InformedIQ CEO Justin Wickett described the ongoing development of artificial intelligence (AI) and machine learning (ML) within the automotive space for this episode of the Auto Remarketing Podcast recorded in Dallas during the Vehicle Finance Conference hosted by the American Financial Services Association.
Wickett also touched on how automotive has set the foundation for the company to explore other parts of the credit market.
To listen to the conversation, click on the link available below.
Download and subscribe to the Auto Remarketing Podcast on iTunes.
Alfa, provider of the asset finance software platform Alfa Systems, recently published the third and final paper in its thought leadership series, “AI in Equipment and Auto Finance.”
The whitepaper titled, “Part 3: Moving Forward with Machine Learning” was produced in association with Alfa iQ, which is a partnership between Alfa and Bitfount.
Bitfount works with some of the world’s leading auto and equipment finance companies to build and deploy machine learning models.
Combining the theoretical insights from Alfa’s position paper, “Balancing Risk and Reward” with the use cases explored in the technical paper, “Using Machine Learning in the Wild,” the company highlighted the new white paper explores the trajectory of machine learning, its uses in auto and equipment finance, and how machine learning will continue to advance in the near future.
The project also includes in-depth exploration of federated learning and how organizations can use private data to train machine-learning models without ever compromising the privacy of that data.
Martyn Tamerlane, author of “Moving Forward” and a solution architect at Alfa said: “AI and ML represent an exciting shift for finance providers and, while the benefits are better understood now than they were a couple of years ago, the practical side to acquiring those benefits is still unclear for many.
“Alfa’s aim for this series has been to expose that practical side; to demonstrate where ML can help solve problems and make lenders more competitive, through its ability to detect patterns in vast amounts of data and feed that into higher-quality, sometimes fully automated, decision making. Then, to show ML taking different forms; first as an in-house framework, and secondly relying on AI-as-a-Service,” Tamerlane continued.
“Now we consider ML's continued success, particularly in the context of the ever-increasing volume and variety of data that is being collected; but with complex challenges posed by data privacy, fairness and the high level of expertise required to analyze the data effectively. By illuminating the key characteristics of this technology, we’re providing a platform from which people can effect major change,” Tamerlane went on to say.
The series can be downloaded at alfasystems.com/ai3.
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.”
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.
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.
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.
A recent survey conducted by TD Bank showed treasury and finance professionals anticipate more operational challenges in 2019 than in previous years.
And a separate analysis distributed by Frost & Sullivan highlighted that technologies such as machine learning, big data and blockchain will become prominent, especially as cybercrime becomes more sophisticated and even a method of warfare.
According to an endeavor orchestrated by TD Bank during the 2018 Association for Financial Professionals annual conference in Chicago late last year, the risk of payments fraud and cybersecurity topped professionals’ list of concerns with 44 percent naming it their top operational challenge. That response level presented a 14 percent year-over-year increase.
TD Bank found the ability to adapt to or process faster or electronic payments is an obstacle for 37 percent of survey respondents, also rising 14 percent year-over-year. The bank acknowledged this concern is likely to cause some anxiety for finance professionals, as commercial payments continue evolving.
In fact, the majority (60 percent) of respondents expect to see the largest amount of growth this year within faster or real-time processing, an 8 percent increase from last year.
Despite industry uncertainties, blockchain has benefits
Unsurprisingly, the TD Bank findings showed that technology continues to influence treasury operations, and the majority of survey respondents (90 percent) feel that blockchain/distributed ledger technology will have some type of positive effect on the payments industry.
The top impact of blockchain/distributed ledger technology is its ability to create stronger audit trails (29 percent), respondents said. Additional positive outcomes include:
— Speeding up the payments process (22 percent)
— Improving efficiency of cross-border payments (21 percent)
— Reducing payments fraud (18 percent)
“Blockchain technology has broad implications for the commercial payments space, from speeding up settlements to securing cross-border transactions,” said Rick Burke, head of corporate products and services at TD Bank.
