Podcasts about decisioning

Hear from Terisa Roberts, Global Head of Risk Modeling and Decisioning at SAS and Sarah Murphy, Principal Director of Accenture Data and AI, as we explore real-time customer decision making and what it means for portfolio monitoring. Thanks to the internet and artificial intelligence, consumers today can make financial decisions through multiple channels, resulting in a new level of competitive pressure for the sector. Financial services firms must make decisions that are not only fast and reliable, but also automated. Real-time customer decisioning plays a pivotal role in achieving these goals throughout the credit value chain, from the point of onboarding (including KYC, credit risk and fraud assessments and marketing) and beyond. Today's episode will focus on: What are the global trends driving change in customer decisioning in financial services? What problems/challenges are there with conventional approaches? What are the benefits of modernizing your credit decisioning infrastructure? How are forward-thinking organizations deriving concrete business value from their decisioning modernization projects? Links from today's discussion: SAS and Accenture Risk Model Decisioning Risk-Based Decisioning in an Age of Uncertainty Part 1 Risk-Based Decisioning in an Age of Uncertainty Part 2 Speakers Bios: Terisa Roberts Global Head of Risk Modeling and Decisioning, SAS Terisa Roberts is a risk management professional with 15 years of experience primarily in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. Terisa has an extensive background in risk modeling for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks other financial services providers and regulators concerning innovations in Risk Modeling and Decisioning including artificial intelligence and machine learning. Teresa holds a Ph.D. in Operations Research and Informatics and lives in Sydney Australia   Sarah Murphy, Principal Director, Accenture Data and AI As a Principal Director at Accenture, Sarah leads the growth of Intelligent Decisioning within the Applied Intelligence practice, leveraging 25+ years of risk management and operational experience in financial services and global consulting. ​  Sarah has a proven track record of solving complex risk issues across the credit customer lifecycle, applying predictive analytics and decision management to transform business culture, minimize exposure, increase profitability, and create risk management centers of excellence. She also has a strong executive presence and excellent communication skills, enabling her to partner with clients and stakeholders at all levels and deliver value-added solutions. ​ Passionate about staying at the forefront of the latest trends and technologies in intelligent decisioning, her mission is to help organizations harness the power of data and analytics to optimize their decision making, enhance their customer experience, and achieve their strategic goals.    Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   About SAS SAS is a global leader in data and AI. We help organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. No matter how you prioritize risk, SAS has proven solutions and best practices to help organizations establish a risk-aware culture, optimize capital and liquidity, and meet regulatory demands. SAS® provides on-demand, high-performance risk analytics to ensure greater efficiency and transparency. Strike the right balance between short- and long-term strategies. And confidently address changing regulations and manage compliance.  Discover why 90% of Fortune 100 companies choose SAS to solve their toughest challenges at sas.com/riskmanagement.

Today, we're joined by Peter van der Putten, director of the AI Lab at Pega and assistant professor of AI at Leiden University. We discuss the newly adopted European AI Act and the challenges of applying academic fairness metrics in real-world AI applications. We dig into the key ethical principles behind the Act, its broad definition of AI, and how it categorizes various AI risks. We also discuss the practical challenges of implementing fairness and bias metrics in real-world scenarios, and the importance of a risk-based approach in regulating AI systems. Finally, we cover how the EU AI Act might influence global practices, similar to the GDPR's effect on data privacy, and explore strategies for closing bias gaps in real-world automated decision-making. The complete show notes for this episode can be found at https://twimlai.com/go/699.

Thinking about running a new event? Let's make sure you're headed in the right direction from the start! The choices you make early on can set the stage for success or create hurdles down the line. This mini-series and the accompanying Behind The Results™ Event Guide will help set you off on the right foot - Download it here: katerubyaroha.com/eventguide[TIME SENSITIVE OFFER] Get 12 months of leadership mentoring with me in the Leaders Impact program, for just $77 per month! Down from $3850, as this is the last time this program will be run --> katerubyaroha.com/leaderInstagram: www.instagram.com/katerubyarohaWebsite: https://www.katerubyaroha.com

At the start of summer last year, we had a really inspiring conversation with Christopher Paquette and are excited to reshare it this year, in our “Best Of” series. Originally published 06/29/23.Tasked with accelerating digital transformation at Allstate, Christopher Paquette recognizes the digital potential embedded everywhere. Reflecting on his first year as Chief Digital Transformation Officer at Allstate, Christopher shares essential lessons in collaboration, creating value for the customer, and transformation strategy. In this episode, Christopher discusses focus areas of connectivity, automation, decisioning, and pattern recognition. He gives examples of analysis indicators and the various speeds of digital transformation. Christopher dives into the idea of influence when your discipline is not siloed and discusses his passion for community building through music and music education.(01:42) – Introducing Christopher Paquette(03:21) – Digital transformation(07:04) – Decisioning(09:11) – Relationship building and collaboration(13:34) – Influence (18:10) – Outcomes and determining the “why”(21:51) – Indicators: starts, containment, and satisfaction(24:40) – Beginning a role in Q2(26:01) – Dedication to music and The People's Music SchoolChristopher Paquette is the Chief Digital Transformation Officer at Allstate. Previously, Christopher served as a Partner at McKinsey & Company for twelve years. His over two-decade career has orbited strategy, digital, and analytics. Christopher earned an MBA from the Kellogg School of Management at Northwestern University.If you'd like to receive new episodes as they're published, please subscribe to Innovation and the Digital Enterprise in Apple Podcasts, Google Podcasts, Spotify, or wherever you get your podcasts. If you enjoyed this episode, please consider leaving a review in Apple Podcasts. It really helps others find the show.Podcast episode production by Dante32.

Kathy Stares, EVP of North America for Provenir talks about AI-powered risk decisioning software, processing more than four billion transactions annually for disruptive financial services organizations in more than 50 countries worldwide.01:14 Meet Kathy Stares04:34 The Start of Summer08:01 AI Powered Risk Decisioning11:31 The Tech Behind Povenir13:42 Models14:32 Data Source16:43 The Business Problem17:33 Banking Strategies18:48 The Extent of the Platform20:28 Automation21:46 Provenir Differentiation 22:47 Millennials and GenZs?29:05 Trends in the Future31:57 The Takeaway33:28 Reaching Provenir35:25 The Wealthy BarberLinkedIn: linkedin.com/in/kathy-mitchell-stares-8150159Website: https://www.provenir.comWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Kathy Stares, EVP of North America for Provenir talks about AI-powered risk decisioning software, processing more than four billion transactions annually for disruptive financial services organizations in more than 50 countries worldwide.01:14 Meet Kathy Stares04:34 The Start of Summer08:01 AI Powered Risk Decisioning11:31 The Tech Behind Povenir13:42 Models14:32 Data Source16:43 The Business Problem17:33 Banking Strategies18:48 The Extent of the Platform20:28 Automation21:46 Provenir Differentiation 22:47 Millennials and GenZs?29:05 Trends in the Future31:57 The Takeaway33:28 Reaching Provenir35:25 The Wealthy BarberLinkedIn: linkedin.com/in/kathy-mitchell-stares-8150159Website: https://www.provenir.comWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this #DataTalk episode, Keith Little, MD Analytics, Decisioning and Platforms at Experian Software Solutions, unveils the game-changing enhancements to Experian's Ascend Technology Platform™. Keith discusses how client feedback has shaped a solution that streamlines operations, automates processes, and strengthens fraud detection in today's fast-paced business landscape. Join us to discover how Ascend empowers businesses with seamless integration, personalized experiences, and top-notch security measures, setting a new standard for success. Keith Little is a seasoned technology executive with a global purview, currently spearheading Experian's Ascend Technology Platform and Decisioning suite (Powercurve) software products. He began his tenure at Experian in November 2022 with the role of Chief Technology Officer for Global Decision Analytics (GDA) and subsequently expanding his responsibilities to encompass the Decisioning products during the transition to Experian Software Solutions (ESS). Before joining Experian, Keith held various high-profile positions, including Chief Information Officer at Barclays, where he oversaw the Barclaycard credit business, Payments businesses, and Fraud technologies. Prior to that, he was involved in a startup leveraging artificial intelligence for online behavioral advertising. Keith's illustrious career also includes roles at BT, the BBC, and as a founder and non-executive director of www.worldgallery.co.uk. He holds a Bachelor's degree in Computer Science and a Postgraduate degree in Image and Video Compression from Kingston University. Additionally, he spent nine years as a non-executive director at Kings College London, demonstrating his commitment to both academia and industry advancement.

