The Consumer Financial Protection Bureau (CFPB) understands tools such as artificial intelligence and machine learning are making their way into underwriting departments at auto finance companies and other providers of financial services.
It’s why CFPB director Kathleen Kraninger recently reiterated that the regulator is keeping close tabs on the potential impact artificial intelligence (AI) and machine learning could have on deciding who is approved for credit.
Kraninger made the assertions during the TCH + BPI Annual Conference, a gathering for financial services executives, regulators, policymakers, and academics to discuss the changing regulatory landscape and the future of payments hosted by the Clearing House and the Bank Policy Institute. Kraninger emphasized in her remarks that the bureau is strongly committed to helping spur innovation, while being mindful of possible risks.
“Alternative modeling techniques, such as the use of machine learning algorithms, have the potential to expand access to credit for some of the approximately 45 million Americans with no or thin credit files,” Kraninger said. “The technologies also can make models more efficient, leading to faster decision times and potentially reducing the cost of credit. Given these potential benefits, we see these technologies as important to our mission.
“Despite AI’s potential to expand access to credit, uncertainty about how AI fits into the existing regulatory framework may be hindering adoption of the technology, especially for credit underwriting,” she continued.
“One issue we have heard a lot about is whether complex AI models are compatible with the adverse action notice requirements in the Equal Credit Opportunity Act (ECOA) and the Fair Credit Reporting Act (FCRA),” Kraninger went on to say. “For example, ECOA requires creditors to explain to consumers the main reasons for a denial of credit or other adverse action. FCRA includes additional requirements for credit report and similar information used in taking adverse action.”
Kraninger noted that the CFPB is aware development of tools and technologies to explain complex AI decisions accurately continues to develop.
“These developments hold great promise as ways to comply with the adverse action notice requirements,” she said.
Furthermore, Kraninger mentioned the regulator is interested in exploring three specific areas regulatory uncertainty, including for adverse action notices. They include:
— Methods for determining the main reasons for a denial of credit or other adverse action
— The accuracy of explainability methods
— Experimentation on how to convey the reasons in a manner that accurately reflects the factors used in a model and is understandable to the consumer.
“The bureau intends to leverage experiences gained through the innovation policies,” Kraninger said. “For example, applications granted under the innovation policies, as well as other stakeholder engagement with the bureau, may ultimately be used to help support an amendment to a regulation or its commentary.”
On Wednesday, defi SOLUTIONS announced a partnership with Zest AI, a leader in AI software. Zest AI will provide defi clients direct access to Zest Automated Machine Learning (ZAML) software for loan decisioning.
Officials explained the partnership between defi SOLUTIONS and Zest AI can make machine learning credit scoring and advanced risk management capabilities more accessible to banks, credit unions, finance companies and other lenders.
Organizations using ZAML software to predict creditworthiness typically achieve a 15% approval rate increase with no added risk, or a 30% decrease in charge-offs with constant approval rates, according to Zest AI.
“defi helps lenders of all sizes leverage and capitalize on innovations such as Zest AI technology,” said Charles Sutherland, defi SOLUTIONS chief strategy officer. “We welcome Zest AI to the defi COMMUNITY and are excited to bring the benefits of their software to our clients through our defi products.”
Mike de Vere, chief operating officer at Zest AI, added in a news release, “AI and machine learning are the future of business, and our platform is helping lenders better manage and dramatically advance their credit underwriting business.
“defi SOLUTIONS’ ability to quickly and easily integrate our software into their offerings is of great benefit to their current and future clients,” de Vere went on to say.
Does more data mean more problems? You might arrive at that conclusion based on information from a new Aite Group study commissioned by TransUnion.
Across the globe, companies are amassing volumes of data with the intent of optimizing performance, identifying trends and meeting rising consumer expectations. Yet this new research showed nearly 75% of financial services and insurance executives admit they are challenged by the fractured nature and vast amount of data available.
As a result, experts think it’s difficult for many of them to achieve rich analytics capabilities to further their respective businesses.
Even with these challenges, this study found that executives in the financial services and insurance industries plan on continuing to secure more data sources. Furthermore, they look to incorporate more artificial intelligence (AI) and machine learning (ML) technology into their analytic platforms to help them make sense of the information.