“Even though much of the industry has a baseline understanding that blockchain can evolve and improve payments, the varied responses indicate that the technology’s specific capabilities and implications are still a great unknown for many finance professionals,” Burke continued.
Despite the hype around new innovations like blockchain, TD Bank found that finance professionals appear to be split on the use of another technology type to facilitate payments: open APIs.
Survey results showed 50 percent of respondents claim that their organization currently uses or is in the process of integrating open APIs into company operations, while 49 percent do not use open APIs, and nearly a quarter of that group does not have plans to do so in the future.
With so much change on the horizon, TD Bank’s survey uncovered that companies are investing in training strategies for several facets of treasury operations. Survey respondents said their organization has training strategies specifically for data and analytics (45 percent), AI and automation (26 percent) and blockchain (14 percent).
Fraud casts a larger cloud
As the risk of payments fraud and cybersecurity threats is top of mind across the industry, TD Bank learned that there comes an expectation from 98 percent of respondents that financial institutions should assist organizations with protecting against fraud and cybercrime.
More than half (55 percent) said financial institutions can help them better protect against fraud and cybercrime through education — although 48 percent of respondents admitted that their company does not have any in-house cyber fraud prevention training.
Additionally, TD Bank said one in four finance professionals surveyed feel that banks should offer greater controls on transactions, and 18 percent state they want risk or process reviews.
“As global fraud and cybersecurity incidents continue to rise, corporations recognize the need to bolster their protective measures and improve employee understanding of how to safeguard finances,” Burke said.
“To achieve real success, organizations and their employees need to be better able to identify and deter fraud attempts. This should be a responsibility shared by businesses and their financial institutions, beginning with better education,” he went on to say.
TD Bank polled finance professionals at the 2018 AFP Conference held last November in Chicago. A total of 406 responses were collected from industry professionals, including business end-users and financial and technology services organizations.
More discussion about machine learning and blockchain
Experts at Frost & Sullivan highlighted that machine learning aids early detection of anomalies, while blockchain creates a trustworthy network between endpoints,
The firm also pointed out the rise of the Internet of Things (IoT) has opened up numerous points of vulnerabilities, compelling cybersecurity companies, especially startups, to develop innovative solutions to protect enterprises from emerging threats.
“Deploying big data solutions is essential for companies to expand the scope of cybersecurity solutions beyond detection and mitigation of threats,” Hiten Shah, a research analyst at TechVision, said in the Frost & Sullivan report available here.
“This technology can proactively predict breaches before they happen, as well as uncover patterns from past incidents to support policy decisions,” Shah continued.
Frost & Sullivan’s recent analysis titled, “Envisioning the Next-Generation Cybersecurity Practices,” presents an overview of cybersecurity in enterprises and analyzes the drivers and challenges to the adoption of best practices in cybersecurity. It also covers the technologies impacting the future of cybersecurity and the main purchase factors.
“Startups need to make their products integrable with existing products and solutions as well as bundle their solutions with market-leading solutions from well-established companies,” Shah said. “Such collaborations will lead to mergers and acquisitions, ultimately enabling companies to provide more advanced solutions.”
Frost & Sullivan explained that technologies that are likely to find the most application opportunities include:
— Big data: It can enable automated risk management and predictive analytics. Experts think its adoption will be mostly driven by the need to identify usage and behavioral patterns to help security operations spot anomalies.
— Machine learning: It can allow security teams to prioritize corrective actions and automate real-time analysis of multiple variables. Using the vast pools of data collected by companies, machine learning algorithms can zero in on the root cause of the attack and fix detected anomalies in the network.
— Blockchain: The data stored on blockchain cannot be manipulated or erased by design. Experts explained the tractability of activities performed on blockchain is integral to establishing a trustworthy network between endpoints. Furthermore, the decentralized nature of blockchain greatly increases the cost of breaching blockchain-based networks, which can discourage hackers.