In today's rapidly evolving financial landscape, it is more important than ever for financial institutions to stay ahead of the curve and offer tailored products and services that meet the unique needs of their customers. In this webinar, we discuss how financial services institutions are overcoming the challenges presented by traditional architectures, adopting AI and leveraging the independent software vendors (ISV) ecosystem.By considering a holistic unified customer view, companies are able to look at customer insights across a number of dimensions. There are ways and means to create this view, and this session will explore creating that capability, faster.

Saturday, May 21, 2022 It's decision time! In this special episode we debate which three detective movies we're gonna watch during the live event on July 1st! Everybody put July 1st in your calendars for the live event! 0:00 -- Pre-lim live event chatter4:23 -- Andy's decisioning8:00 -- Josh's decisioning11:27 -- Mark's decisioning13:33 -- Ammon's decisioning23:31 -- Brooke's decisioning24:17 -- Katie's decisioning28:17 -- J.B.'s decisioning32:04 -- Detective cred40:45 -- Sorting 43:10 -- Lobbyvoting1.01:49 -- Outro Hey! Leave us a voicemail at (801) 896-4542!Hey! We're on Spotify now!Hey! Watch Sleuth on YouTube!Hey! Hear our Murder by Death podcast on JRWSTFTFT!Hey! Subscribe in iTunes!Hey! Check out the Facebook page and vote on the next category!Hey! Check out Jon's YM&T Letterboxd list!Hey! Check out Roy's YM&T Letterboxd list!Hey! Email us at yoursminetheirspodcast@gmail.com! Send new topics! Send new theme songs!

In this episode, Hiten Patel and his co-host Cosimo Schiavone are joined by Silvio Tavares, the CEO of VantageScore, a national credit scoring company. Silvio shares his personal journey and the challenges his family faced as immigrants in the United States. He also discusses the role of VantageScore in the credit scoring industry and the importance of financial inclusion. Silvio highlights the need for innovation and the incorporation of alternative data in credit decisions. He also shares his insights on the future of data usage and the importance of creating value for multiple stakeholders.

In this episode, Hiten Patel and his co-host Cosimo Schiavone are joined by Silvio Tavares, the CEO of VantageScore, a national credit scoring company. Silvio shares his personal journey and the challenges his family faced as immigrants in the United States. He also discusses the role of VantageScore in the credit scoring industry and the importance of financial inclusion. Silvio highlights the need for innovation and the incorporation of alternative data in credit decisions. He also shares his insights on the future of data usage and the importance of creating value for multiple stakeholders.

In this podcast Zeynep Salman, Head of Risk Decisioning, EMEA at SAS, will explore the top trends and market practices for financial institutions as they adapt to digitizing credit decisioning. We will dive deeply into key success factors for establishing innovative credit customer journeys while achieving successful business outcomes that keep the lending business profitable. We will also discuss how a country's regulatory requirements and market dynamics can affect the transformation journey. Link from today's discussion can be found here: The Value of Credit Risk Transformations and the Role of AI   Speaker's  Bio Zeynep Salman is a credit risk professional with experience managing originations, customer management, and collections teams for consumer and small business portfolios. She joined SAS in 2022 and is currently leading risk decisioning advisory activities across EMEA. Zeynep is passionate about driving automation, seamless customer experiences, convergence of credit and fraud evaluations across customer lifecycle, AI-driven customer engagements, and working with clients to support near and long-term strategic roadmaps to drive value. Before joining SAS, Zeynep held key roles at financial institutions including Citibank, HSBC, Toyota Finance, and UniCredit, as well as software vendors such as FICO.   -----------------------   Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   About SAS As a leader in analytics, SAS' award-winning capabilities in analytics, risk management, and other technology areas have helped customers across the globe solve their toughest and ever-evolving business problems. Its unrelenting commitment to innovation enables organizations across financial services to modernize and sustain a competitive edge. Through the latest developments in machine learning, natural language processing, forecasting, and optimization, SAS supports diverse environments and scales to meet changing needs. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk

Is it possible for financial institutions to offer on-demand, superior customer experiences while making risk decisions in near real-time in an increasingly digital and interconnected world? That is the question we'll explore in this podcast featuring Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning at SAS, and Bruce Erb, Director – Credit Risk Consulting, KPMG. Traditional financial institutions are encountering additional hurdles, including fierce competition from agile newcomers, new regulatory demands for operational resiliency, and increased technology risk. In an age of digital lending driven by artificial intelligence, what are modern financial institutions doing differently to remain agile and profitable while keeping costs in check? We'll delve into several strategies that financial institutions are adopting for risk-based decision-making to bolster their resilience in times of uncertainty.   Speakers   Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning, SAS Terisa Roberts is a risk management professional with 15 years of experience primarily in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. Terisa has an extensive background in risk modeling for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks, other financial services providers, and regulators concerning innovations in Risk Modeling and Decisioning including artificial intelligence and machine learning. Teresa holds a Ph.D. in Operations Research and Informatics and lives in Sydney, Australia.   Bruce Erb, Director – Credit Risk Consulting, KPMG Bruce Erb has been a risk professional for over 23 years in both industry and consulting. At KPMG, he has supported financial services clients in a variety of risk programs and initiatives with a current focus on transformation of credit and risk governance operating and execution models leveraging alternative approaches including automation, advanced analytics, and cognitive technologies.    Bruce was the product owner and co-inventor of an audit investigation tool that leveraged digitization, automation, and cognitive components to augment the way risk professionals evaluate and score a commercial loan. He was a loan officer for more than nine years before joining KPMG.   -----------------------   Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   About SAS As a leader in analytics, SAS' award-winning capabilities in analytics, risk management, and other technology areas have helped customers across the globe solve their toughest and ever-evolving business problems. Its unrelenting commitment to innovation enables organizations across financial services to modernize and sustain a competitive edge. Through the latest developments in machine learning, natural language processing, forecasting, and optimization, SAS supports diverse environments and scales to meet changing needs. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk

Tasked with accelerating digital transformation at Allstate, Christopher Paquette recognizes the digital potential embedded everywhere. Reflecting on his first year as Chief Digital Transformation Officer at Allstate, Christopher shares essential lessons in collaboration, creating value for the customer, and transformation strategy. In this episode, Christopher discusses focus areas of connectivity, automation, decisioning, and pattern recognition. He gives examples of analysis indicators and the various speeds of digital transformation. Christopher dives into the idea of influence when your discipline is not siloed and discusses his passion for community building through music and music education.(01:42) – Introducing Christopher Paquette(03:21) – Digital transformation(07:04) – Decisioning(09:11) – Relationship building and collaboration(13:34) – Influence (18:10) – Outcomes and determining the “why”(21:51) – Indicators: starts, containment, and satisfaction(24:40) – Beginning a role in Q2(26:01) – Dedication to music and The People's Music SchoolChristopher Paquette is the Chief Digital Transformation Officer at Allstate. Previously, Christopher served as a Partner at McKinsey & Company for twelve years. His over two-decade career has orbited strategy, digital, and analytics. Christopher earned an MBA from the Kellogg School of Management at Northwestern University.If you'd like to receive new episodes as they're published, please subscribe to Innovation and the Digital Enterprise in Apple Podcasts, Google Podcasts, Spotify or wherever you get your podcasts. If you enjoyed this episode, please consider leaving a review in Apple Podcasts. It really helps others find the show.Podcast episode production by Dante32.

It's decision time! In this special episode we debate vote upon which three detective afterlife movies we're gonna watch during the live event on July 1st 8th! Everybody put July 1st 8th in your calendars for the live event!0:00 -- List of contenders and other2:28 -- Michael's decisioning3:02 -- Miriam's decisioning4:00 -- Sean's decisioning4:25 -- Brooke's decisioning6:03 -- Dale's decisioning7:09 -- Josh's decisioning8:35 -- Marie's decisioning10:15 -- J.B.'s decisioning11:30 -- Ammon's decisioning14:10 -- Katie's decisioning16:40 -- Andy's decisioning19:58 -- Zo's decisioning21:34 -- Richard's decisioning23:10 -- Christel's decisioning25:53 -- Mark's decisioning31:35 -- Anthony's decisioning32:48 -- Kjirsten's decisioning33:40 -- Garrett's decisioning33:55 -- Subtotalling34:30 -- Announcementing35:26 -- Jon's decisioning36:13 -- Roy's decisioning36:30 -- Detail reiterating38:25 -- Outro and outtakesHey! Leave us a voicemail at (801) 896-4542!Hey! We're on Spotify now!Hey! Subscribe in iTunes!Hey! Check out the Facebook page and vote on the next category!Hey! Check out Jon's YM&T Letterboxd list!Hey! Check out Roy's YM&T Letterboxd list!Hey! Email us at yoursminetheirspodcast@gmail.com! Send new topics! Send new theme songs!Download this episode right here!