The global study explored the existing analytical processes, tools, data sources and operational effectiveness of analytics solutions used by the financial services and insurance industries. The quantitative online survey recorded the feedback of 682 marketing and risk executives at financial institutions located in the U.S., Canada, U.K., Hong Kong and India, many of whom do business across the globe.
The study found that the proliferation of AI/ML is expected to continue during the next 24 months with three in four global executives considering integrating new analytic technology into their platforms.
There’s good reason for this implementation as AI and ML can shorten the traditional analytic lifecycle from months to just weeks or even days, according to Gene Volchek, senior vice president of global data science and analytics at TransUnion.
“Businesses are reevaluating their technology investments, and looking to implement artificial intelligence, machine learning and alternative data models and sources,” Volchek said in a news release.
“Their end game is to gain deeper analytics and competitive insights that better allow them to mitigate risk and meet consumer needs,” he continued. “Ultimately, the companies that best leverage these data and analytical technologies will provide consumers with the best experiences, resulting in more revenue.”
Help wanted to enhance analytic capabilities
To stay competitive in a data-rich world, experts acknowledged companies need access to cutting-edge analytic solutions and data science expertise. However, the study found that inflexible legacy technology, talent shortages and regulatory barriers are among the factors that prevent businesses from harnessing the power of analytics with speed and ease.
“Most financial institutions lack a single, cohesive analytics platform,” said Tiffani Montez, senior analyst at Aite Group. “Firms may have vastly different data repositories and teams managing analytics functions, often leading to multiple approaches — by line of business, role and channel — across their institutions.
“To address these issues, many financial institutions are looking to centralize their data into a single platform that can quickly support change and integrate new data models,” Montez continued.
Enhancing analytic capabilities through AI/ML technology is a top priority globally, but with distinct differences across geographies.
The United States lags in AI/ML technology adoption with 22% of U.S. executives indicating they currently do not have any solutions that can implement AI/ML into analytical models. While this capability may be commonly lacking, 66% of U.S. respondents also believe this technology is a major differentiator.
The study indicated the data scientist talent shortage is another pressing issue contributing to the global insights gap. As the volume of data has increased, the need for data science and analytics professionals has increased exponentially.
Globally, 86% of respondents noted there are challenges with accessing the right data science and analytics talent, compared to 74% of executives in the U.S.
“To enable purposeful insights development, it is crucial for companies to streamline their processes and have closer alignment between the technical tools that are readily available and talent with specialized knowledge of turning data into insights,” officials said.
In the report, financial institutions noted they are increasing their investments in both talent and in analytics technology — but these firms are also greatly increasing their investments into another resource, more data.
Analytics Challenges Across Regions
|
Region
|
Percent of Respondents Stating that Finding Qualified Data Scientists is a Challenge
|
Percent of Respondents Stating that AI/ML is a Competitive Differentiator
|
Percent of Respondents Stating that they have no AI/ML
Analytical Models
|
|
United States
|
74%
|
66%
|
22%
|
|
Canada
|
82%
|
58%
|
7%
|
|
Hong Kong
|
88%
|
62%
|
14%
|
|
United Kingdom
|
85%
|
58%
|
18%
|
|
India
|
97%
|
78%
|
13%
|
|
Total
|
86%
|
66%
|
14%
|
*The Aite Group Global Survey of Marketing and Risk Executives was conducted in Q3 2019.
Despite challenges, growth expected
TransUnion and the Aite Group emphasized financial institutions have placed an increasing amount of influence on the value of expanding data sources. The desire to invest in data includes new sources such as non-traditional, third-party and alternative data among the banking and insurance communities.
During the next 24 months, the study noted 89% of institutions have plans to use alternative data.
More than half of respondents plan to increase spending on most types of data sources with 65% intending to increase spend on newer forms of data such as mobile information about web browsing and app usage.
In the U.S. alone, 44% of executives indicated that the integration of new data sources will be very important to their business strategies. Yet the lack of the right tools continues to pose an issue as only 14% of U.S. firms can integrate new data sources across all of their analytic solutions.
