ai - CULytics Community2024-03-29T06:52:39Zhttps://culytics.com/blogs/feed/tag/aiArtificial Intelligence as a Playing Field for Credit Unionshttps://culytics.com/blogs/artificial-intelligence-as-a-playing-field-for-credit-unions2021-12-06T15:46:58.000Z2021-12-06T15:46:58.000ZMedhavi Singlahttps://culytics.com/members/MedhaviSingla<div><p>On November 30, a panel discussion was conducted with a focus for credit unions addressing “<a href="https://youtu.be/ynoXFz6RePI" target="_blank">Assessing risk and optimizing growth for each member</a>”, hosted by <strong><a href="https://bit.ly/3GlcOth" target="_blank">Neuton.AI</a></strong>. This event brought together thought leaders from the industry who shared views on how credit unions can uncover new growth opportunities and mitigate risks by leveraging AI.</p>
<p>Needless to say, the pandemic has caused a seismic shift in how we interact with customers such as how members are now expecting to consume services, their digital expectations which have in turn forced credit unions to rethink the way they interact and respond to member needs. This has subsequently led more and more credit unions to adopt a more data-driven mindset while leveraging innovative technologies such as artificial intelligence or machine learning. Beginning this journey, institutions are faced with a number of challenges such as where you begin, why data is important, what the possibilities are, and how I complete this journey when I may not have the resource or financial capital that is historically required to implement such services. The panel takes these topics head-on providing practical and ready to apply solutions to these challenges.</p>
<p>The panel discussion brought together <em>Anne Legg</em>, Founder of Thrive and Author of Big Data/Big Climb, <em>Naveen Jain</em>, Founder of CULytics, <em>Jay Lauer</em>, Senior Innovation Strategist at PSCU, <em>Todd Lindemann</em>, Senior VP of Payments at Redwood Credit Union, <em>Michael Lawson</em>, Creator at CUbroadcast, and <em>Blair Newman</em>, CTO at <a href="https://bit.ly/3GlcOth" target="_blank">Neuton.AI</a>, all well-respected professionals in their field of expertise.</p>
<h2><strong>Post-pandemic challenges for credit unions</strong></h2>
<p>Michael and Blair kicked off the event with a brief fireside chat where they began to discuss and note the challenges that credit unions have faced in light of our new pandemic reality. One notable realization is that members have begun to consume services differently than prior to the pandemic, which has forced credit unions to adjust quickly. The new realization is that it has become more challenging to engage your existing customer base let alone continue to drive growth with new members or additional services. The current state of affairs indicates the need for alternative and innovative ways to service your members as the need for enhancing the customers’ digital experience has come crashing to the forefront now.</p>
<p>“We see that credit unions are at different stages of their journey. Some customers are looking to explore how they can leverage a forward-leaning technology such as machine learning, some are looking to debunk some of the myths about the ability to implement ML solutions, some are ready to begin their journey and some are well on their way. One of the things that we've really focused on is eliminating all of those barriers.” — recapped Blair.</p>
<p>Naveen also mentioned that, based on his experience, the majority of data and digital initiatives simply fail to deliver on the promised value due to the lack of understanding of what problems they should solve. “Our mission is to help credit union leaders be successful with their investments in data and digital, with the focus on events, a vibrant community, management consulting, and complimentary advisory services.”, — added the founder of CULytics.</p>
<h2><strong>Barriers on the way to innovation</strong></h2>
<p>Speaking of innovation, Jay Lauer highlighted that credit unions don’t have to invent anything revolutionary but simply adapt to new ways of thinking and doing business. On the other hand, they need to figure out how to go faster and bring innovation to production quickly and effectively. “Nearly 85% of credit unions feel that AI is critical to long-term success. At the same time, however - over 70% feel they are behind when it comes to adopting such solutions.”, — said Jay. He also mentioned three reasons that hold credit unions back at the moment:</p>
<ul>
<li><strong><em>Lack of focus on the data strategy and effective data management</em></strong>. As data is the lynchpin for both AI strategy and execution, credit unions need to eliminate data silos, shine a light on dark data, and adopt data stewardship principles. Such practices help to build trust in the credit union’s data and in how that data may be used.</li>
<li><strong><em>Lack of organizational readiness</em></strong>. Many credit unions feel they have a limited understanding of AI potential and have trouble with use case identification. Educating credit unions on these aspects can be a big step towards their success.</li>