This recording is from Fintech Nexus USA held at the Javits Center in New York City on May 10-11, 2023.Session: "Fast, Flexible, Functional: Smart growth decisioning for fintechs " from the Consumer Lending: Personal Loans, Cards and BNPL track - Sponsored by ExperianFeaturing:Steve Eichenlaub, ExperianTo receive updates about the 2024 Fintech Nexus USA event, join our LinkedIn event here:  https://www.linkedin.com/events/fintechnexususa20247063890713540734977/

In episode 60 of the Get Hired Up podcast, our host, Maureen Farmer joins the podcast as a guest while the producer, Maddie Shears, interviews her on employee turnover versus employee retention. Maureen shares fast tips for individuals looking to leave their current organization as well as companies looking to keep their employees. This episode shares two sides of the coin on career decisioning for leaders. We hope you enjoy the show!Westgate Executive BrandingOur Main Event!Listen on SpotifyListen on Apple Podcasts 

In this episode of Leaders of Analytics, I am joined by Ada Guan who is one of the most innovative minds in the field of credit decisioning. Ada is CEO and co-founder of Rich Data Co, a company that helps lenders make informed and accurate credit decisions by leveraging AI and machine learning. Listen in as Ada sheds light on the role that AI and machine learning can play in transforming the lending industry and what the future may hold for credit decisioning. In this episode, we'll discuss: Ada's entrepreneurial journey The typical pain points lenders face and how RDC's unique AI solution solves these problems What makes RDC's solution unique and why banks should buy rather than build themselves How to find product-market fit or an AI product The additional benefits an AI solution brings over traditional credit scorecards or rules-based decisioning engines, and much more. Learn more about Rich Data Co here: https://www.richdataco.com/ Connect with Ada Guan on LinkedIn.

In this episode of Leaders of Analytics, I am joined by Ada Guan who is one of the most innovative minds in the field of credit decisioning. Ada is CEO and co-founder of Rich Data Co, a company that helps lenders make informed and accurate credit decisions by leveraging AI and machine learning. Listen in as Ada sheds light on the role that AI and machine learning can play in transforming the lending industry and what the future may hold for credit decisioning. In this episode, we'll discuss: Ada's entrepreneurial journey The typical pain points lenders face and how RDC's unique AI solution solves these problems What makes RDC's solution unique and why banks should buy rather than build themselves How to find product-market fit or an AI product The additional benefits an AI solution brings over traditional credit scorecards or rules-based decisioning engines, and much more. Learn more about Rich Data Co here: https://www.richdataco.com/ Connect with Ada Guan on LinkedIn.

Unternehmen brauchen Daten! Und davon richtig viele! Acxiom ist ein Unternehmen, welches diese Daten sammelt und als Data Provider für Marketeers zur Verfügung stellt, sowie zu Data-Systemen berät. In dieser Folge von MY DATA IS BETTER THAN YOURS spricht der Host Jonas Rashedi mit Eric Heiliger, der sich bei Acxiom um das Thema Strategic Growth kümmert. Doch warum brauchen sowohl etablierte Marken als auch Start ups externe Daten? Historisch gesehen gab es in den 80ern die ersten Daten-Allianzen (wovon Acxiom schon damals ein Teil war). Denn die damaligen Versandhäuser haben gemerkt: Das Marketing ist effizienter, wenn Daten genutzt werden! Heute sind Daten für das Marketing unerlässlich geworden, um Kund:innen anzusprechen. Acxiom nutzt dafür winzige Kohorten und hat alleine in Deutschland durch die Datenlogik 5-7 Millionen unterschiedliche Kohorten. Eric erzählt dabei auch von Use Cases für die Daten von Acxiom und erklärt am Beispiel eines Automobilherstellers, dass manchmal auch auf die falschen KPIs geschaut wird. In dem Zusammenhang spricht Jonas auch von seinem Modell der Datennutzung: Collect, Understand, Decide, Automate und Execute, wobei der letzte Schritt bedeutet, sich komplett auf Daten zu verlassen. Eric vergleicht dies mit seinen „4 D's“ – Data Foundation, Decisioning, Design und Distribute. Spannend ist dabei auch, dass Eric die Data Economy und somit die Art, wie Menschen Daten preisgeben, unterteilt in 3 Bereiche: Datenpragmatisten, welche pragmatisch Daten preisgeben, um an Informationen zu gelangen, Fundamentalisten, die gar keine Daten von sich preisgeben und Unconcerned, die alles preisgeben ohne darüber nachzudenken. Zum Schluss geht es noch darum, wie die Data-Welt in 5 Jahren aussieht! MY DATA IS BETTER THAN YOURS ist ein Projekt von BETTER THAN YOURS, der Marke für richtig gute Podcasts. Zum LinkedIn-Profil von Eric: https://www.linkedin.com/in/eric-heiliger1/ Zur Webseite von Acxiom: https://www.acxiom.com/ Zu allen wichtigen Links rund um Jonas und den Podcast: https://linktr.ee/jonas.rashedi Dieser Podcast wurde mit freundlicher Unterstützung von Acxiom erstellt.

On today's episode I had the pleasure of speaking with not one, but two Co-founders Laura Spiekerman, President & Co-founder at Alloy. As well as Charles Hearn, who is the CTO & Co-Founder at Alloy. On this episode we discuss a variety of topics from product evolution to trends as well as the recent emergence of Reg-Tech in Fintech. Enjoy! Learn more about Alloy (https://www.alloy.com/). Also check out a recently published blog on how Alloy built on AWS here. https://aws.amazon.com/blogs/startups/alloys-global-identity-decisioning-platform-built-on-aws/ You can also learn more about Fintechs and Startups on AWS (https://aws.amazon.com/startups/ or https://aws.amazon.com/startups/FinTech/)

Listen to our interview with Terisa Roberts and Stephen Tonna Terisa is the Director, Global Lead in Risk Modeling and Decisioning at SAS and Stephen is a AI and Modeling Lead at SAS. Their  book considers how Technologies driven by machine learning and AI have transformed industries and help evaluate and solve risk management problems. You can purchase the book via the link below  Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning, published by Wiley as part of the SAS Business Series. Please read the introduction excerpt, available for complimentary download. We discussed the following topics among others.  How can AI and ML help risk practitioners? What are the strengths and weaknesses of AI and ML and clarify the main misconceptions that you have both experienced? Who is responsible and accountable for governing AI and ML models? How AI and machine learning can be effectively applied to everyday risk management problems? How should firms approach balancing business benefit with the newer risks created by use of AI/ML? What are the new opportunities for AI/ML in Risk in the short and medium term? and more... If you want to be our guest, or you know some one who would be a great guest on our show, just send your email to info@globalriskconsult.com with a subject line “Global Risk Community Show” and give a brief explanation of what topic you would like to to talk about and we will be in touch with you asap.

Bias may present itself in a variety of ways within lending. When assessing biases, two issues frequently arise: Was someone treated differently because of who they are? Or did a sincere goal activity end as being harmful to one group? A recent wave of technological innovation has enabled lenders to better comprehend how distinct subpopulations might perform differently than the kind of borrower they're used to seeing or that's effectively represented in the data. On this episode of The Lending Link, we sit down with Kareem Saleh, CEO and co-founder of fairplay.ai, which assists lenders in identifying potential disparities in the decisioning systems, provides options to increase profitability and fairness, and helps in demonstrating to consumers, regulators and the public that they are taking strong steps to be fair. Kareem and Rich discuss how to assess algorithms for bias and optimize them for failures and as well as discuss a number of topics, including: The role of alternative data in credit underwriting and machine learning What is the adverse impact ratio? How is it determined? How does it function? How to identify variables for the protected groups that may not be in your initial model Opportunities for lenders to meet the requirements under the Community Reinvestment Act and more! About Kareem Saleh Kareem Saleh is the founder and CEO of FairPlay, the world's first Fairness-as-a-Service company. Financial Institutions use FairPlay's APIs to embed fairness considerations into their marketing, underwriting, pricing, and loss mitigation algorithms and automate fair lending testing and reporting. Previously Kareem served as Executive VicePresident at Zest.ai, where he led business development for the company's machine learning-powered credit underwriting platform. Prior to Zest.ai, Kareem served as an executive at SoftCard, a mobile payments company that Google acquired. Kareem also served in the Obama Administration, first as Chief of Staff to the State Department's Special Envoy for Climate Change, where he helped manage the 50-person team that negotiated the Paris Climate Agreement, then as Senior Advisor to the CEO of the Overseas Private Investment Corporation (OPIC) where he helped direct the U.S. Government's $30B portfolio of emerging market investments with responsibility for transaction teams in Europe, Latin America and the Middle East. Kareem is a Forbes contributor and a frequent speaker on the application of AI to financial services. He is a graduate of Georgetown University Law Center and an honors graduate of the University of Chicago. Be sure to follow Kareem and our host Rich on LinkedIn, and for the latest GDS Link updates and news, follow us on Twitter and LinkedIn. You can subscribe to the Lending Link on Apple Podcasts, Spotify, Google Play, or wherever you prefer to listen to your podcasts!