Deloitte focused on three new technologies in an annual report that highlights on the latest trends that experts described as creating a climate of disruption and uncertainty.
The report titled, “Tech Trends 2019: Beyond the digital frontier,” explored how the convergence of new technologies with powerful forces is driving disruption across industries. According to a recap shared on Wednesday, those new technologies include advanced networking, serverless computing and intelligent interfaces as well as technological forces encompassing digital experiences, cognitive and cloud.
Back 10 years ago, when smartphones and mobile apps were gaining traction, and technologies like cloud and the Internet of Things were emerging on the scene, Deloitte released its first Tech Trends report. The organization has watched this evolution unfold as the digital imperative and the changing role of technology redefine the enterprise, yet adoption of these trends continues to vary widely.
Experts noted that some companies are only beginning to explore trends Deloitte wrote about in 2010, while others have advanced rapidly along the maturity curve.
“Make no mistake: Technology is not just an enabling function. Tech is the universal language of business today,” said Bill Briggs, global and U.S. chief technology officer for Deloitte Consulting.
“As the pace of change quickens, technology now leads business strategy. And technology trends has evolved from a CIO (chief information officer) and CTO (chief technology officer) concern into something driving CEO, management team, boardroom agendas — to redefine what enterprises can accomplish,” Briggs continued.
Authors recapped that “Tech Trends 2019: Beyond the digital frontier,” begins with a reflection on a decade of disruptive change driven by nine macro forces: digital experience, analytics, cloud, core modernization, cyber, business of information technology, cognitive, blockchain, and digital reality. The report further explores where these forces are headed.
Next, six trends that are giving rise to new operating models, redefining the nature of work and dramatically changing IT’s relationship with the business are detailed, including:
— AI-fueled organizations: Leading companies are systematically deploying rapidly maturing technologies — machine learning, natural language processing, robotic process automation (RPA) and cognitive — not just to every core business process, but into products, services and the future of industries. Deloitte believes organizations’ use of artificial intelligence is moving from “Why?” to “Why not?”
— NoOps in a serverless world: Experts asserted we’ve reached the next stage in the evolution of cloud computing with technical resources completely abstracted and management tasks increasingly automated. Freed from mundane responsibilities, the report noted IT talent can focus on activities that more directly support business outcomes.
— Connectivity of tomorrow: At both macro and micro levels, Deloitte explained technologies like 5G, mesh networks and edge computing are expanding business’ reach to both the far corners of the world — and the smallest spaces in warehouses, retail stores and other places with utmost precision. Experts contend that advanced networking is the “unsung hero,” driving development of new products and services and is transforming how work gets done.
—Intelligent interfaces: Today, Deloitte pointed out that people interact with technology through ever more intelligent interfaces that combine the latest in human-centered design techniques with leading-edge technologies such as computer vision, conversational voice, auditory analytics, augmented reality and virtual reality. Working in concert, experts see these technologies and techniques are transforming the way we engage with machines, data and each other.
— Beyond marketing with a reimagined experience: To deliver the highly personalized, contextualized experiences that today’s customers expect, Deloitte mentioned that some chief marketing officers are trading long-standing, traditional agency relationships for closer partnerships with their own CIOs. Enabled by a new generation of marketing tools and techniques focused on personalized, contextual and dynamic experiences, experts indicated that CIOs and CMOs can illuminate and engage customer needs and desires most effectively.
— DevSecOps and the cyber imperative: Deloitte explained that DevSecOps fundamentally can transform cyber, security, privacy and risk management from being compliance-based activities — typically undertaken late in the development lifecycle — into essential framing mindsets across the product journey.
The report closes by exploring how modern businesses can navigate digital transformation — building a roadmap that incorporates the right technologies, techniques, talent and executive support.
“While we take a pragmatic view, we also aspire to understand fully how forces like serverless technology, connectivity capabilities, and intelligent interfaces are reshaping industries,” said Scott Buchholz, managing director and government and public services chief technology officer at Deloitte Consulting.