<li><strong>Poor execution, primarily centered on a shortage of talent or availability of AI technology</strong>. Credit unions have to attract talent and upskill the talent they already have, but they should also be looking at how technology may help them in this area. They could explore low-code or no-code solutions or look at other platforms which might provide some additional capacity for the team they already have.</li>
</ul>
<p>One more important finding for credit unions, according to Anne Legg, is understanding where Member friction exists within a Credit Union’s ecosystem and building a roadmap to reach the full-enterprise capability. “We see an uptick in critical thinking which enables a credit union to move from a reactionary position to a proactive position, take the right insights and do things with them.” — said Anne.</p>
<h2><strong>Practical use of AI/Machine Learning in Redwood Credit Union</strong></h2>
<p>Redwood Credit Union is a model of not only embarking on their data-driven AI-powered journey but also bringing innovation to life, Todd Lindemann shared their experience in making the member experience more satisfying while also realizing organization value.</p>
<p>Firstly, it’s crucial to understand where you are with your data. Once the Redwood team figured out their situation, they started to use data on a daily basis by regularly asking members for feedback, implementing critical thinking, and infusing data into all business processes.</p>
<p>One of the directions that Redwood has taken is moving to a more cashless environment. At this point, Redwood partnered with Neuton.AI to explore individual member needs with the help of an automated machine learning platform. The Neuton.AI team helped Redwood CU to develop and implement an AI-based predictive Member risk model as a baseline service to understand which Members were considered high risk and which members were considered low risk. This model was built without the consideration and/or use of the FICO score and was developed strictly on individual Member behavior. Leveraging this baseline predictive model Redwood CU was able to apply this risk rating model to a member's ability to withdraw funds during an ATM transaction. Lower risk members would be enabled with higher ATM withdrawal limits above the default limit as well as the ability to boost their access to cash dynamically upwards to $10,000. Implementing such a forward-thinking solution reduced the amount of times Members were effectively reaching their static limit which oftentimes forced them to either go inside the branch or contact the Member Service Center. This was the first step in improving the customer’s digital experience, providing more efficient access to cash resulting in improved customer satisfaction.</p>
<p>The member risk rating model is an innovative approach and the first step for Redwood to continue to bring additional value to their Members by implementing additional solutions such as implementing dynamic overdraft limits, Credit Scoring, and Member Lifetime Value just to name a few. More importantly, by leveraging Neuton’s zero code AutoML platform, Redwood is empowered to implement such solutions without a Data Scientist and realize results in days rather than months.</p>
<h2><strong>Conclusion </strong></h2>
<p>Anne Legg concluded that the key value of credit unions is their mission-based approach as they make great efforts to build member-centric relationships. As the post-pandemic realities continue to impose their own will, Credit Unions should amplify their strategies of personalization of products and services, which can be reached faster only by using AI innovations and handling data appropriately.</p>
<p>It is vital to establish data management strategies, remain active in like-minded communities, and not be paralyzed by the use of transformational solutions such as no-code AutoML platforms like Neuton, which provides enormous opportunities to uncover granular insights to drive personalized services, enhance the Members digital experience while driving value for all Credit Unions irrespective of their size or point in time in their AI Journey.</p>
<p>You can watch the full session here - <a href="https://youtu.be/ynoXFz6RePI" target="_blank">https://youtu.be/ynoXFz6RePI</a></p></div>Using Artificial Intelligence to Improve Your Productivityhttps://culytics.com/blogs/using-artificial-intelligence-to-improve-your-productivity2021-05-15T20:34:02.000Z2021-05-15T20:34:02.000ZMedhavi Singlahttps://culytics.com/members/MedhaviSingla<div><p> <a href="{{#staticFileLink}}8933385885,RESIZE_930x{{/staticFileLink}}"><img class="align-center" src="{{#staticFileLink}}8933385885,RESIZE_710x{{/staticFileLink}}" alt="8933385885?profile=RESIZE_710x" width="710" /></a></p>
<p>The digital age is enabling value like never before. Credit Unions are utilizing technological resources to help with their daily operations and improve productivity.</p>
<p>In this article, we discuss and share some relevant best practices on increasing automation to reduce costs, increase revenue and improve revenue and member satisfaction. These insights on “Automate and Elevate” were shared by Dr. David Tuyo, President, University Credit Union, at the 6th Annual CULytics Summit.</p>