Next-Best-Action – dein Job im DDCM Consulting! Erhalte von Stephan und Christoph Einblicke in die Welt des “Data-driven Customer Management” (DDCM). Die etablierte Unternehmens- und Technologieberatung DYNACON wird ihr Geschäftsfeld DDCM in 2023 stark ausbauen. Dort wird den Kunden bei dieser faszinierenden Reise der Transformation geholfen, Altsysteme in neue Architekturen zu überführen, um mit Next-Best-Action gezielte Kundenerlebnisse zu schaffen. Du hast technisches Verständnis in Kombination mit konzeptionellen Denken und Kundenorientierung, um das datengetriebene Kundenmanagement und Real-time Decisioning voranzutreiben? Dein Interesse an dieser Position kannst du ohne Lebenslauf und ohne Anschreiben in weniger als 30 Sekunden über den Button auf unserer Webseite zeigen. Innerhalb von kürzester Zeit bekommst du von uns eine Rückmeldung.

Today we're going to talk about the power of always-on omnichannel marketing and how AI and next best action approaches can work together to create a better customer experience.   To help me discuss this topic, I'd like to welcome Shoel Perelman, VP Product, 1:1 Customer Engagement, Decisioning and AI, Pega.   RESOURCES   The Agile Brand podcast website: https://www.gregkihlstrom.com/theagilebrandpodcast   Sign up for The Agile Brand newsletter here: https://www.gregkihlstrom.com    Get the latest news and updates on LinkedIn here: https://www.linkedin.com/company/the-agile-brand/    For consulting on marketing technology, customer experience, and more visit GK5A: https://www.gk5a.com    The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow

Today we're going to talk about the power of always-on omnichannel marketing and how AI and next best action approaches can work together to create a better customer experience.   To help me discuss this topic, I'd like to welcome Shoel Perelman, VP Product, 1:1 Customer Engagement, Decisioning and AI, Pega.   RESOURCES   The Agile Brand podcast website: https://www.gregkihlstrom.com/theagilebrandpodcast   Sign up for The Agile Brand newsletter here: https://www.gregkihlstrom.com    Get the latest news and updates on LinkedIn here: https://www.linkedin.com/company/the-agile-brand/    For consulting on marketing technology, customer experience, and more visit GK5A: https://www.gk5a.com    The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow

Risk decisioning or risk assessment has traditionally been a detail intensive task with someone sifting through information or data to make informed decisions based on the risk profiles. With AI in the picture, things become more interesting as this allows for a large amount of data to be processed with the risk profile generated for review. To get an insight into how AI can benefit the whole process, we speak to Bharath Vellore, Provenir's General Manager for the APAC region.Image Credit: Shutterstock | Den Rise

Businesses looking for quick credit-decisioning can benefit from financial reporting that gives banks a clear picture of data. Listen as Sid Saxena, chief executive of artificial intelligence (AI)-powered accounting automation platform Docyt discusses the technology, its integration and how lenders can benefit from automated accounting to streamline decision-making.

It's decision time! In this special episode we debate which three detective movies we're gonna watch during the live event on July 1st! Everybody put July 1st in your calendars for the live event!0:00 -- Pre-lim live event chatter4:23 -- Andy's decisioning8:00 -- Josh's decisioning11:27 -- Mark's decisioning13:33 -- Ammon's decisioning23:31 -- Brooke's decisioning24:17 -- Katie's decisioning28:17 -- J.B.'s decisioning32:04 -- Detective cred40:45 -- Sorting 43:10 -- Lobbyvoting1.01:49 -- OutroHey! Leave us a voicemail at (801) 896-4542!Hey! We're on Spotify now!Hey! Watch Sleuth on YouTube!Hey! Hear our Murder by Death podcast on JRWSTFTFT!Hey! Subscribe in iTunes!Hey! Check out the Facebook page and vote on the next category!Hey! Check out Jon's YM&T Letterboxd list!Hey! Check out Roy's YM&T Letterboxd list!Hey! Email us at yoursminetheirspodcast@gmail.com! Send new topics! Send new theme songs!Download this episode right here!

Today we're joined by Rob Walker, VP of decisioning & analytics and gm of one-to-one customer engagement at Pegasystems. Rob, who you might know from his previous appearances on the podcast, joins us to discuss his work on AI and ML in the context of customer engagement and decisioning, the various problems that need to be solved, including solving the “next best” problem. We explore the distinction between the idea of the next best action and determining it from a recommender system, how the combination of machine learning and heuristics are currently co-existing in engagements, scaling model evaluation, and some of the challenges they're facing when dealing with problems of responsible AI and how they're managed. Finally, we spend a few minutes digging into the upcoming PegaWorld conference, and what attendees should anticipate at the event. The complete show notes for this episode can be found at twimlai.com/go/573

Chris Stephenson, global CMO of media agency Network PHD, thinks the marketing community has a weird and massive blindspot around gaming.  That may be because they are buried in admin rather than doing actual marketing. Per PHD's latest research study, 1,700 marketers around the world say their biggest time allocation is spent on reporting, not strategy, innovation and idea development. Those unable to shake off administrative shackles risk being overtaken by a marketing function overhaul now fast approaching – at least according to the group's new book, ‘SHIFT: a Marketing Rethink'.  In the short-term, it forecasts that key marketing and media roles will span influencer programmatic teams, game commerce, clean room development teams and decision scientists through to ‘layer designers', VR world designers and ‘brain-computer interface developers' in the mid- to long-term. Within 20 years we could see ‘quantum simulation developers' “simulating the entire media universe” for brands. But for now, Stephenson thinks those rushing headlong into the metaverse and Web3.0 are barrelling into the trough of disappointment. See omnystudio.com/listener for privacy information.

Brain Dunphy, SVP of Catalina, speaks with Allyson and Brett about their mutual love of consumer packaged goods and the emerging trends for this industry. Join them as Brian shares what excites him most about the CPG industry, how it's changed over the years, and how data can help CPG marketers get a far deeper understanding of consumer needs, online and offline shopping preferences, and growth drivers. --- Send in a voice message: https://anchor.fm/no-hype/message

In the financial services industry, risks related to climate change are now considered major, resulting in all firms assessing how to incorporate climate risk in financial decision making. As we find ourselves in the decisive decade, there is an urgency for financial services to not only better manage the financial and non-financial risks of climate change but also lead the way in sustainable finance. The scale and complexity of the problem demand new thinking and new technologies that will integrate well with existing risk management ecosystems. In this episode, we'll explore how AI and advanced analytics can help assess and address climate risk, while keeping the business lights on. This episode concludes a four-part series examining Responsible AI. Listen to the previous episodes here: Part One: Alternative Data in Risk Modeling Part Two: Explainable/Interpretable AI Part Three: Addressing Bias and Fairness in AI Systems   Learn More: From Crisis to Opportunity: Redefining Risk Management | SAS   Speakers Mark Nasila, Chief Data and Analytics Officer, FirstRand Risk Dr. Mark Nasila is the Chief Data and Analytics Officer of FirstRand Risk, a Singularity University Faculty. He is also a steering committee member of the National Institute for Theoretical Physics and Computational Sciences (NITheCS). As an experienced AI and data science expert, he ensures the techniques and methodologies he introduces into FNB are at the forefront of where banking is headed, both locally and internationally. He is the developer and the brain behind Manila, an AI system FNB has harnessed to reimagine its risk management and forensic due diligence processes. He holds a PhD in Mathematical Statistics from the Nelson Mandela University, and is also an alumni of the SingularityU South Africa Executive programme. He was named one of the Corinium Global Intelligence “2020 Global Top 100 Innovators in data and analytics.”   Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning, SAS Terisa Roberts is a well-rounded risk management professional with 15 years of risk management experience working predominantly in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in risk modeling topics for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks other financial services providers as well as regulators on innovations in Risk Modeling and Decisioning including Artificial Intelligence and Machine Learning. She holds a Ph.D. in Operations Research and Informatics and lives in Sydney, Australia with her family. ----------------------- Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to financial risk and have partnered on this episode of our podcast series. About SAS As a leader in analytics, SAS has more than 40 years of experience helping organizations solve their toughest problems. Our unrelenting commitment to innovation enables banks to modernize and sustain a competitive edge. SAS provides an integrated, enterprise-wide risk-management platform for managing risk in an organization, from strategic to reputational, operational, financial or compliance-related risk management. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk.