“The report details how organizational leadership can shape ambitions and instill a culture to sense and make sense of what tomorrow may bring. And – importantly – a path to get there from the realities of today,” Buchholz went on to say.
The entire report can be downloaded here.
FICO recently learned its collection of patents grew by five.
Federal officials recently awarded five new patents to the Silicon Valley analytic software firm related to fraud, artificial intelligence (AI) and advanced analytics. In total, FICO currently holds 192 U.S. and foreign patents, and the company has 93 pending patent applications.
Two of the patents are connected to analytic technology used by the FICO Falcon Platform for fraud management:
• Detection of Compromise of Merchants, ATMS and Networks relates to the generation of compromise profiles for financial accounts based on reported fraud data of a payment account and merchant device. These compromise profiles accelerate detection of fraud.
• Card Fraud Detection Utilizing Real-Time Identification of Merchant Test Sites covers a system and method for detecting when criminals are “testing” compromised cards, by using real-time merchant profiles and specialized scoring models.
FICO inventors also received three patents related to analytics and decision management:
• Efficiently Representing Complex Score Models can transform predictive models into a software program for deployment in a rules engine, helping IT departments solve the problem of operationalizing analytics. This technology is integrated in FICO Blaze Advisor decision rules management system, part of the FICO Decision Management Suite.
• Automatic Modeling Farmer covers an AI system that automatically can develop and evaluate a large number of possible predictive models in order to produce optimal models. This is a streamlined modeling process to enable quick development of large-scale models using Big Data, and is used by FICO data scientists to identify candidate data sources with the most predictive promise.
• Systems and Methods to Improve Decision Management Project Testing is an invention that can visualize the validation status of components of an executable decision management project, which improves project testing. This technology is integrated in FICO Origination Manager.
“This is an exciting time for analytics and decision management, and FICO’s inventions are propelling change in this field,” said Stuart Wells, FICO’s chief product and technology officer. “Our data scientists continue to be at the forefront of the AI revolution and the progress in intelligent decision automation.”
Another client-service provider relationship has evolved into one of executive teammates.
TruDecision, a fintech company providing sophisticated applications of artificial intelligence, machine learning and other quantitative tools to dealers and finance companies, has named Joel Kennedy its chief operating officer.
Monday’s development involved Kennedy as the latest addition to the TruDecision executive team. He brings more than 21 years of executive experience in auto lending operations, technology and compliance.
“Today, lenders are inundated with analytic solutions gratuitously labeled as AI. The vast majority of these solutions are built by people who have never worked in auto lending,” said Daniel Parry, chief executive officer of TruDecision. “Decision tools can have very negative consequences when designed without a contextual understanding of the business.
“Our lender customers want to know not only that we have the sophistication to develop top-tier solutions, but that we have also had to live with the results of tools we create as managers and business owners. This is why Joel Kennedy is such a powerful addition to our team,” Parry continued.
“His extensive background will help TruDecision bridge the gap between analytics and the quantifiable results lenders demand,” Parry went on to say.
Kennedy was a co-founder and original investor in Pelican Auto Finance, and as a senior executive helped to grow the company from a startup to more than $100 million in auto receivables. Formerly, he served in senior leadership positions at ACC Consumer Finance, Wells Fargo, Capital One and General Electric.
During his more than two decades in the industry, Kennedy has been integrally involved in the origination of more than $6 billion in auto receivables.
Kennedy is presently a board member of the National Automotive Finance Association. And along with being a guest contributor to Auto Fin Journal, Kennedy is also a part of the collection of experts and executives set to speak during Used Car Week 2018, which begins on Nov. 12 in Scottsdale, Ariz.
And Kennedy will come to the industry’s leading event as COO of TruDecision.
“I have worked with Daniel Parry for years as a lender peer, and also as his client,” Kennedy said. “I have seen first-hand how powerful analytics combined with a real-world understanding of auto lending can transform business operations. I am very excited to join this team and help TruDecision continue to drive bottom line results for their clients.”