<p>Strategic Priorities of University Credit Union - Before the automation initiatives, University Credit Union had the following objectives -</p>
<ol>
<li>To Invest in Employees</li>
<li>To Simplify Products and Services</li>
<li>To Increase Speed and Quality</li>
<li>To Enhance Accessibility to/for the Member</li>
</ol>
<p>Here is how the Credit Union has moved towards achieving its objectives.</p>
<p>1.<strong>ROYCE - Chatbot and Digital Assistant</strong></p>
<p>The problem statement which pushed the initiatives was as follows - “How can University Credit Union leverage technology to exponentially scale to surpass growth rates of assets, loans, and revenue from larger financial institutions?”</p>
<p>The solution was to develop a cognitive agent, and hence, they introduced Royce- Digital Assistant from UCU, which is now integrated throughout the member experience and all touchpoints.</p>
<p><strong>2. Know your numbers, know your business</strong> </p>
<p>The Credit Union developed a 20 mile March Principle, the essentials of which were as follows -</p>
<ul>
<li>Keep a steady pace</li>
<li>Focus on consistent, long term performance</li>
<li>Have concrete, clear, intelligent, rigorously pursued, performance mechanisms.</li>
</ul>
<p><strong>3. Due diligence</strong> - Through due diligence, UCU attempted to discover and answer whether they would want to buy or build a solution, narrowed the market quickly, and chose a solution provider whose scalability was wide and deep.</p>
<p><strong>4. Understand the process and built greater levels of intelligence</strong> - UCU took time to understand the reaction of members and interaction with Royce and built on it. </p>
<p><strong>5. Metamorphosis of Artificial Intelligence at University Credit Union</strong></p>
<p>University Credit Union built artificial intelligence function with Royce, and it got smarter with time. This happened over a series of phases.</p>
<p>Phase 1: Information and Product Discovery Experiences</p>
<p>Phase 2: Product Application using assisted forms and conversational forms</p>
<p>Phase 3: Transactional Experiences</p>
<p>Phase 4: Call Center Automation</p>
<p>Phase 5: Intelligent Banking Experiences</p>
<p>On-going learning maintenance</p>
<p>Eventually, Royce Interactions and UCU Live video banking increased, whereas calls to call centers decreased. There has been a sustainable spike in digital and mobile banking as well.</p>
<p><strong>6. Transforming the Technology Stack </strong>- UCU had to rethink the entire technology stack. They had to do core assessment, digital services assessment, and look at API Functionality, mobile and digital banking, API Access to other services and reduce initial transactional set because of risk. With a better understanding of member behavior, the transaction sets were eventually increased.</p>
<p><strong>7. Employee Education Program and initiatives - </strong>The employees at UCU went through education and knowledge-based promotions for roles and responsibilities like:</p>
<ul>
<li>Career Pathing/Laddering</li>
<li>Member Service Specialist</li>
<li>Member Success Coach</li>
<li>Member Wellness Coach</li>
<li>Financial Advisor. </li>
</ul>
<p>There are also certifications available like :</p>
<ul>
<li>Certificate in Accounting</li>
<li>Internal Audit Certificate</li>
<li>NAFCU Compliance Certification</li>
<li>NAFCU Risk Management Certification.</li>
</ul>
<p>Through this, employees became capable of addressing member’s questions professionally and intelligently.</p>
<p><strong>CONCLUSION</strong></p>
<p>As we can learn from UCU’s transformation, Never stop learning, and become a student of your profession. The switch to intelligent automation is no less than metamorphosis, and you become efficient only with time, and as you stay consistent. </p></div>Story of James: An Intelligence Transformationhttps://culytics.com/blogs/story-of-james-an-intelligence-transformation2021-04-19T18:18:12.000Z2021-04-19T18:18:12.000ZMedhavi Singlahttps://culytics.com/members/MedhaviSingla<div><p><a href="{{#staticFileLink}}8811404100,RESIZE_930x{{/staticFileLink}}"><img class="align-center" src="{{#staticFileLink}}8811404100,RESIZE_710x{{/staticFileLink}}" width="710" alt="8811404100?profile=RESIZE_710x" /></a></p>
<p>With the constantly increasing competition in the market; it has become imperative to deliver the right thing and within the said timeline. And, with the introduction of Artificial Intelligence, it is easy to do. AI is nothing but a simulation of human processes by a machine. These processes encompass learning, reasoning, and self-correction. So, automating day-to-day work that requires a quick response with accuracy could be the right decision. This will surely result in saving manpower and increase productivity. So, for better understanding, Kevin L.E. Landel talked about the same at the 5th Annual CULytics Summit.</p>