As AI becomes more capable, it must collect more data to adapt better to our world. By creating data artificially (and not at the expense of our privacy), our future becomes smarter that much faster. From teaching autonomous cars how to drive using 3D content to helping the blind run without fear using machine learning, our guests talk share the ways they've used synthetic data to achieve big things – and talk about even greater things it can make possible.    Key Takeaways: [2:01] Beatrice and her fellow researchers were handing over their own data to fill gaps in the studies when they did not have enough data, or when there were challenges around convincing subjects to be part of their study. So how could synthetic data have solved these problems? [2:54] Synthetic data is data that is artificially created and has the same statistical properties as the original data. However, when you generate synthetic data, the process is completely irreversible. [3:50] Without synthetic data, if the world has biased information, you may not see equal representation of people in all places and data that represents them. Phil Bayer, an engineer at Google's Project Guideline, discusses how data bias is no small concern. [6:17] Emna talks about how AI needs to develop new algorithms and methods to detect things and to mimic human behavior, with self-driving cars as an example. [9:07] Phil and his team at Project Guideline are working on a project that allows blind individuals to run outside by detecting a yellow line on the ground. Phil talks about how it all began when a man named Thomas Panek walked into a Google Hackathon and asked if they could help blind people run freely. A few surreal data sets later, Phil was moved by watching Thomas run freely outside. [14:36] Robotic systems might benefit from some virtual reality training, and using 3D environments to train AI on synthetic data is just the tip of the iceberg when we look at what is possible. Peter van der Putten, Director of Decisioning and AI Solutions at Pegasystems, and Prof of Media Technology at Leiden University speaks about how a lot of VR is too perfect, and we can benefit when it has the graininess and character of the real world. [16:57] After Grand Theft Auto 5 was released in 2013, Intel researchers decided to try to make a movie version of the game that would be more photorealistic. They used a machine learning technique that used real-world data. [20:02] Peter's student research has some interesting implications for how AI systems train best in virtual reality. Phil agrees, saying that using VR as a training site for AI just might be the way of the future.   Quotes: “We basically, as consumers or customers of any type, have no privacy at all. So, of course, I wanted to join this mission to build a technology that would eventually give us what is ours back.” - Beatrice 3:15 “Synthetic data can even help us balance out some of the biases we see in the real world. With synthetic data, you can create worlds that sort of you are hoping for, or that you're envisioning.”  - Phil 5:12 “With synthetic data, you can create realistic 3D content and without too much human effort and you can make more areas diverse.” - Emna 7:09 “To see sort of the variety of ways in which someone can be helped by technology —  like this is really powerful.” - Phil 14:11  “A lot of VR is hyper-realistic. It's not that it's not perfect enough. It's too perfect. It's missing the graininess, and the glossy character of the real world.” - Peter 15:58 “The other thing that has been showing a lot of promise in synthetic data is helping to try and remove bias from datasets. And so I think that's another reason why it's growing in popularity.” Phil - 19:40 “We can create less biased AI. We can share our data with confidence in our privacy.” James - 20:31   Continue on your journey: pega.com/podcast   Mentioned:  Grand Theft Auto  Article by the Imperial College London  Beatrice Milik  Emna Amor  Philip Bayer  Peter van der Putten

In this episode, we begin a four part series looking at Responsible AI by looking at Alternative Data in risk Modeling. Over the course of the coming months we will also look at Explainable / Interpretable AI, Fairness and Bias in AI, and the new frontier of climate models.  We will conclude the series with a wraps up webcast in January of 2022 - click here to register. Survey Says: Risk management key to resiliency in 2021 and beyond; click her to learn more and read the full report. To view GARP's DE&I webcast, "Risk Modeling to Further Diversity and Inclusion", mentioned in this episode - click here.  Speaker Bio Terisa Roberts is a well-rounded risk management professional with 15 years of risk management experience, working predominantly in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in risk modeling topics for retail and commercial portfolios including regulatory capital, stress testing and IFRS9/CECL. She advises banks, other financial services providers as well as regulators on innovations in Risk Modeling and Decisioning including Artificial Intelligence and Machine Learning. She holds a Ph. D in Operations Research and Informatics and lives in Sydney, Australia with her family. ----------------------- Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to financial risk and have partnered on this episode of our COVID podcast series. About SAS As a leader in analytics, SAS has more than 40 years of experience helping organizations solve their toughest problems. Our unrelenting commitment to innovation enables banks to modernize and sustain a competitive edge. SAS provides an integrated, enterprise-wide risk-management platform for managing risk in an organization, from strategic to reputational, operational, financial or compliance-related risk management. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk.

Minter Dialogue Episode #424Peter van der Putten, Director of Decisioning & AI Solutions at Pegasystems, a company that delivers innovative software designed to increase customer lifetime value, streamline service and boost efficiencies of their business client. A specialist on responsible Artificial Intelligence, Peter's also Assistant Professor of Data Mining & Creative Research at the Leiden University in The Netherlands. In this conversation, we dive into using Artificial Intelligence in business, discussing the state of play of AI, how to build and use AI systems in big business with an aim to drive performance and improve the decision-making process at scale, with an AI that is responsible, understandable and trustworthy. Pega's mission is to help its clients "crush complexity." We look at how this happens and how companies can integrate ethics, values and trust into their AI systems.        If you've got comments or questions you'd like to see answered, send your email or audio file to nminterdial@gmail.com; or you can find the show notes and comment on minterdial.com. If you liked the podcast, please take a moment to go over to iTunes or your favourite podcast channel, to rate/review the show. Otherwise, you can find me @mdial on Twitter.Support the show (https://www.patreon.com/minterdial)

In this week's episode of Analytics Neat we discuss a solution coming from Acxiom and MullenLowe and an update on the Google lawsuit in Australia on the Undercard. For the Main Event, we review a new paper from Pega on real-time decisioning and what that looks like within organizations. All this and more in this week's episode of Analytics Neat. Thanks for listening! iTunes: https://itunes.apple.com/us/podcast/analytics-neat/id1350608276?mt=2 Spotify: https://open.spotify.com/show/2DIz7pDt5IYA2VJ86LbaK3 Google Play: https://play.google.com/music/m/Iaeur7hjizv7s654nbcsfgtxsmq?t=Analytics_Neat Amazon: https://music.amazon.com/podcasts/3f77907d-81b7-46ff-a9cd-12c3c539a2ad/Analytics-Neat Continue the conversation on Twitter with #AnalyticsNeat https://twitter.com/BillBruno https://twitter.com/AnalyticsNeat Visit BillBruno.com

We're super excited to be hosting the wonderful Luky Primadani on Product with Panash.It's not an easy thing to grow UX as a practice in an organisation.It's even harder to make it central to your product decisioning and strategy and get your whole company on board.We thought we'd dive straight into this topic which proves challenging for many...We talk about