The survey also found that across all regions, 78% of marketing executives and 70% of risk executives expect their overall budget to increase year-over-year, for data analytics /big data and analytics/data science tools for each role, respectively. Volcheck explained this finding points to a significant investment in expanding the amount of data available despite ongoing challenges such as data cleansing and prep, which 76% of respondents said can be significantly challenging.
He added this is in addition to the larger operational issues such as cumbersome technology and the talent deficit.
Global Investment in Alternative Data Sources Expected to Increase Over the Next Two Years
|
Alternative Data Source
|
Investment Increase of More than 15%
|
Investment Increase of 5% to 15%
|
Investment Increase of Less than 5%
|
|
Mobile Data (browsing, app usage, etc.)
|
19%
|
25%
|
21%
|
|
Purchase (Spending) Data
|
15%
|
26%
|
18%
|
|
Social Media
Data
|
14%
|
24%
|
20%
|
|
Transactional or Bank Account Data
|
13%
|
23%
|
22%
|
|
Shared Data Sources (Third-Party Source)
|
13%
|
19%
|
24%
|
*The Aite Group Global Survey of Marketing and Risk Executives was conducted in Q3 2019.
“Integrating data from across a consumer’s credit journey provides a rich canvas for drawing insights, however it is clear that financial and insurance industries are struggling to manage and extract the right information without access to the proper analytical tools or having people with the right skillset,” Volchek said.
“Those companies that put in the investment will also most likely develop the top solutions that make them more competitive in today’s consumer-driven market,” he went on to say.
To learn more about the state of analytics in the financial services and insurance industries, access the full Aite Group and TransUnion report titled, “Current State Assessment: Global Analytics Ecosystem,” on this website.
ZestFinance, a provider of credit software fueled by artificial intelligence (AI), announced its integration with MeridianLink, a multichannel loan and new account origination platform.
According to a news release distributed last week, MeridianLink will be integrating Zest Automated Machine Learning (ZAML) credit scoring directly to its LoansPQ platform, providing MeridianLink clients the ability to access advanced machine learning for lending.
The companies explained machine learning underwriting uses thousands of credit signals to make more accurate and profitable credit decisions than traditional methods, resulting in more good contracts and fewer bad ones. On average, Zest customers see a 15% increase in approval rates without increasing losses, as well as increases in booked loans due to more competitive, risk-based pricing.
Officials added machine learning models are especially good at safely increasing approval rates for traditionally underserved segments. One auto-finance company used Zest to increase approvals for millennials by 25%.
“Our integration with MeridianLink removes the resource and risk constraints that have made machine learning technologically challenging for lenders,” said Jay Budzik, chief technology officer of ZestFinance. “The partnership will increase the adoption of machine learning and give more consumers access to fair credit.”
MeridianLink’s LoansPQ is a single origination platform, consolidating all channels (mobile, branch, call center, indirect, retail and kiosk) into a single processing system for a consistent experience for originators, underwriters, processors and funding officers.
Zest anticipates that the addition of machine learning into LoansPQ will allow MeridianLink clients to achieve a positive ROI in year one by pricing their products more effectively.
“Machine learning technology is typically only available to larger financial institutions, but with this integration with Zest, our clients of any size can take advantage of it,” said Doug Glagola, vice president at MeridianLink.
FICO chief analytics officer Scott Zoldi recently reached the century mark, achieving another data-science career milestone with his 100th software patent application.
Zoldi has been an inventor on 100 patent applications for machine learning and AI software technologies and techniques. Of the 100 patent applications, FICO said 47 have been granted, and 53 are pending.
In his nearly 20-year career with FICO, the innovations he has pioneered have helped FICO products transform entire industries. The company highlighted he has developed unique machine learning inventions for financial fraud, anti-money laundering, cybersecurity and collections, as well as fundamental data science capabilities.
“Dr. Scott Zoldi is a tremendous asset to FICO and our customers worldwide,” FICO chief executive officer Will Lansing said in a news release. “Scott’s non-stop creativity in developing AI, machine learning and analytic technologies is captured in the large portfolio of intellectual property he has produced. His work has propelled FICO’s competitive advantage in our fraud, compliance, cybersecurity and collections business units and within our corporate body of machine learning applications.
“Beyond the data science lab, Scott brings innovative thinking and enthusiasm to every customer conversation, industry speaking engagement and team meeting,” Lansing continued.