<p><strong><em>Kevin L.E. Landel</em></strong>, with 15 years of industry experience, has been serving Patelco Credit Union for years as SVP, Chief Information Officer and his new role at the organization is - SVP, Innovation, and Payments Strategy.</p>
<p><strong><em>Patelco Credit Union</em></strong> is $7.8 Billion in Assets with 36 Branches and 380,000 Members. The organization is operating with an aim to fuel hope and create opportunities to empower the members to build lifelong financial health and well-being. It has been proudly serving the Northern CA market for over 80 years.</p>
<p><strong><em>James</em></strong> – a digital worker – has been with the Patelco Credit Union since 2016. It is an AI-powered Virtual People designed to Talk-Think-Act and currently serving as the primary knowledge base for the organization. </p>
<p>Kevin L.E. Landel explained how James was created to ease the work of the team members at the Transformation Challenge Summit organized by The CUytics. Here is the information:</p>
<p><strong><u>Problem Statement</u></strong></p>
<p>Patelco Credit Union rolled out a new online banking and bill payment platform. And, whenever an organization introduces a new online platform, there is a need for a lot of resources for communication for information sharing with the members and answer the queries they might have. The “team member readiness” program ensures that in-house people can help the members whenever they approach. However, despite the best preparations, questions came in that the organization never anticipated, and issues it didn’t catch in QA.</p>
<p>So, there was a need to generate answers quickly and keep the team up to date on the latest fixes and information.</p>
<p>Efforts were made to collect questions that members might have. So, there was a fast-paced environment but there was a need to update it quickly and get it to the team member quickly. An internet page was there to dedicated the issues that members are facing and how to deal with them. That was still challenging to navigate for the team members. So, a better solution was required.</p>
<p><strong>Solution: Ask James</strong></p>
<p>James is a perfect combination of Knowledge Base and Digital Assistant. It has a Chat-based interface. So, instead of searching for information or putting keywords to get the right thing, it is easy to ask James to bring it to you. It provides information in Bite-sized nuggets and answers procedures & documents in the interface. James is based on a dynamic and powerful knowledge base that is easy to update and make it responsive to the needs of the team members. As the new information comes in, it is easy to come up and add that information to the content management system, and best of all, no need to spend much time to build James to bring this information out.</p>
<p>And because it is AI-based, James can access the website and then crawl the intranet site and gather the relevant info and tag that information with potential keywords and categories. This eliminates the efforts required to categorize. Team members can provide feedback to James on whether the information is useful or not and we can turn around to fine-tune the content based on the same. </p>
<p><strong><u>Results</u></strong></p>
<p>The team gets answers quickly, easily, asking natural language questions rather than keyword search terms. Responses are precise rather than a list of results. James has become a primary knowledge base. It has been observed that over 3500 questions were answered in the first two weeks, 50% decrease in 2nd level support calls, 15% decrease in handle time, 2.82 pts NPS increase, 91% Team approval means the team loved it.</p>
<p><strong><u>Lesson Learned</u></strong></p>
<p><em>Success is what happens when preparation meets opportunity. </em>And, here are some points that are worth to learn:</p>
<ul>
<li>Be willing to be Rogue – Be bold and ready to transform when and where it is required. Great things will happen automatically. </li>
<li>Leverage Enthusiasm - Find team members, managers, and peers who are excited about the prospects</li>
<li>Responsive Partner – Important to grow together</li>
<li>Content is King – Ensure that the information in the system is as per the requirements </li>
</ul>
<p>Artificial Intelligence is important as it enables us to complete a task with increased efficiency, effectiveness, and at a low cost. So, work on the needs of the organization, create a layout, and implement a strategy to adopt artificial intelligence to meet the set targets of the organization to best serve the members.</p></div>CUAS2018: Harnessing the Right Datahttps://culytics.com/blogs/cuas2018-harnessing-the-right-data2018-03-19T14:34:23.000Z2018-03-19T14:34:23.000ZSundeep Kapurhttps://culytics.com/members/SundeepKapur<div><p>More than 325 leaders in innovation from 160+ organizations got together for an incredible amount of learning at this year’s Credit Union Analytics Summit covering very important topics around big data and analytics – from business & technology considerations to consumer adoption – we spoke about trends and challenges faced. There were so many case studies shared – a lot of useful information – innovative, yet practical insight to drive success.</p>