Hello and welcome to the new episode of the Risk Management Show brought to you by Global Risk Community. This is your host Boris Agranovich and our guest today is Terisa Roberts, Director, and Global Solution lead for Risk Modeling and Decisioning at SAS. In this interview we discussed the following questions: How did COVID impacted risk models? Based on your work with regulators and firms around the world, what are some of the kinds of AI/ML applications that are delivering tangible benefit? With new technologies come new risks. What are the main challenges that firms are facing in the use of newer advanced technologies in risk management? Are existing model governance frameworks sufficient for AI/ML? and more... ___ More detailed description below____ Terisa explains in a few sentences what her team at SAS have been up to these days: SAS has always been a leader in providing world-class analytical solutions for a wide range of business applications. These include risk management, fraud detection and customer diligence as well. What is exciting for her at the moment is they started to move and make their solutions available on their SAS Wire which is a cloud native platform. So that opens up a whole lot of new opportunities to innovate. But the COVID-19 pandemic has massively disrupted our lives. How did it impact risk models? Terisa believes that there is a pre-covid saying that essentially, all models are wrong, some are useful which now can be transformed into Essentially, all models are wrong, some are useless. And yes, most turned out to be useless. That is just because the model inputs have moved outside of the calibration range of these models. The models have never seen the narrative of a pandemic play out. So we've seen lockdown measures in many countries that had an impact on unemployment and on movement restrictions, et cetera. We as individuals then have been massively disrupted, but so have the business models of companies. So we've seen disruption at a global scale. And what we noticed on the risk management front is that not all the industries were impacted in the same way. So some were harder hit, than others. And the recovery path is still uncertain of what will happen now. She just wants to add to that, that we saw both the traditional statistical and econometric models breakdown, as well as the newer algorithms such as machine learning. Both models have had trouble in coping. So financial institutions had to apply their own human judgment and make adjustments and management overlays with those in place for the models. Based on Terisa's work with the financial and the regulators and the firms around the world, what are some of the kinds of AI/ML applications that are delivering tangible benefits? Well, what she sees with the use of AI and machine learning for risk management, it's really good at jobs that require repetition and that can be automated. So AI and machine learning is good at trolling through volumes and volumes of unstructured and structured data and picking up patterns that the human eye might miss. Possibly it's less glamorous than what we see in the movies, but definitely it's starting to pay off and deliver tangible benefits in the areas of credit scoring. So being able to offer credit and access to credit, to minority groups where perhaps the credit bureau funds are not available and also in the area of fraud detection and cybersecurity. And what did Terisa learn specifically as a risk management practitioner? Because with new technologies come new risks, what are the main challenges that firms are facing in the use of these new technologies? So in the area of risk management, she thinks there's still a lot of caution in the industry. These are known risks that we associate with the use of these more complex and sophisticated algorithms, say they lack transparency. It's not so easy to explain to the various stakeholders how the model works but there's also great strides being made in addressing the explainability of all of these algorithms. The other challenge that is often associated with AI and machine learning is that it may perpetuate and amplify a bias that might be present in your training data. So historically we might have some individual and societal biases, and that might be baked into, into the data that these algorithms are not smart enough to adjust for. So, we might be amplifying those biases with a user and we've seen this in the news. We saw it with facial recognition systems and in the credit space and approvals of credit cards, some big technology companies gave women a much lower credit limit because of the historical data. But by having said that, a bias definitely is a concern there always to address it. And once she has addressed it in these models, the AI and the machine learning models might even help us to make more consistent data-driven decisions. So definitely not in an insurmountable challenge. But are existing model governance frameworks sufficient for AI/ML or should there be new ones developed and approved by different bodies? The answer to that is yes, Terisa has had people mentioning: how about AI validating AI? So can we use AI models to also monitor these? Of course the shelf life of some of the models might be shorter than our traditional models because of the sophistication in the patterns that they've detected and maybe the robustness. So, she needs to up her levels of validation, to make room for AI and machine learning and it's putting a lot more demand on validation teams. Also in the areas of feature engineering that needs to be validated as well as other hyper parameter tuning methods that have been employed. So putting a lot more demand on model governance and it's certainly not going away with the use of AI and machine learning. So how can firms take a more strategic approach to the use of this new technology and the risk management from your opinion? What Terisa and her team has seen happen is that the process that takes to put models, whether they are traditional or more innovative into production is still long, on average it's six to nine months for the financial services industry. So, for banks to take new innovation and modeling seriously, they would need to rethink the model life cycle process, and look for efficiency gains perhaps in standardizing the data that goes into the models as well as looking at the deployment. Ideally if you think about it, a traditional model might have a handful of input variables. If we look at an AI or machine learning model that can easily turn into hundreds and thousands of input variables. So if you have a manual process of deploying those models into your decision architectures, for example, that might not be scalable for you as the models increasingly grow in number. So what should risk managers start doing in this field of a new technology of AIML that they are not doing, or maybe also another way around what should they stop doing that they are doing now? Terisa thinks that there's a hesitation to embrace new technologies. She understands that because there's also a lot of hype around the use of computer vision and robots doing people's work, but that is not the case. That is more than science fiction. So if we look at the science fact, there are areas where innovation can make a real difference, we see it in customer experience. By having these models to estimate income, you can gain efficiency and get much more accurate data. So, look at perhaps not replacing all your traditional models with machine learning. Look at where the AI and the machine learning model can give you additional value of perhaps in the auxiliary function, in your data quality processes, as well as in the feature engineering process, which is typically in the model of development life cycle, also quite a manual process. Just to summarize the major takeaways, if someone who is listening to this interview, would like to walk away with one or two major takeaways, what would it be from Terisa's point of view? When it comes to AI and machine learning, we need to rethink our architecture, the infrastructure behind the data management, the Modeling, as well as the deployment of the models and making sure that the infrastructure is future-proof to handle the sophistication of these models and look for areas where the manual processes can potentially be improved with automation, for those efficiency gains and scaling because the operational efficiencies or quite substantial,

In episode 32, I'm joined by James Dunlop. James is the Head of Decisioning and Digital for the Wealth division in NatWest Group. Before joining Natwest, James has worked for financial services brands including AXA and Lloyds in various data and analytics roles. Plus, like two of my previous guests (Andy Sutton & Harry Wilkes) James previously worked as part of my leadership team at Lloyds Banking Group. As well as exploring James' career history & why working in Financial Services is far from dull, we explore his focus on decisioning . James shares why this branch of data work appeals & the biggest challenges he sees today for decisioning (or database marketing) leaders. Along the way there are also tips for leadership development & for those newer in their careers. So, sit back and enjoy this data leader wisdom from the West Country (with some very well behaved guinea pigs in the background). It might just persuade you to either work for a Bank or focus your career on decisoning.

When it comes to CRMs, AI and other systems salespeople feel changes in systems benefits management not salespeople. Points covered: How does this AI product benefit the salesperson themselves? Does it help them schedule their calling? Does this function give better qualified leads, which would eliminate the 55% of the people not going to buy? Does it help in forecasting? Does it shorten the time to close a lead? Who is the special for, management or sales person? AND is it a special for the customer - what does it do for them? To get the answers to these questions, join Susan Finch and her guest, Matthew Nolan. Matt is the Senior Director of Product Marketing for Marketing, AI, and Decision Sciences at Pega.   ----more---- ------------------- Pegasystems is the leader in cloud software for customer engagement and operational excellence. If you’ve driven a car, used a credit card, called a company for service, opened an account, flown on a plane, submitted a claim, or performed countless other everyday tasks, chances are you’ve already interacted with Pega. For the past 30 years, their technology – CRM, digital process automation, robotics, AI, and more – has empowered the world’s leading companies to achieve breakthrough results.

In this Marketing Over Coffee: In this episode learn about SmartHub Customer Data Platforms (CDP), Agility of Decisioning, and more! Direct Link to File Brought to you by our sponsors: Upfluence and MarketingProfs Career Day Vijay is Co-Founder & CEO at Blueshift Walmart, Groupon and Beginning by watching CX change The mistake is thinking about […] The post Customer Data Platforms with Vijay Chittoor appeared first on Marketing Over Coffee Marketing Podcast.

What can AI teach us, about ourselves? What does it mean to be human? Check out this discussion on AI, where Peter shares some interesting examples of AI being used, and gaining insight into what it means to be the biological machines that we are. Find the guest: Twitter: @PetervanderP http://liacs.leidenuniv.nl/~puttenpwhvander/ https://www.linkedin.com/in/petervanderputten/ ‘The Future of AI is Human' event: https://www.universiteitleiden.nl/en/sails/research/webinar-dec-2020-art-society-and-technology Bots Like You (joint work with Maarten Lamers) https://sites.google.com/view/botslikeyou Thesis Jules Verdijk on generating abstract modern art paintings https://mediatechnology.leiden.edu/research/theses/evolving-affective-abstract-art-through-measures-learned-from-a-corpus-of-h Joost Mollen's couchsurfing BlockBots http://joostmollen.com/index.php/robotics/blockbot/ Jeroenvandermost https://www.jeroenvandermost.com/letters-from-nature Find me: patreon.com/jasonspodcast findinginspirationpodcast@gmail.com

On our 7th episode we are joined by two very talented women, Siew Choo Soh, Managing Director & Group Head of Consumer Banking and Big Data/AI Technology at DBS Bank and Terisa Roberts, Director and Global Lead: Risk Modelling and Decisioning at SAS. Siew Choo shares with us DBS’s mindset around innovation. For them, the use of technology does not equate to innovation. They don’t have a designated innovation department, just a small innovation team whose job is not to innovate, it’s rather helping other people across the bank to innovate. They provide resources to enable everyone to be able to innovate by empowering the individuals and teams to be curious. Terisa draws attention to a recent study by Deloitte, showing that firms who invest in diversity and innovation are 8 times more likely to achieve their business outcomes. She also mentions that in Risk Management, they monitor the algorithms they’re using in society and how these algorithms can discriminate against certain groups. Whenever they are faced with these challenges, a diverse team is in charge of identifying and remediating these biases. Quotes: "Their job is not to innovate, their job is to help other people across the bank to innovate." "You have to introduce bias to unbias your algorithm, because the algorithm has been trained by biased data." "Because of historical biases that were present in the training data that the algorithms learned from, that was perpetuated. A diverse team would have been able to stop that bias from becoming operational in the way decisions are made within that firm." "To make them understand each other from the different background they have, whether from cultural perspective or job experience perspective, can sometimes be quite a challenge, but I would say that once you manage to go through that initial phase you’ll see that it will help you get the best results, if you have a very diverse group of people." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 7 Enjoy the seventh episode of our #SheLeads Series! --- Send in a voice message: https://anchor.fm/datafuturology/message