Zoldi’s patent work addresses a broad range of domains, including:
— Fraud analytics
— Cybersecurity
— Collections and credit risk
— Unstructured data analytics
— Unsupervised machine learning
— Utility analytics
— Self-learning machine learning models
— Explainable and ethical AI
— Deep learning algorithms
— Anti-money laundering
— Mobile analytics
“FICO is driven to help our customers operationalize analytic innovation,” said Stuart Wells, executive vice president of products and technology and chief technology officer at FICO. “They are looking for practical ways to put AI and machine learning to work today, to solve business problems and work more efficiently.
“Scott’s work is at the heart of our broader initiatives to operationalize AI, ML, and other emerging technologies,” Wells added.
In total, FICO currently holds 197 US and foreign patents, and 102 pending patent applications.
Zoldi and his team will present many of their latest analytic innovations at FICO World on Nov. 4-7 in New York. He will also present the closing keynote address on ethical AI.
“I am endlessly fascinated by the behavioral patterns and predictive insights that data can yield, and developing new machine learning algorithms to capture them,” Zoldi said. “During my nearly 20 years at FICO, I have had the opportunity to apply my analytic curiosity to develop machine learning applications addressing a wide range of seemingly unpredictable human and machine behaviors.
“I am thankful to be surrounded by brilliant colleagues at FICO who have influenced my thinking, and who have co-authored numerous of the patent applications. It is a true honor to have the novelty of my work acknowledged by patent offices around the globe and in use across FICO’s customer base,” Zoldi went on to say.
Zoldi previously participated in an episode of the Auto Remarketing Podcasted recorded in San Francisco earlier this year during the Vehicle Finance Conference hosted by the American Financial Services Association. Zoldi described what clean data really is.
That conversation is available below.
As an evaluation firm articulated the top seven steps to follow within a software development life cycle, a provider of cloud-based software solutions for all financial institutions announced the results of its latest survey focused on the need for artificial intelligence (AI) in auto financing.
Inovatec Systems Corp. released its study findings this week that showed 79.3% of C-Suite finance executives polled overwhelmingly reported their organization was most in need of AI integration in their automotive financing processes.
Although Inovatec insisted in a news release that it’s no surprise businesses are increasingly interested in automating processes and utilizing intelligence tools, respondents prioritized AI integration business transformation over cost reduction, process improvement, workflow management, product launch, digitalization and documentation needs.
The survey revealed a glaring need for process automation for financial organizations, especially automotive finance companies.
Approximately 81% of finance companies polled said they are not currently using an online digital origination channel that leverages process automation. However, most participants (36%) said their current system struggles with operational issues, and nearly half (43%) said compliance requirements are also the leading reason why they would consider a process management solution.
When asked what specific challenges they faced in finance processing, 52.6% admitted the process was too complicated and required too many steps. Inovatic noted 23% percent said the process takes too long, and 27.4% said the system was not easy to navigate.
In a separate news release, Top Software Development Companies identified what it contends are the top steps to follow within a software development life cycle. Top Software Development Companies is a firm that analyzes the best software developers from around the world to determine the leading software development firms across all specialties and in all locations.
Those seven steps included:
1. Planning
2. Requirements and analysis
3. Design and prototyping
4. Software development
5. Testing
6. Software deployment
7. Operations and management
“Software development projects are complicated initiatives that require hefty budgets and plenty of time,” the firm said. “Therefore, it is imperative that businesses partner with the best software development agencies who can follow proven processes in order to make software solutions efficient and offer a strong return on investment.”
And Inovatec is looking to be that firm. To obtain a complete picture of the AI situation, Inovatec also surveyed a group of consumers who recently purchased or sold a vehicle and asked about their experience surrounding vehicle financing.
Among the 125 consumers polled, 72% of sellers stated that once a buyer was interested, securing financing took the longest amount of time; followed by transfer of title or paperwork and price agreement.
When asked what their biggest complaint was in financing their last vehicle, 59.2% said the process took a long time from start to finish, and another 21.4% said there were too many steps involved.
“The survey sheds light on the fact that lenders and consumers both recognize the need for more efficient lending processes and procedures in the marketplace,” Inovatec vice president of sales and marketing Bryan Smith said.