<p>I took the liberty of taking key ideas from each presentation to share with our community:</p>
<p><strong>Mike Upton on Innovation:</strong> Look at your financial institution is an APP. Focus on creating efficient service interfaces. Omni channel will drive success. Omni is about remaining relevant, removing friction, and creating a culture within. Executive sponsorship is the most important success factor for Omni.</p>
<p><strong>Sandi Papenfuhs on Value of Analytics in Lending – Income:</strong> Sandi’s was able to nearly double the interest earned by focusing on income analytics strategies. Her focus was to analyze income numbers – stated, verified, and validated to arrive at strategies to make the First Tech card top of wallet.</p>
<p><strong>Roger Hull on Transactional Analytics:</strong> Roger spoke about reducing the time between getting insight and actually taking action. His presentation focused on leveraging machine learning capabilities to further operationalize insight resulting in more loans with less risk & a much better member experience.</p>
<p><strong>Michael Cochrum on Using Analytics to Drive Loan Portfolio Management Decisions:</strong> Michael spoke about keeping the underwriter involved in the lending process even after the loan has been made by AI. This underwriter feedback adds to their knowledge base and allows them to make even better decisions.</p>
<p><strong>Brian Knollenberg on a Machine Learning Trial:</strong> Brian spoke about how machine learning is helping drive results at BECU with initial projects in card, auto, checking, and mortgage. Machine learning can help quickly sift through a lot of data plus even make decisions based on patterns and expectations.</p>
<p><strong>Mike Terzian on The Power of Storytelling:</strong> Mike spoke about leveraging the influence of members – ‘social currency through members.’ In addition to deep dive analytics he spoke about the simplicity of campaigns – putting an offer out by featuring a “valuable” gift to drive uplift in campaigns.</p>
<p><strong>Naveen Jain on Influence:</strong> Simply said, what would you do if you knew who your most influential members were. Wouldn’t you treat them a little better? The power of focusing on this influencer segment will get you more from members & reduce attrition. Remember, recommendations from friends is the most credible form of advertising.</p>
<p><strong>Rob Silverii on Using Data to Drive Marketing Priorities & Content:</strong> Rob offered a systematic three step approach – use data to tell a story, align on a single metric, & iterate (and move) quickly. A simple image supported by data goes a long way in explaining things. And of course, “avoid the zombie dashboard.”</p>
<p><strong>Aaron Hill on Conjoint Analysis & Maximum Distance Scaling for Credit Unions:</strong> Aaron helped us answer a very simple yet powerful question, “Which topics should be on the program so that each person has at least one session that they really want to attend?” His approach allowed us to create a precise agenda & this methodology will help you resolve a number of CU “data choice” problems.</p>
<p><strong>Gary Angel on The New Frontier in Customer Experience Measurement:</strong> Gary asked a question, “Does the branch still matter” and provided some measurement strategies that are used in other industries including Wi-Fi, Mobile Apps, Passive Sniffers, & Video Cameras. And yes, the branch does matter.</p>
<p><strong>Jon Voorhees on Branch Distribution Analytics:</strong> Jon led the discussion on a simple question, “How many branches do I need?” Two concepts he shared were competitive saturation and branch density. He explained the efficiency ratio well – “How much expense does it take to generate revenue?”</p>
<p><strong>Ron Shevlin on Using Mobile Location Data to Improve Marketing Effectiveness:</strong> Ron spoke about studying path by understanding – where they went, how frequently, how long did they spend, & where did they go from there? Oh, but before you track your consumer make sure you are compliant.</p>
<p><strong>Adam Hass on Using Mobile App Analytics to Make Data Driven Decisions:</strong> Adam shared a very good graphic on important metrics from number of downloads, to retention rate, to number of users, to user journeys, to active users, all the way to conversion (and a few others in between).</p>
<p><strong>Manoj Rai on Analytics Driven Member Experience:</strong> Manoj made a simple yet very powerful statement – numbers don’t lie. His advice – look at data from a member centric perspective – observe them, understand them, and solve for what they want (and expect). Of course, keep tracking, keep improving.</p>
<p><strong>Joseph W. McLean on Fraud – A Moment That Matters:</strong> Joseph brought it home by asking a very simple question, “how you would feel if you were made to jump through hoops if you were the victim of fraud?” His systematic data driven approach leveraging a member first approach was extremely useful.</p>