MLOps community meetup #39! Last week we talked to Ivan Nardini, Customer Engineer at SAS, about Operationalize Open Source Models with SAS Open Model Manager. // Abstract: Analytics are Open. According to their nature, Open Source technologies allows an agile development of the models, but it results difficult to put them in production. The goal of SAS is supporting customers in operationalize analytics In this meetup, I present SAS Open Model Manager, a containerized Modelops tool that accelerates deployment processes and, once in production, allows monitoring your models (SAS and Open Source). // Bio: As a member of Pre-Sales CI & Analytics Support Team, I'm specialized in ModelOps and Decisioning. I've been involved in operationalizing analytics using different Open Source technologies in a variety of industries. My focus is on providing solutions to deploy, monitor and govern models in production and optimize business decisions processes. To reach this goal, I work with software technologies (SAS Viya platform, Container, CI/CD tools) and Cloud (AWS). //Other Links you can check Ivan on: https://medium.com/@ivannardini ----------- Connect With Us ✌️------------- Join our Slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Ivan on LinkedIn: https://www.linkedin.com/in/ivan-nardiniDescription Timestamps: 0:00 - Intro to Ivan Nardini 3:41 - Operationalize Open Source Models with SAS Open Model Manager slide 4:21 - Agenda 5:01 - What is ModelOps and what is the difference between MLOps and ModelOps? 6:19 - "Do I look like an expert?" Ivan's Background 7:12 - Why ModelOps? 7:20 - Operationalizing Analytics 8:12 - Operationalizing Analytics: SAS 9:08 - Operationalizing Analytics: Customer 11:36 - What's a model for you? 12:07 - Hidden Complexity in ML Systems 12:52 - Hidden Complexity in ML Systems: Business Prospective 14:12 - Hidden Complexity in ML Systems: IT Prospective 17:12 - One of the hardest things is Security? 17:52 - Hidden Complexity in ML Systems: Analytics Prospective 19:20 - Why ModelOps? 20:09 - ModelOps technologies Map 22:29 - Customers ModelOps Maturity over Technology Propensity. MLOps Maturity vs. Technology Propensity 26:23 - Show us your Analytical Models 26:56 - SAS can support you to ship them in production providing Governance and Decisioning. 27:28 - When you talk to people, is there something that you feel like there is a unified model, but focusing on the wrong thing? 29:14 - Have you seen Reproducibility and Governance? 30:47 - Advertising Time 30:55 - Operationalize Open Source Models with SAS Open Model Manager 31:02 - ModelOps with SAS 32:06 - SAS Open Model Manager 33:18 - Demo 33:27 - SAS Model Ops Architecture - Classification Model 35:02 - Model Demo: Credit Scoring Business Application 50:20 - Take Homes 50:24 - Operationalize Analytics 50:32 - Model Lifecycle Effort Side 51:20 - Business Value Side 51:47 - Typical Analytics Operationalization Graph 52:18 - Analytics Operationalization with ModelOps Graph 53:18 - Is this for everybody?

In episode 25 we travel to Scotland for my conversation with Firas Khnaisser. He is Head of Decisioning for Standard Life Aberdeen & Chair of DMA Scotland. In this interview, we explore his career history (starting in a Dubai DM agency) and how he was challenged to not be afraid of data. From there we confront the limiting belief that you can't effectively lead data teams without a data background. We also explore the reality of 'Decisioning' work & the difference that the DMA still makes as a force for change today. Finally, we explore the benefit of being different & being yourself, with an encouragement to listen to Firas' other passion, his music. My thanks to Firas for being so open.

In this interview we discuss the Risk Modelling and Decisioning as well as the model governance in our digital future. Especially we discuss the impact COVID-19 as a driver to the new operating reality

Robot-fan Tom speaks to Peter van der Putten, Assistant professor in AI & Creative Research at Leiden University, and Director, Decisioning & AI Solutions, at Pegasystems. Peter researches robots, in all their forms, looking particularly at the interface between human and machine. He and Tom discuss emotional robots, misbehaving robots, and why it's important to experiment with machines that do bad, as well as machines that do good.  You can find out more about Peter and his projects, both academic and corporate, at these links: Academic page: http://liacs.leidenuniv.nl/~puttenpwhvander/ Bots Like You: https://sites.google.com/view/botslikeyou Twitter: @PetervanderP LinkedIn: https://www.linkedin.com/in/petervanderputten/ Industry: www.pega.com, www.pega.ai

Minter Dialogue Episode #374Vince Jeffs is Senior Director of Product Strategy, Marketing AI and Decisioning at Pegasystems, which is holding its iNspire online event on June 2. Vince is also currently the #6 ranked overall author on CustomerThink.com, and the #2 on Customer Analytics. Vince and I discuss how AI has been applied during the pandemic, how to use AI responsibly for example in developing the best customer experience, Pega's Ethical Bias Check to help guide AI implementation.If you've got comments or questions you'd like to see answered, send your email or audio file to nminterdial@gmail.com; or you can find the show notes and comment on minterdial.com. If you liked the podcast, please take a moment to rate/review the show on RateThisPodcast. Otherwise, you can find me @mdial on Twitter.Support the show (https://www.patreon.com/minterdial)

Decisioning in detail is what it's like to be human 

The term "Gamechanger" gets used a little too often these days.In fact, it's becoming kinda like YOLO (which died way too young, ironically).Stedman Cleveland was an OOH Outsider until he found a billboard for a Broadway show that made him want to buy tickets.Then he went on a journey, like so many of us, where he saw a piece of advertising that made him want to spend money and it was impossible to find out more information on the thing he wanted to buy - tickets.So, he popped open his Product Development toolbox and went to work.Less than 10 months later and he has people LOOKING for his client's billboards like its the summer of 2016 and Pokemon Go is the hottest thing on the streets.Is his app, Tadaw, the Pokemon Go craze for OOH?Maybe.Probably not.But who cares when you can get 60% of users to show up at your billboard and then consume nearly 5 minutes of bonus content by the advertiser?Oh, sales?Yeah, 3 out of the 100 made a purchase DIRECTLY THRU THE APP, meaning that the retailer was able to keep selling to people who showed up AFTER they were closed.Seriously, the whole thing is insanely cool and something you should be talking about with your clients.Out of Home creates Awareness and Interest.Tadaw creates the ability to convert that Awareness and Interest into Decisioning and Action.And that, fellow marketers, is a complete funnel.Wait wait wait!"But how much is it?!" you may be asking.You only pay when someone actually engages with the billboard and takes action.Yup, only pay for engagement you actually get.Check it out.ACCESS THE FREE CASE STUDY HERE: https://www.linkedin.com/pulse/tadaw-case-study-story-stedman-cleveland/Get in touch with Stedman at: stedman@tadaw.appOr connect with him on LinkedIn: https://www.linkedin.com/in/stedmancleveland/Make sure to follow Tadaw on Instagram:https://www.instagram.com/tadawapp/Or on the Facebooks: https://www.facebook.com/tadawappAs always, you can connect with me at: https://www.linkedin.com/in/troweactual/Support the show (http://oohswag.com)

Today we speak with Vikas Deep Sharma, Executive Director, EY and Ivy Tan, EY Senior Manager, specializing in IFRS 9 and Credit Risk for the Financial Services Sector, on the subject of Credit Risk Modeling and Decisioning. For more insights on this topic, read this white paper: 6 Keys to Credit Risk Modeling for the Digital Age The emerging role of machine learning and alternative data in credit decision making Download: https://www.sas.com/gms/redirect.jsp?detail=GMS116860_161344

Today's interview is with Rob Walker, Vice President Decision Management and Analytics at Pegasystems and is responsible for the company's suite of predictive decisioning technologies. I had a chat with Rob at Pega's annual customer event: Pegaworld 2016 to find out more about what makes Pega different and a bit more about their analytics and decisioning technology, how it can be applied and how it can improve the customer experience. This interview follows on from my recent interview – Most personalisation initiatives fail to improve customer experience – Interview with Jan Jensen of CXense – and is number 184 in the series of interviews with authors and business leaders that are doing great things, helping businesses innovate and delivering great service and experience to their customers.

Today's interview is with Kerim Akgonul who is Senior Vice President of Products at Pega and is responsible for the company's suite of Customer Relationship Management (CRM) applications. I had a chat with Kerim at their annual customer event: Pegaworld 2016to find out more about what they are up to, what makes them different and how they are fast becoming the big, new challenger in the CRM space. This interview follows on from my recent interview – Your people know the best ways to improve your organisation – Interview with Cathy Brown of Engage For Success – and is number 182 in the series of interviews with authors and business leaders that are doing great things, helping businesses innovate and delivering great service and experience to their customers.