“It’s clear that artificial intelligence process integration is a top priority for lenders. The strategic implementation of AI and machine learning tools enables lenders to focus on improving the finance process for each individual customer in a more seamless and accurate fashion.”
Accuracy certainly is paramount to successful accounting at auto finance companies.
And new research from Robert Half Finance & Accounting suggested artificial intelligence (AI) is expected to enhance accuracy even more and bring significant transformation to companies’ accounting and finance functions.
According to 47% of chief financial officers who participated in a Robert Half Finance & Accounting survey, the area expected to benefit most is payroll. More than four in 10 respondents (45%) believe budget and analysis will be impacted, as well.
Increased reliance on technology has had a positive impact on accounting and finance employees, according to 78% of senior financial managers polled for Robert Half’s Jobs and AI Anxiety report. Its influence is also expected to generate a substantial gain in the number of jobs worldwide.
According to the World Economic Forum, intelligent technologies could create a net 58 million new positions by 2022.
Turning back to that Robert Half Finance & Accounting CFO survey, participants also were asked, “What reasons do you think these functions will be most impacted by AI in the next three years?” They were able to give more than one answer, and the results included:
— Eliminates human error: 57%
— Reduces costs: 56%
— Increases employee efficiency and output: 50%
— Reduces burden on finance and accounting professionals so they can focus on higher value work: 49%
— Improves the bottom line: 43%
“AI presents a tremendous opportunity for companies to improve functions by reducing error and boosting efficiency,” said Steve Saah, executive director of Robert Half Finance & Accounting. “Implementing technology to address routine tasks also frees up employees’ time to take on strategic work that adds value to the business.”
Saah added, “Automation can create more opportunities for employees to engage in creative, collaborative, relationship-driven work, which is why we believe in technology as a job creator. As certain positions disappear, more new jobs are expected to surface, as has been the case with all waves of technology advancement over time.”
Robert Half Finance & Accounting offered the following tips for managers to ease worker anxiety around new technology:
— Provide training: Take advantage of new technology by upskilling staff. Investing in professional development increases the department’s strength and the firm’s success.
— Deploy change management: As companies adopt emerging technologies, managers need to communicate to staff what’s being done and what it means for their jobs. Keep morale up by conveying key benefits of digital transformation.
— Offer stretch assignments: Remind workers of their value and leadership potential by engaging their talents in projects that encourage them to learn and build new skills.
The online surveys were developed by Robert Half Finance & Accounting and conducted by independent research firms. The CFO survey includes responses from more than 1,100 CFOs at companies in the United States with 20 or more employees. The survey developed for the Jobs and AI Anxiety report includes responses from 250 accounting and finance managers in the United States.
As the company gears up to host FICO Auto Mastermind 2019 this week, Nick shared his conversations with a pair of FICO experts who were in San Francisco earlier this year for the Vehicle Finance Conference hosted by the American Financial Services Association.
FICO chief analytic officer Scott Zoldi described what clean data really is as FICO vice president of security solutions Doug Clare revisited the ongoing challenge of maintaining cybersecurity.
The full episode can be found below.
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Technology Hyundai is already deploying in South Korea with its financial services enterprises might be a preview of what the OEM eventually brings to the United States.
During IBM Think, Hyundai Card and Hyundai Commercial, financial services subsidiaries of Hyundai and Kia Motors, announced they are working with IBM to advance their use of cloud-based artificial intelligence and blockchain technology with the aim of improving the customer experience and expanding its financial services business globally.
The news was shared on Wednesday during IBM Think 2019, IBM’s annual conference focused on technology and business.
For the first time in the Korean finance industry, Hyundai Card has introduced an AI-based chatbot for customer service. Named “Hyundai Card Buddy,” it can engage with customers to answer common questions quickly while freeing Hyundai professionals to handle more complex customer service needs.
The company said South Korea has some of the highest rates of Internet use than any other country in the world, so Hyundai Card Buddy is a natural way to improve clients’ digital experience. Hyundai Card Buddy has helped 1 million customers since it has launched, according to a news release.