<p><strong>Joel Hartzler on Data Analytics on Supporting Credit Union’s Members First Philosophy:</strong> Joel walked us through the evolution of our data journey. He spoke about achieving ROI – balancing business value and maturity – from what happened to why did it happen to what will happen to making it happen.</p>
<p><strong>Steven Simpson on Engagement Metric – Advanced Analytics:</strong> Steven’s message focused on achieving advanced analytics to power prescribed action. His framework of combining the channel (digital/traditional), with a message, at the right time (and context) was a powerful one.</p>
<p><strong>Brian Ley on Customer Graph Analytics – Humanizing Data:</strong> Brian spoke about identifying influencers and leveraging their connections to drive three to four times better results. He spoke about activating, influencing, and converting. Look hard he said, because “everyone is connected.”</p>
<p><strong>Khosrow Hassibi on Behavioral Predictive Modeling of Attrition in Financial Institutions:</strong> Khosrow shared a proven methodology of data analysis for attrition. Voluntary or involuntary, the ability to predict attrition in advance provides an opportunity to create proactive improvements.</p>
<p><strong>Nate Derby on Growth Through Member Centricity & Analytics:</strong> Nate helped define member centricity with this message, “focus on your most valuable members by aligning your products & services to serve those members” with this caveat – “the right member is always right.”</p>
<p><strong>Dave Ulrich on Credit Risk Analytics – Preparing for CECL:</strong> Dave described First Tech’s approach to CECL & capital planning so they can provide & plan for what they think will happen. This approach to risk-based pricing will help them offer a fair price for every member and stay compliant.</p>
<p><strong>Karan Bhalla on Small to Big – Credit Unions CAN Use Analytics to Win:</strong> Karan spoke about a five-step journey – make a commitment, allocate a budget, obtain talent, small manageable projects, & keep improving. A key reason for failure – inadequate resources and technology.</p>
<p><strong>Matthew Maguire on 4 Ways to Make Data Your Best Digital Transformation Asset:</strong> Matt’s session focused on positioning – top of wallet becomes top of device. He spoke about integrating utility functions into your applications thereby offering consumers convenience & reasons for top of wallet.</p>
<p><strong>Sam Maule on Barbarians at the Gate:</strong> Sam spoke about the future of digitized objects aka Digital RICHES – Real-time, Intelligent, Contextual, Human, Extendable, Social. Your mantra - use digital capabilities to deliver valuable services to consumers who are underserved or overcharged.</p>
<p><strong>Paul Ablack on The Analytics Journey @ Ideal Credit Union:</strong> Paul’s message was on the mark – what can you do to get your member to transact more often. He explained the value of nurturing by sharing a successful member VIP program case study – analytics & digital make for a powerful combination.</p>
<p><strong>Anne Legg on Drowning in Data & Starving for Insight? How to Fuel Your Credit Union Growth:</strong> Success comes through effort, you can decipher intent & effort by deciphering data. Anne’s message - leverage predictive analytics to customize what you can offer & improve operational efficiencies.</p>
<p><strong>Sundeep Kapur on Selling, Starting, & Effectively Executing a Big Data Project:</strong> I shared three successful case studies and offered a five-step process to chart a big data project. Start with a decision discovery workshop (educational), conduct an analytics assessment, map prioritized big data journeys, focus on continuous improvement, & instill analytics expertise within your organization.</p>
<p><strong>Andre Iervolino on Big Data, Small Data, But What About the Right Data:</strong> Andre prioritizes big data projects on their ability to deliver on revenue. He walked through the process of creating an end to end data success strategy including defining a clear vision, mission, & specific tactics including measurement.</p>
<p><a href="http://storage.ning.com/topology/rest/1.0/file/get/839256806?profile=original" target="_self"><img class="align-full" src="http://storage.ning.com/topology/rest/1.0/file/get/839256806?profile=RESIZE_1024x1024" width="750"></a></p>
<p><strong>Concluding Thoughts:</strong> So, what should we expect in the future?</p>
<p>Five key trends are driving innovation - there is a tremendous amount of data, artificial intelligence to help us sift through this data, connectivity to disseminate information & services expeditiously, consumer adoption of technology, and a world that is going to a mobile first strategy.</p>
<p>The future lies in digitized objects (better API’s), omni-channel integration, & intelligent (AI based) digital services. The financial institution of the future will be built on an API providing real-time seamless services to consumers.</p>
<p>As an attendee of this event I can assure you that the interaction and learning was phenomenal. This conference has grown from 100+ to 200+ to many more than 300. We look forward to a continued year of learning & an even better conference in 2019!</p></div>