Half of the companies on the S&P 500 will fall off the list in the next 10 years. Heightened customer preferences, rapid innovation and easy access to scalable and inexpensive technology have given way to a business environment where never normal is the new normal. In this episode, we introduce Adapt or Die, a new podcast that explores the fast-changing global landscape, its effects on the supply chain and the science behind intentional enterprise decision making.

Today we speak with Vikas Deep Sharma, Executive Director, EY and Ivy Tan, EY Senior Manager, specializing in IFRS 9 and Credit Risk for the Financial Services Sector, on the subject of Credit Risk Modeling and Decisioning.    For more insights on this topic, click here.  White Paper 6 Keys to Credit Risk Modeling for the Digital Age The emerging role of machine learning and alternative data in credit decision making   About this paper Does your organization want to make faster and more accurate credit decisions for both origination and servicing? Modernizing and automating the end-to-end process – from data management to model development and credit decisions – can reduce credit losses and boost performance. Empowering this process with machine learning supports more effective decisions about credit for individuals, products or portfolios.   About SAS SAS is the leader in analytics. Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS gives you THE POWER TO KNOW®.

Ep. 9 - Decisioning engines

Ep. 9 - Decisioning engines

The latest instalment of Boardroom Hustle has co-hosts Paul Smith and Anna Byrne discussing something that affects every single one of us. Something that many of us aren’t even aware of…...cognitive bias. Our episode is a sort of follow-on of the fifth episode of Boardroom Hustle, The Elephant in the (Board)room, where we talked about cultivating clearer decision-making, but focusing on how cognitive biases affect our decision-making, not just as directors in the boardroom, but as people in life! But first, what is a cognitive bias? Simply put, it refers to the mental shortcuts our brains take when we make decisions. The brain is an enormously intelligent piece of machinery that has created a way to jump to conclusions rather than spend precious energy trying to sort through the never-ending stream of information that is constantly being downloaded. While cognitive biases often have a bad reputation, they’re actually quite useful – to a point. We live in such a rich, complex, stimulating environment that, in order to be more efficient, our brains collect a number of cognitive biases (or shortcuts) about a wide aspect of topics in order to help us make decisions faster. So, how can we make our cognitive biases work for us? Have a listen to the episode to find out. Anna and Paul also discuss things like: The biggest thing that impacts cognitive bias Are biases infectious? How can a boardroom environment influence individual biases? One particular bias that can be hugely detrimental to the boardroom Following the peanuts; how our emotional elephants encourage us to jump to conclusions and how we can train them to make better, more effective decisions The different types of biases we experience, such as social, information, confirmation and anchoring, and how we can make them work for us rather than against us The best strategy you can implement in your boardroom/s, to unpack cognitive bias and create a more powerful method of decision-making How integrative AI may eventually be able to assist us in recognising and deleting any bias from our decision-making The five killer questions you can ask yourself and your board to discover any existing biases you might have and begin to overcome them Links:Future Directors Website: https://futuredirectors.com/ NeuroPower Website: http://neuropowergroup.com  Paul Smith LinkedIn: https://www.linkedin.com/in/futurepaulsmith/Anna Byrne LinkedIn: https://www.linkedin.com/in/anna-byrne-13901262/  

In this episode of our Deep Learning Indaba Series, we’re joined by Osonde Osoba, Engineer at RAND Corporation and Professor at the Pardee RAND Graduate School. Osonde and I spoke on the heels of the Indaba, where he presented on AI Ethics and Policy. We discuss his framework-based approach for evaluating ethical issues, such as applying the ethical principles laid out in the Belmont Report, and how to build an intuition for where ethical flashpoints may exist in these discussions. We then shift gears to Osonde’s own model development research and end up in a really interesting discussion about the application of machine learning to strategic decisions and game theory, including the use of fuzzy cognitive map models. The complete show notes for this episode can be found at twimlai.com/talk/192. For more info on the Deep Learning Indaba series, visit twimlai.com/indaba2018.

In this episode of Boardroom Hustle, co-hosts Paul Smith and Anna Byrne flip the script and interview Anna herself, to discuss her fascination with decisioning – the cognitive process we undergo with every single choice we make. But how much of this process is subconscious? Are we really making decisions based on new information, or are we merely running on autopilot? And could technology possibly replace decision-making for us? Understanding this intricate process is key in unlocking higher cognition, which can lead to making better choices and, ultimately, creating a greater impact in what we do. Anna has an avid interest in cognitive neuroscience, and she takes us on an interesting journey in which she explains the importance of “training an elephant” to cultivate clearer decisioning. Anna developed a love of neuroscience at a young age, thanks to her mother’s psychiatric career path, and she has such an easy, natural way of explaining tricky subjects – like the mechanics of the brain – that just about anyone can understand. So, if you’re eager to hear more about this elephant and peek behind the curtain to see how we make decisions, as well as how you can apply certain tricks and tips to your own cognitive thinking to create the best possible outcome for your life, and how you can improve your board through doing so, give the episode a listen. You’ll also dive deep into the following: Decisioning, the cognitive process that leads us to choose the things we choose Why we can lose up to 75 percent of our cognitive functioning if we try to avoid how we’re really feeling The positive and negative impacts that technology can potentially have on human-based decision making How we can use technology to enhance, rather than replace, our humanness Why we need to understand the complex, fascinating process of decisioning, and how we can use it to our advantage The three lenses we use to view decision-making Common problems that are often seen in small groups of powerful people (and what you can do to solve them!) The danger in constantly referring back to habitual perspectives How our brains are controlled by two systems that have very different approaches to problem-solving Changing your narrative so you can take on a brand new perspective Wasting valuable bandwidth with emotional reactions, and how we can get more time by taking control of our decisioning Links: Future Directors Website: https://futuredirectors.com/ NeuroPower Website: http://www.neuropowergroup.com  Paul Smith LinkedIn: https://www.linkedin.com/in/futurepaulsmith/ Anna Byrne LinkedIn: https://www.linkedin.com/in/anna-byrne-13901262/  

In this, the final episode of our PegaWorld series I’m joined by Vince Jeffs, Senior Director of Product Strategy for AI and Decisioning at Pegasystems. Vince and I had a great talk about the role AI and advanced analytics will play in defining future customer experiences. We do this in the context provided by one of his presentations from the conference, which explores four technology scenarios from Pegasystems’ innovation labs. These look at a connected car experience, the use of deep learning for diagnostics, dynamic notifications, and continuously optimized marketing. We also get into an interesting discussion about how much is too much when it comes to hyperpersonalized experiences, and how businesses can manage this challenge. The notes for this show can be found at twimlai.com/talk/154. For more information on the Pegaworld series, visit twimlai.com/pegaworld2018.

Machine learning is transforming business from every angle. Learn how machine learning is driving operational efficiency, improving customer experience and helping to solve business problems.

In this week's episode, Dr. Steve has an inspiring and powerful interview with Scott Rotermund, the co-founder and Chief Growth Officer for Welltok - an enterprise SaaS company focusing on driving healthcare consumers to attain and optimize their health. Welltok works with payers, providers and self-insured companies; and they have recently been added to Deloitte's fastest-growing companies in North America. This show episode includes a highly-engaging back-and-forth on: Welltok's CafeWell Platform The power of engagement in massive value gains Company growth through organic & inorganic means Loss aversion, rewards, and consumer responsibility 40-50% operational efficiencies realized by customers The importance of coordinating and streamlining multiple streams of consumer messaging.

FEATURING: Our special guest this week is Kimberly Keller!New Business includes Call of Duty on Wii U, Super Metroid, #UNDEADBOWLING, Puzzle & Dragons, and quite a bit more!Our Wii U fall preview sees the four panelists taking turns to choose a couple games each that most excite us!

Title – Leveraging “Customer Insights” and “Real Time” Decisioning for Customer Success  Expected Outcomes: Using real-time decisioning to guide customer interactions across multiple channels Applying business intelligence and analytics to customer interactions How companies can access customer information with little or no access What quantifiable results should you expect if implementation is made with real-time decisioning What are the organizational obstacles to getting real-time decisioning up and running Example of best practicesFeaturing: Jo Ann Parris Principal, The Parris Group Formerly Vice President - Vertical Solutions Marketing at Convergys Bob Moore - Independent Consultant Formerly Director of Marketing at Convergys Episode: • Friday October 5th 12:00pmEST - 1:00pmEST • Call-in Number: (323) 679-0913  

Straight from the VP's mouth.  Bud and I talk about his adoption of Agile and Lean practices in his line of business.  Who said you can not do Agile in an opreations group...Not Me.  Capital One has a large Agile implimentation and Bud was one of the early adopters.I enjoyed this interview quite a bit.  I hope to see Bud on the next Agile tour here in DC at Agile 2007. -bob