The automaker explained the system continuously learns through interactions with users and by relying on natural language processing and machine learning technology from IBM Watson, Hyundai Card Buddy is able to understand hidden meaning, interpret client questions and provide answers and information to enhance the client experience and streamline customer service operations.
In addition, Hyundai Commercial, a corporate finance company that provides leasing and financial services for commercial vehicles and construction equipment, is collaborating with IBM to apply blockchain and modernize its business model.
Using the open source Hyperledger Fabric to create a new supply chain financing ecosystem for Hyundai Commercial, officials explained the network is designed to reduce lead times and costs in financial transactions among dealers, distributors and manufacturers.
Officials went on to mention the network for commercial financing will provide participants with a single view of all transactions happening in the network while automating manual processes and enabling transaction data to be securely managed and shared more efficiently.
“It’s almost impossible to fully understand or memorize the benefits, limits or conditions of a finance product. Customer services employees’ turnover rate and training cost is very high while the customers demand high quality service. So we introduced IBM Watson and it became a very powerful tool to help our employees and helped us to lower our employee turnover rate to less than 10 percent,” said Ted Chung, chief executive officer of Hyundai Card, Hyundai Capital and Hyundai Commercial.
Andrew Chang, general manager of IBM Korea, also discussed being involved in this technology project. IBM is a world leader in AI software, services and technology for business. IBM has deployed Watson solutions in thousands of engagements with clients across 20 industries and 80 countries.
“Korea enjoys a digital-first financial services industry in which the rapid adoption of technologies such as artificial intelligence, analytics, blockchain and cloud are improving the customer experience and helping expand into new opportunities,” Chang said.
“Working with IBM, Hyundai Card and Hyundai Commercial have pioneered these new technologies and have been a strong innovator in the industry,” Chang went on to say.
GBG, a U.K.-headquartered identity data intelligence specialist, recently announced that it has conditionally agreed to acquire IDology, a U.S.-based provider of identity verification and fraud prevention services.
The company said the all-cash transaction is for $300 million.
IDology is a fast-growing provider of identity verification services that is designed to help remove friction both in onboarding customers and in the detection of fraud. Officials highlighted its U.S. identity verification and fraud prevention services, led by its ExpectID product range, are the perfect strategic complement to GBG’s identity verification solutions.
“For the past 15 years, IDology has provided multi-layered identity verification. With the combination of IDology and GBG, we intend to innovate, delivering exceptional solutions for our customers, focusing on driving customer revenue and preventing fraud,” IDology president and chief executive officer John Dancu said.
“With GBG’s expertise in global data, we are all excited to expand our solutions and our trusted consortium network for customers across the globe,” Dancu continued.
GBG claims it can quickly validate and verify the identity and location of 4.4 billion people globally and accesses a breadth of data from more than 200 global partners to establish trust between businesses and their customers. Having completed 11 acquisitions since 2011, GBG’s $300 million acquisition of IDology is its largest to date.
GBG has seen strong growth in the U.S. market. Its existing U.S. identity business has grown organically with customers across technology, payments and retail verticals. Meanwhile, Loqate, its location intelligence solution, has offices in New York and San Francisco and has seen high demand from household names like Abercrombie and Fitch, Oracle and Nordstrom.
The acquisition will strengthen GBG’s broader portfolio and enhance the business’ product capability and customer reach.
The companies went on to mention GBG and IDology have a history of working together in partnership and share a similar culture with a strong emphasis on people and talent. IDology’s U.S. customer base currently accounts for 99 percent of its revenue, which will provide GBG with geographic scale and help to position GBG as a global leader in electronic identification verification.
“I am delighted to announce the acquisition of IDology. With attractive organic growth, significant synergies and a strong cultural alignment, this is a high-quality addition to GBG,” chief exeutive officer Chris Clark said. “The combination of IDology and GBG enables us to meet growing customer appetite for an identity verification provider with global capabilities and scale in key markets.
“We are excited by the compelling strategic rationale behind this acquisition,” Clark continued. “It enables GBG to quickly expand even further into North America, a key growth territory for the business. We have already built an exciting domestic presence in the U.S. with Loqate, our location proposition, and IDology now gives us an excellent platform for both identity verification and fraud prevention.
“The board and I look forward to the future success that we anticipate that our combined business can deliver,” Clark went on to say.
