in 2016.



As the pressure on corporations to demonstrate their trustworthiness increases, investors will also look to financial services to bolster trust. Wealth managers that embrace ESG issues and preferences, enhanced technology tools, and personalisation, can demonstrate their value and build durable client relationships over market cycles.

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2022 ESG Investment Trends



Jay Mukhey, Senior Director, ESG at Finastra


Environmental, Social and Governance (ESG) themes have been front and center throughout the pandemic. While the framework has been surging in popularity for several years, COVID-19 served as a period of reflection causing many companies, investors and other individuals to take these factors seriously. It’s something that we can no longer afford to ignore.

Jay Mukhey

We are witnessing drought, adverse weather patterns, hotter climates, and wildfires with more regularity, raising the profile of the climate crisis. Efforts were renewed at COP26 in Glasgow last November to help address the challenge, with the signing of the Glasgow Climate Pact and agreement of the Paris Rulebook. As a result, we are now seeing record net new inflows into ESG investing and impact.


Evaluating ESG criteria

Long gone are the days when ESG issues were at the periphery of a company’s operations. In just a few short years, ESG criteria have become a key metric for investors to evaluate businesses they are considering investing in.

Investor money has poured into funds that consider environmental, social and governance issues. Data from the US SIF Forum for Sustainable and Responsible Investment shows that ESG funds under management have now reached more than $16.6 trillion. It’s not just institutional investors who are embracing ESG, with Bloomberg Intelligence predicting that savers across the world will amass £30.2 trillion in ESG funds by the end of the year.

Due to the multitude of divergent factors that contribute to a company’s success on ESG, it can be tricky to pin down exactly what criteria to measure. Depending on the industry a company operates within, environmental criteria could include everything from energy usage, the disposal of waste and even the treatment of animals.

Social criteria are primarily related to how a company conducts itself in business relationships and with stakeholders. For example, does it treat suppliers fairly? Is the local community considered when the business makes decisions that would impact them? Do they have a statement and policy around modern slavery?

While governance criteria have traditionally been an afterthought, this may be changing. Everything from executive pay to shareholder rights and internal controls are relevant to investors within these criteria.


Tracking ESG for competitive advantage

Many experts within the financial services industry point to the power of ESG as a major competitive advantage, if used correctly. It has been noted that increasingly corporations, from big Fortune 500 companies down to small scale-ups, will communicate on their sustainability metrics to grow their business and to attract talent. However, it’s no longer enough to just pay lip service to ESG issues, with abstract commitments increasingly being seen as insufficient. Companies must now quickly progress to concrete objectives that can be measured and tracked.

A wide range of data providers now offer detailed information and tools that can measure ESG performance and effectiveness. Yet major challenges remain around bringing together what is often extremely fragmented data and transforming it into actionable insights.


Focus areas for 2022

The ESG criteria that investors measure is by no means stagnant. Complex societal challenges regularly emerge that require the attention of companies. Contributors recognize several topics that demand a sophisticated approach, including the COVID pandemic, diversity challenges and powerful social movements.

Companies operating within the financial services sector face several specific challenges related to ESG, with contributors believing that fintech will also continue to play a central role in finding answers to them.
For example, industry experts expect customers to be more demanding of firms in SME lending when it comes to understanding exactly what impact they are having on the climate. For many financial services firms, 2022 will be the year that they will try to reduce the time it takes to bring ESG products and services to market, such as green loans and mortgages, as well as checking accounts with sustainability and carbon tracking capabilities.

When selecting a service provider, customers are increasingly interested in the ESG credentials of their bank or financial institution. Research from PwC finds that 80% of consumers are more likely to buy from a company that stands up for environmental and governance issues. Consumers are one of the main drivers of ESG and many are putting their money where their mouth is. It’s a trend that’s not going away; financial institutions need to start implementing their strategy for ESG now.

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