The Future of Banking Technology Is Here

The future of bank­ing tech­nol­o­gy is not some­thing the aver­age per­son thinks about, and we usu­al­ly take our rela­tion­ship with our bank for grant­ed until some­thing goes wrong—such as los­ing your wal­let. That’s exact­ly what hap­pened to me a few weeks ago, and although I’m gen­er­al­ly hap­py with the ser­vice my bank pro­vides, the loss of my deb­it and cred­it cards plunged me into a night­mare of red tape.

Sev­er­al days after los­ing my cards, I received a let­ter in the post, warn­ing me about fraud­u­lent activ­i­ty that had already tak­en place on my account, which my bank hadn’t pre­vent­ed. I had to sched­ule time to vis­it the branch to sort this out, since my bank didn’t allow me to talk with a man­ag­er online.

As I stood at the back of a long queue, anx­ious and pan­icked, I thought of all the ways the bank could have han­dled this expe­ri­ence more effec­tive­ly. For exam­ple, they should have detect­ed that a thief was try­ing to use my deb­it card at an ATM before they placed a charge on it, because it clear­ly was not me at that loca­tion. They should have alert­ed me instan­ta­neous­ly, via a mes­sage on my phone. And I should have been able to sort out the issue and order new cards online, sav­ing me a dri­ve to the branch.

The tech­nol­o­gy for every one of these improve­ments already exists. In a vari­ety of indus­tries, arti­fi­cial intel­li­gence (AI) and machine learn­ing (ML) already enhance and stream­line cus­tomer expe­ri­ences. Now cus­tomers are increas­ing­ly expecting—and demanding—that banks adopt these solu­tions as well.

Here’s what the future of finan­cial ser­vices looks like.

Three key trends dri­ving dis­rup­tion in the bank­ing industry

• First, dig­i­tal is dri­ving cus­tomer demands and expec­ta­tions, espe­cial­ly when it comes to bank­ing now. This is par­tic­u­lar­ly true of cus­tomers who’ve grown up with the web at their fin­ger­tips. A recent Visa Dig­i­tal Pay­ments study found that 69 per­cent of Euro­pean mil­len­ni­als reg­u­lar­ly man­age their mon­ey via mobile devices.
• Sec­ond, a new wave of fin­tech com­pa­nies (such as True Lay­er, Pay­base, and Trans­fer­Wise) is dis­rupt­ing the old high-street bank par­a­digm. These agile new play­ers under­stand where the mar­ket is head­ing and what their audi­ences want. They’re nim­ble, unen­cum­bered by the com­plex­i­ty (and in many cas­es, reg­u­la­to­ry red tape) slow­ing down big­ger banks.
• Third, today’s reg­u­la­to­ry envi­ron­ment cre­ates a lot of mov­ing tar­gets. In an effort to ensure reg­u­la­to­ry com­pli­ance, many high-street banks shy away from dis­rup­tive tech­nolo­gies, tak­ing their eyes off expe­ri­ence-led efforts to focus on safe­guard­ing cus­tomer pri­va­cy. While this sounds like a ben­e­fit, the cus­tomer of tomor­row already expects both pos­i­tive expe­ri­ences AND tight secu­ri­ty. If a bank boasts that they are the most secure option avail­able yet make the con­sumer jump through hoops in order to enjoy the secu­ri­ty advan­tages, it will nev­er be a win. In fact, a friend of mine, who banked with a lead­ing insti­tu­tion for over two decades, changed providers last week after she found her­self in a for­eign coun­try with no access to funds after hav­ing gone through the fifth hold on her account in just three months due to sus­pect­ed fraud­u­lent activ­i­ty. In her words: “I trav­el a lot. I always let them know where and when I am going. I will not put up with incon­ve­nience when I fol­low their rules and still get penalised.”

Many banks are begin­ning to lever­age the pow­er of AI and ML to help address these chal­lenges. By let­ting com­put­ers do the heavy lift­ing, they free their mar­ket­ing experts to iden­ti­fy new ways to enhance the cus­tomer experience.

Per­son­al­is­ing experiences

Although AI and ML are fre­quent­ly used buzz­words, few real­ly under­stand their impli­ca­tions. Plat­forms such as Adobe Sen­sei make their ben­e­fits con­crete by using intel­li­gent auto­mat­ed tar­get­ing to deter­mine which expe­ri­ences are best suit­ed for which customers.

For exam­ple, say you’re run­ning an A/B test on your web­site to deter­mine which home­page lay­out gen­er­ates the most con­ver­sions. After an ini­tial test, you’ve deter­mined that lay­out A gen­er­ates a 50 per­cent con­ver­sion rate, where­as lay­out B gen­er­ates a 20 per­cent con­ver­sion. Is lay­out A the only win­ner? After all, 20 per­cent of your vis­i­tors are still con­vert­ing in response to lay­out B, which means you need to con­tin­ue serv­ing lay­out B to that audi­ence seg­ment. It would, how­ev­er, take you days, if not months, to trawl through the data to find the char­ac­ter­is­tics of the peo­ple who liked lay­out B, though.

This is where machine learn­ing comes in. When a new vis­i­tor arrives on your home­page, the algo­rithm can analyse data you’ve already acquired about that per­son, recog­nise that they’re like­ly to pre­fer lay­out B, and then serve them lay­out B, increas­ing the like­li­hood that they’ll con­vert. This is known as auto­mat­ed tar­get­ing, and a grow­ing num­ber of FSI organ­i­sa­tions are adopt­ing it today.

But tru­ly per­son­alised cus­tomer expe­ri­ences aren’t lim­it­ed to your web­site. AI and ML real­ly shine when you imple­ment them across all channels.

Inte­grat­ed communication

Tools such as Adobe’s Expe­ri­ence Cloud ensure that time­ly com­mu­ni­ca­tion is deliv­ered to every cus­tomer, via any dig­i­tal chan­nel nec­es­sary. And by putting togeth­er data from mul­ti­ple chan­nels, the Adobe Expe­ri­ence Cloud helps weave a seam­less expe­ri­ence across web and branch. Per­son­alised expe­ri­ences are just the begin­ning of the ben­e­fits AI and ML can deliv­er. To see their true pow­er in action, you’ve got to see what these tech­nolo­gies can do when some­thing goes wrong.

Detect­ing anomalies

One way for banks to pre­vent the kind of fraud­u­lent activ­i­ty I expe­ri­enced is to use facial aware­ness and bio­met­rics to detect that the per­son using my card isn’t actu­al­ly me. Adobe has been devel­op­ing AI and ML in its Cloud prod­ucts, such as Light­room, Stock, and Expe­ri­ence Man­ag­er for years, devel­op­ing enhanced object recog­ni­tion capa­bil­i­ties that can help iden­ti­fy fraud­sters and alert banks to take action. Here’s a video demon­strat­ing how this process could come together.

In the video, you saw an ATM using object recog­ni­tion with facial aware­ness to assist in fraud detec­tion. Although the process looks seam­less on the customer’s end, the AI is work­ing hard behind the scenes, auto­mat­i­cal­ly send­ing a mes­sage to the bank man­ag­er and a text to the cus­tomer when the fraud is detected.

Through all of these devel­op­ments and dis­rup­tors, the core prin­ci­ples of FSI cus­tomer ser­vice remain the same. As always, con­sumers expect con­ve­nience, per­son­alised ser­vice, rapid respon­sive­ness, and atten­tion to detail. As bank­ing moves into the future, AI and ML allow FSI com­pa­nies to deliv­er these ben­e­fits more effec­tive­ly than ever before. Click here to read more from me about tech­no­log­i­cal trends affect­ing the retail bank­ing industry.